From cac5c9c951abf2c672075eb950382876b19ac808 Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 14:42:36 -0700
Subject: [PATCH 01/10] Refactor `search_and_download` into multiple functions

This is groundwork for developing a more flexible API. Instead of always just
downloading anything that matches search results and then reading it, users will
be able to individually:

* Search for data
* Download data
* Read data
---
 src/nsidc/iceflow/api.py         |  6 +--
 src/nsidc/iceflow/data/fetch.py  | 77 +++++++++++++++++++++-----------
 src/nsidc/iceflow/data/models.py | 10 +++++
 3 files changed, 64 insertions(+), 29 deletions(-)

diff --git a/src/nsidc/iceflow/api.py b/src/nsidc/iceflow/api.py
index 25e353c..f3cd0e3 100644
--- a/src/nsidc/iceflow/api.py
+++ b/src/nsidc/iceflow/api.py
@@ -29,8 +29,7 @@ def _df_for_one_dataset(
     output_itrf: str | None,
 ) -> IceflowDataFrame:
     results = search_and_download(
-        short_name=dataset.short_name,
-        version=dataset.version,
+        dataset=dataset,
         bounding_box=bounding_box,
         temporal=temporal,
         output_dir=output_dir,
@@ -120,8 +119,7 @@ def create_iceflow_parquet(
 
     for dataset in dataset_search_params.datasets:
         results = search_and_download(
-            short_name=dataset.short_name,
-            version=dataset.version,
+            dataset=dataset,
             temporal=dataset_search_params.temporal,
             bounding_box=dataset_search_params.bounding_box,
             output_dir=output_dir,
diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index da05eeb..5742426 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -6,32 +6,25 @@
 import earthaccess
 from loguru import logger
 
-from nsidc.iceflow.data.models import BoundingBox
+from nsidc.iceflow.data.models import BoundingBox, Dataset, IceflowSearchResult
 
 
-def search_and_download(
+def _find_iceflow_data(
     *,
-    version: str,
-    short_name: str,
+    dataset: Dataset,
     bounding_box: BoundingBox,
     temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date],
-    output_dir: Path,
-) -> list[Path]:
-    """Search and download data.
-
-    Wraps EDL auth and CMR search using `earthaccess`.
-
-    Data matching the given parameters are downloaded to a subfolder of the
-    given `output_dir` named after the `short_name`.
-    """
+) -> IceflowSearchResult:
     earthaccess.login()
 
-    ctx_string = f"{short_name=} {version=} with {bounding_box=} {temporal=}"
+    ctx_string = (
+        f"{dataset.short_name=} {dataset.version=} with {bounding_box=} {temporal=}"
+    )
 
     try:
-        results = earthaccess.search_data(
-            short_name=short_name,
-            version=version,
+        granules_list = earthaccess.search_data(
+            short_name=dataset.short_name,
+            version=dataset.version,
             bounding_box=(
                 bounding_box.lower_left_lon,
                 bounding_box.lower_left_lat,
@@ -42,27 +35,61 @@ def search_and_download(
         )
     except IndexError:
         # There's no data matching the given parameters.
-        logger.error(f"Found no results for {ctx_string}")
-        return []
+        granules_list = []
 
-    num_results = len(results)
+    num_results = len(granules_list)
 
     if not num_results:
         logger.error(f"Found no results for {ctx_string}")
-        return []
+        granules_list = []
+
+    iceflow_search_result = IceflowSearchResult(dataset=dataset, granules=granules_list)
+    return iceflow_search_result
+
 
+def _download_iceflow_results(
+    *, iceflow_results: IceflowSearchResult, output_dir: Path
+) -> list[Path]:
     # short_name based subdir for data.
-    output_subdir = output_dir / short_name
+    output_subdir = output_dir / iceflow_results.dataset.short_name
     logger.info(
-        f"Found {num_results} granules for {ctx_string}."
-        f" Downloading to {output_subdir}."
+        f"Downloading {len(iceflow_results.granules)} granules" f" to {output_subdir}."
     )
 
     output_subdir.mkdir(exist_ok=True)
-    downloaded_files = earthaccess.download(results, str(output_subdir))
+    downloaded_files = earthaccess.download(
+        iceflow_results.granules, str(output_subdir)
+    )
     downloaded_filepaths = [Path(filepath_str) for filepath_str in downloaded_files]
     # There may be duplicate filepaths returned by earthaccess because of data
     # existing both in the cloud and on ECS.
     downloaded_filepaths = list(set(downloaded_filepaths))
 
     return downloaded_filepaths
+
+
+def search_and_download(
+    *,
+    dataset: Dataset,
+    bounding_box: BoundingBox,
+    temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date],
+    output_dir: Path,
+) -> list[Path]:
+    """Search and download data.
+
+    Wraps EDL auth and CMR search using `earthaccess`.
+
+    Data matching the given parameters are downloaded to a subfolder of the
+    given `output_dir` named after the `short_name`.
+    """
+    iceflow_results = _find_iceflow_data(
+        dataset=dataset,
+        bounding_box=bounding_box,
+        temporal=temporal,
+    )
+
+    downloaded_filepaths = _download_iceflow_results(
+        iceflow_results=iceflow_results, output_dir=output_dir
+    )
+
+    return downloaded_filepaths
diff --git a/src/nsidc/iceflow/data/models.py b/src/nsidc/iceflow/data/models.py
index 20125f0..ec1630d 100644
--- a/src/nsidc/iceflow/data/models.py
+++ b/src/nsidc/iceflow/data/models.py
@@ -5,6 +5,7 @@
 
 import pandera as pa
 import pydantic
+from earthaccess.results import DataGranule
 from pandera.typing import DataFrame, Index, Series
 
 from nsidc.iceflow.itrf import ITRF_REGEX
@@ -235,3 +236,12 @@ class DatasetSearchParameters(pydantic.BaseModel):
     datasets: list[Dataset]
     bounding_box: BoundingBox
     temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date]
+
+
+class IceflowSearchResult(pydantic.BaseModel):
+    dataset: Dataset
+    granules: list[DataGranule]
+
+    # Pydantic can't infer what `DataGranule` is. This ignores validation for
+    # this that type
+    model_config = pydantic.ConfigDict(arbitrary_types_allowed=True)

From 1c2af83bb4ded452d6353d2dbfa5d1ff51f3aa4f Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 14:57:58 -0700
Subject: [PATCH 02/10] Add function to find iceflow data based on
 `DatasetSearchParameters`

And improve kwarg/variable naming
---
 src/nsidc/iceflow/data/fetch.py  | 44 +++++++++++++++++++++++++-------
 src/nsidc/iceflow/data/models.py |  3 +++
 2 files changed, 38 insertions(+), 9 deletions(-)

diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index 5742426..a01c8e1 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -6,7 +6,13 @@
 import earthaccess
 from loguru import logger
 
-from nsidc.iceflow.data.models import BoundingBox, Dataset, IceflowSearchResult
+from nsidc.iceflow.data.models import (
+    BoundingBox,
+    Dataset,
+    DatasetSearchParameters,
+    IceflowSearchResult,
+    IceflowSearchResults,
+)
 
 
 def _find_iceflow_data(
@@ -47,18 +53,21 @@ def _find_iceflow_data(
     return iceflow_search_result
 
 
-def _download_iceflow_results(
-    *, iceflow_results: IceflowSearchResult, output_dir: Path
+def _download_iceflow_search_result(
+    *,
+    iceflow_search_result: IceflowSearchResult,
+    output_dir: Path,
 ) -> list[Path]:
     # short_name based subdir for data.
-    output_subdir = output_dir / iceflow_results.dataset.short_name
+    output_subdir = output_dir / iceflow_search_result.dataset.short_name
     logger.info(
-        f"Downloading {len(iceflow_results.granules)} granules" f" to {output_subdir}."
+        f"Downloading {len(iceflow_search_result.granules)} granules"
+        f" to {output_subdir}."
     )
 
     output_subdir.mkdir(exist_ok=True)
     downloaded_files = earthaccess.download(
-        iceflow_results.granules, str(output_subdir)
+        iceflow_search_result.granules, str(output_subdir)
     )
     downloaded_filepaths = [Path(filepath_str) for filepath_str in downloaded_files]
     # There may be duplicate filepaths returned by earthaccess because of data
@@ -82,14 +91,31 @@ def search_and_download(
     Data matching the given parameters are downloaded to a subfolder of the
     given `output_dir` named after the `short_name`.
     """
-    iceflow_results = _find_iceflow_data(
+    iceflow_search_result = _find_iceflow_data(
         dataset=dataset,
         bounding_box=bounding_box,
         temporal=temporal,
     )
 
-    downloaded_filepaths = _download_iceflow_results(
-        iceflow_results=iceflow_results, output_dir=output_dir
+    downloaded_filepaths = _download_iceflow_search_result(
+        iceflow_search_result=iceflow_search_result,
+        output_dir=output_dir,
     )
 
     return downloaded_filepaths
+
+
+def find_iceflow_data(
+    *,
+    dataset_search_params: DatasetSearchParameters,
+) -> IceflowSearchResults:
+    iceflow_search_results = []
+    for dataset in dataset_search_params.datasets:
+        iceflow_search_result = _find_iceflow_data(
+            dataset=dataset,
+            bounding_box=dataset_search_params.bounding_box,
+            temporal=dataset_search_params.temporal,
+        )
+        iceflow_search_results.append(iceflow_search_result)
+
+    return iceflow_search_results
diff --git a/src/nsidc/iceflow/data/models.py b/src/nsidc/iceflow/data/models.py
index ec1630d..0ec8208 100644
--- a/src/nsidc/iceflow/data/models.py
+++ b/src/nsidc/iceflow/data/models.py
@@ -245,3 +245,6 @@ class IceflowSearchResult(pydantic.BaseModel):
     # Pydantic can't infer what `DataGranule` is. This ignores validation for
     # this that type
     model_config = pydantic.ConfigDict(arbitrary_types_allowed=True)
+
+
+IceflowSearchResults = list[IceflowSearchResult]

From 3efd690132d9fb20c45cd8b8bebf5602dbc7cf22 Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 15:11:36 -0700
Subject: [PATCH 03/10] Search results are downloaded to subdir based on
 short_name and version

---
 src/nsidc/iceflow/data/fetch.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index a01c8e1..3bfa934 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -58,8 +58,10 @@ def _download_iceflow_search_result(
     iceflow_search_result: IceflowSearchResult,
     output_dir: Path,
 ) -> list[Path]:
-    # short_name based subdir for data.
-    output_subdir = output_dir / iceflow_search_result.dataset.short_name
+    # short_name and version-based subdir for data.
+    subdir_name = f"{iceflow_search_result.dataset.short_name}_{iceflow_search_result.dataset.version}"
+    output_subdir = output_dir / subdir_name
+
     logger.info(
         f"Downloading {len(iceflow_search_result.granules)} granules"
         f" to {output_subdir}."
@@ -89,7 +91,7 @@ def search_and_download(
     Wraps EDL auth and CMR search using `earthaccess`.
 
     Data matching the given parameters are downloaded to a subfolder of the
-    given `output_dir` named after the `short_name`.
+    given `output_dir` named after the `short_name` and `version`.
     """
     iceflow_search_result = _find_iceflow_data(
         dataset=dataset,

From 6b15bef547cc68c7a0e4d53279e0bfb082dbe2df Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 16:41:06 -0700
Subject: [PATCH 04/10] Search for data across all supported datasets by
 default

---
 src/nsidc/iceflow/data/__init__.py | 15 ++++++++-------
 src/nsidc/iceflow/data/models.py   | 12 +++++++++++-
 2 files changed, 19 insertions(+), 8 deletions(-)

diff --git a/src/nsidc/iceflow/data/__init__.py b/src/nsidc/iceflow/data/__init__.py
index 3eb4547..7855f29 100644
--- a/src/nsidc/iceflow/data/__init__.py
+++ b/src/nsidc/iceflow/data/__init__.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from nsidc.iceflow.data.models import (
+    ALL_DATASETS,
     BLATM1BDataset,
     Dataset,
     GLAH06Dataset,
@@ -8,11 +9,11 @@
     ILVIS2Dataset,
 )
 
-ALL_DATASETS: list[Dataset] = [
-    ILATM1BDataset(version="1"),
-    ILATM1BDataset(version="2"),
-    BLATM1BDataset(version="1"),
-    ILVIS2Dataset(version="1"),
-    ILVIS2Dataset(version="2"),
-    GLAH06Dataset(),
+__all__ = [
+    "ALL_DATASETS",
+    "BLATM1BDataset",
+    "Dataset",
+    "GLAH06Dataset",
+    "ILATM1BDataset",
+    "ILVIS2Dataset",
 ]
diff --git a/src/nsidc/iceflow/data/models.py b/src/nsidc/iceflow/data/models.py
index 0ec8208..1eb9ffb 100644
--- a/src/nsidc/iceflow/data/models.py
+++ b/src/nsidc/iceflow/data/models.py
@@ -232,8 +232,18 @@ class BoundingBox(pydantic.BaseModel):
     upper_right_lat: float
 
 
+ALL_DATASETS: list[Dataset] = [
+    ILATM1BDataset(version="1"),
+    ILATM1BDataset(version="2"),
+    BLATM1BDataset(version="1"),
+    ILVIS2Dataset(version="1"),
+    ILVIS2Dataset(version="2"),
+    GLAH06Dataset(),
+]
+
+
 class DatasetSearchParameters(pydantic.BaseModel):
-    datasets: list[Dataset]
+    datasets: list[Dataset] = ALL_DATASETS
     bounding_box: BoundingBox
     temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date]
 

From d0c7ae00e19c4d4a847317450f0e9e8eeb7d2ba1 Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 16:42:37 -0700
Subject: [PATCH 05/10] Update api to use newly created fetch/read funcs

---
 src/nsidc/iceflow/api.py        | 129 ++++++++++++--------------------
 src/nsidc/iceflow/data/fetch.py |  15 ++++
 src/nsidc/iceflow/data/read.py  |  54 ++++++-------
 3 files changed, 93 insertions(+), 105 deletions(-)

diff --git a/src/nsidc/iceflow/api.py b/src/nsidc/iceflow/api.py
index f3cd0e3..e2e2163 100644
--- a/src/nsidc/iceflow/api.py
+++ b/src/nsidc/iceflow/api.py
@@ -1,56 +1,20 @@
 from __future__ import annotations
 
-import datetime as dt
 import shutil
 from pathlib import Path
 
 import dask.dataframe as dd
-import pandas as pd
 from loguru import logger
 
-from nsidc.iceflow.data.fetch import search_and_download
+from nsidc.iceflow.data.fetch import download_iceflow_results, find_iceflow_data
 from nsidc.iceflow.data.models import (
-    BoundingBox,
-    Dataset,
     DatasetSearchParameters,
     IceflowDataFrame,
 )
-from nsidc.iceflow.data.read import read_data
+from nsidc.iceflow.data.read import read_iceflow_datafiles
 from nsidc.iceflow.itrf.converter import transform_itrf
 
 
-def _df_for_one_dataset(
-    *,
-    dataset: Dataset,
-    bounding_box: BoundingBox,
-    temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date],
-    output_dir: Path,
-    # TODO: also add option for target epoch!!
-    output_itrf: str | None,
-) -> IceflowDataFrame:
-    results = search_and_download(
-        dataset=dataset,
-        bounding_box=bounding_box,
-        temporal=temporal,
-        output_dir=output_dir,
-    )
-
-    all_dfs = []
-    for result in results:
-        data_df = read_data(dataset, result)
-        all_dfs.append(data_df)
-
-    complete_df = IceflowDataFrame(pd.concat(all_dfs))
-
-    if output_itrf is not None:
-        complete_df = transform_itrf(
-            data=complete_df,
-            target_itrf=output_itrf,
-        )
-
-    return complete_df
-
-
 def fetch_iceflow_df(
     *,
     dataset_search_params: DatasetSearchParameters,
@@ -70,20 +34,24 @@ def fetch_iceflow_df(
     format.
     """
 
-    dfs = []
-    for dataset in dataset_search_params.datasets:
-        result = _df_for_one_dataset(
-            dataset=dataset,
-            temporal=dataset_search_params.temporal,
-            bounding_box=dataset_search_params.bounding_box,
-            output_dir=output_dir,
-            output_itrf=output_itrf,
-        )
-        dfs.append(result)
+    iceflow_search_reuslts = find_iceflow_data(
+        dataset_search_params=dataset_search_params,
+    )
+
+    downloaded_files = download_iceflow_results(
+        iceflow_search_results=iceflow_search_reuslts,
+        output_dir=output_dir,
+    )
+
+    iceflow_df = read_iceflow_datafiles(downloaded_files)
 
-    complete_df = IceflowDataFrame(pd.concat(dfs))
+    if output_itrf is not None:
+        iceflow_df = transform_itrf(
+            data=iceflow_df,
+            target_itrf=output_itrf,
+        )
 
-    return complete_df
+    return iceflow_df
 
 
 def create_iceflow_parquet(
@@ -117,41 +85,42 @@ def create_iceflow_parquet(
                 "An iceflow parquet file already exists. Use `overwrite=True` to overwrite."
             )
 
-    for dataset in dataset_search_params.datasets:
-        results = search_and_download(
-            dataset=dataset,
-            temporal=dataset_search_params.temporal,
-            bounding_box=dataset_search_params.bounding_box,
+    iceflow_search_results = find_iceflow_data(
+        dataset_search_params=dataset_search_params,
+    )
+
+    for iceflow_search_result in iceflow_search_results:
+        downloaded_files = download_iceflow_results(
+            iceflow_search_results=[iceflow_search_result],
             output_dir=output_dir,
         )
 
-        for result in results:
-            data_df = read_data(dataset, result)
-            df = IceflowDataFrame(data_df)
+        iceflow_df = read_iceflow_datafiles(downloaded_files)
 
-            df = transform_itrf(
-                data=df,
-                target_itrf=target_itrf,
-                target_epoch=target_epoch,
-            )
+        iceflow_df = transform_itrf(
+            data=iceflow_df,
+            target_itrf=target_itrf,
+            target_epoch=target_epoch,
+        )
 
-            # Add a string col w/ dataset name and version.
-            df["dataset"] = [f"{dataset.short_name}v{dataset.version}"] * len(
-                df.latitude
+        # Add a string col w/ dataset name and version.
+        dataset = iceflow_search_result.dataset
+        iceflow_df["dataset"] = [f"{dataset.short_name}v{dataset.version}"] * len(
+            iceflow_df.latitude
+        )
+        common_columns = ["latitude", "longitude", "elevation", "dataset"]
+        common_dask_df = dd.from_pandas(iceflow_df[common_columns])  # type: ignore[attr-defined]
+        if output_subdir.exists():
+            dd.to_parquet(  # type: ignore[attr-defined]
+                df=common_dask_df,
+                path=output_subdir,
+                append=True,
+                ignore_divisions=True,
+            )
+        else:
+            dd.to_parquet(  # type: ignore[attr-defined]
+                df=common_dask_df,
+                path=output_subdir,
             )
-            common_columns = ["latitude", "longitude", "elevation", "dataset"]
-            common_dask_df = dd.from_pandas(df[common_columns])  # type: ignore[attr-defined]
-            if output_subdir.exists():
-                dd.to_parquet(  # type: ignore[attr-defined]
-                    df=common_dask_df,
-                    path=output_subdir,
-                    append=True,
-                    ignore_divisions=True,
-                )
-            else:
-                dd.to_parquet(  # type: ignore[attr-defined]
-                    df=common_dask_df,
-                    path=output_subdir,
-                )
 
     return output_subdir
diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index 3bfa934..e17eee4 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -121,3 +121,18 @@ def find_iceflow_data(
         iceflow_search_results.append(iceflow_search_result)
 
     return iceflow_search_results
+
+
+def download_iceflow_results(
+    iceflow_search_results: IceflowSearchResults,
+    output_dir: Path,
+) -> list[Path]:
+    all_downloaded_files = []
+    for iceflow_search_result in iceflow_search_results:
+        downloaded_filepaths = _download_iceflow_search_result(
+            iceflow_search_result=iceflow_search_result,
+            output_dir=output_dir,
+        )
+        all_downloaded_files.extend(downloaded_filepaths)
+
+    return all_downloaded_files
diff --git a/src/nsidc/iceflow/data/read.py b/src/nsidc/iceflow/data/read.py
index 8440262..06614e7 100644
--- a/src/nsidc/iceflow/data/read.py
+++ b/src/nsidc/iceflow/data/read.py
@@ -1,41 +1,45 @@
 from __future__ import annotations
 
-import functools
 from pathlib import Path
 
+import pandas as pd
+
 from nsidc.iceflow.data.atm1b import atm1b_data
 from nsidc.iceflow.data.glah06 import glah06_data
 from nsidc.iceflow.data.ilvis2 import ilvis2_data
 from nsidc.iceflow.data.models import (
     ATM1BDataFrame,
-    ATM1BDataset,
-    Dataset,
     GLAH06DataFrame,
-    GLAH06Dataset,
     IceflowDataFrame,
     ILVIS2DataFrame,
-    ILVIS2Dataset,
 )
 
 
-@functools.singledispatch
-def read_data(
-    dataset: Dataset, _filepath: Path
+def read_iceflow_datafile(
+    filepath: Path,
 ) -> IceflowDataFrame | ATM1BDataFrame | ILVIS2DataFrame | GLAH06DataFrame:
-    msg = f"{dataset=} not recognized."
-    raise RuntimeError(msg)
-
-
-@read_data.register
-def _(_dataset: ATM1BDataset, filepath: Path) -> ATM1BDataFrame:
-    return atm1b_data(filepath)
-
-
-@read_data.register
-def _(_dataset: ILVIS2Dataset, filepath: Path) -> ILVIS2DataFrame:
-    return ilvis2_data(filepath)
-
-
-@read_data.register
-def _(_dataset: GLAH06Dataset, filepath: Path) -> GLAH06DataFrame:
-    return glah06_data(filepath)
+    # iceflow data are expected to exist in a directory named like
+    # `{short_name}_{version}`
+    dataset_subdir = filepath.parent.name
+    short_name, _version = dataset_subdir.split("_")
+
+    if short_name in ["ILATM1B", "BLATM1B"]:
+        return atm1b_data(filepath)
+    elif short_name == "ILVIS2":
+        return ilvis2_data(filepath)
+    elif short_name == "GLAH06":
+        return glah06_data(filepath)
+    else:
+        err_msg = f"Unrecognized dataset {short_name=} extracted from {filepath.parent}"
+        raise RuntimeError(err_msg)
+
+
+def read_iceflow_datafiles(filepaths: list[Path]) -> IceflowDataFrame:
+    all_dfs = []
+    for filepath in filepaths:
+        df = read_iceflow_datafile(filepath)
+        all_dfs.append(df)
+
+    complete_df = IceflowDataFrame(pd.concat(all_dfs))
+
+    return complete_df

From 1880fd2953cfb1cf93ddf2beda2bacfa13a1cd11 Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Fri, 8 Nov 2024 16:46:25 -0700
Subject: [PATCH 06/10] Remove OBE `search_and_download`

---
 src/nsidc/iceflow/data/fetch.py | 28 ----------------------------
 1 file changed, 28 deletions(-)

diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index e17eee4..64f2817 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -79,34 +79,6 @@ def _download_iceflow_search_result(
     return downloaded_filepaths
 
 
-def search_and_download(
-    *,
-    dataset: Dataset,
-    bounding_box: BoundingBox,
-    temporal: tuple[dt.datetime | dt.date, dt.datetime | dt.date],
-    output_dir: Path,
-) -> list[Path]:
-    """Search and download data.
-
-    Wraps EDL auth and CMR search using `earthaccess`.
-
-    Data matching the given parameters are downloaded to a subfolder of the
-    given `output_dir` named after the `short_name` and `version`.
-    """
-    iceflow_search_result = _find_iceflow_data(
-        dataset=dataset,
-        bounding_box=bounding_box,
-        temporal=temporal,
-    )
-
-    downloaded_filepaths = _download_iceflow_search_result(
-        iceflow_search_result=iceflow_search_result,
-        output_dir=output_dir,
-    )
-
-    return downloaded_filepaths
-
-
 def find_iceflow_data(
     *,
     dataset_search_params: DatasetSearchParameters,

From ae44677c4602f96666a3abbe39f95832b11e5cee Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Mon, 9 Dec 2024 10:33:16 -0700
Subject: [PATCH 07/10] Improve API around finding, downloading, and accessing
 data.

Also improve the documentation!!
---
 docs/getting-started.md             | 111 +++++++++++++
 docs/index.md                       |   1 +
 notebooks/iceflow-example.ipynb     |  59 ++++++-
 notebooks/iceflow-with-icepyx.ipynb | 248 +++++++---------------------
 src/nsidc/iceflow/__init__.py       |  43 ++++-
 src/nsidc/iceflow/api.py            |  57 ++++---
 src/nsidc/iceflow/data/fetch.py     |   5 +-
 src/nsidc/iceflow/data/models.py    |   4 +
 tests/integration/test_e2e.py       |  50 +++++-
 9 files changed, 352 insertions(+), 226 deletions(-)
 create mode 100644 docs/getting-started.md

diff --git a/docs/getting-started.md b/docs/getting-started.md
new file mode 100644
index 0000000..be47a41
--- /dev/null
+++ b/docs/getting-started.md
@@ -0,0 +1,111 @@
+# Getting started with iceflow
+
+## Jupyter Notebooks
+
+[Jupyter notebooks](https://docs.jupyter.org/en/latest/) provide executable
+examples of how to use `iceflow`:
+
+- [iceflow-example.ipynb](./iceflow-example.ipynb) provides an example of how to
+  search for, download, and interact with `ILATM1B v1` data for a small area of
+  interest. This notebook also illustrates how to perform
+  [ITRF](https://itrf.ign.fr/) transformations to facilitate comparisons across
+  datasets. To learn more about ITRF transformations, see the
+  [corrections.ipynb](https://github.com/nsidc/NSIDC-Data-Tutorials/blob/main/notebooks/iceflow/corrections.ipynb)
+  notebook in the
+  [NSIDC-Data-Tutorials GitHub repository](https://github.com/nsidc/NSIDC-Data-Tutorials).
+
+- [iceflow-with-icepyx.ipynb](./iceflow-with-icepyx.ipynb) shows how to search
+  for, download, and interact with a large amount of data across many datasets
+  supported by `iceflow`. It also illustrates how to utilize
+  [icepyx](https://icepyx.readthedocs.io/en/latest/) to find and access ICESat-2
+  data. Finally, the notebook provides a simple time-series analysis for
+  elevation change over an area of interest across `iceflow` supported datasets
+  and ICESat-2.
+
+## API overview
+
+`iceflow` provides a simple API for finding, downloading, and accessing
+iceflow-supported datasets.
+
+### Finding data
+
+To find `iceflow`-supported data for an area of interest and timeframe, use
+[`find_iceflow_data`](nsidc.iceflow.find_iceflow_data):
+
+```
+import datetime as dt
+
+from nsidc.iceflow import (
+    find_iceflow_data,
+    DatasetSearchParameters,
+    BoundingBox,
+)
+
+
+search_results = find_iceflow_data(
+    dataset_search_params=DatasetSearchParameters(
+        bounding_box=BoundingBox(lower_left_lon=-103.125559, lower_left_lat=-75.180563, upper_right_lon=-102.677327, upper_right_lat=-74.798063),
+        temporal=(dt.date(2009, 11, 1), dt.date(2009, 12, 31)),
+    ),
+)
+```
+
+### Downloading data
+
+Once search results have been found, download data with
+[`download_iceflow_results`](nsidc.iceflow.download_iceflow_results):
+
+```
+from pathlib import Path
+from nsidc.iceflow import download_iceflow_results
+
+downloaded_filepaths = download_iceflow_results(
+    iceflow_search_result=iceflow_search_result,
+    output_dir=Path("/path/to/data/dir/"),
+)
+```
+
+### Accessing data
+
+Iceflow data can be very large, and fitting it into memory can be a challenge!
+To facilitate analysis of iceflow data,
+[`make_iceflow_parquet`](nsidc.iceflow.make_iceflow_parquet) provides a
+mechanism to create a [parquet](https://parquet.apache.org/docs/overview/)
+datastore that can be used alongside [dask](https://www.dask.org/):
+
+```
+import dask.dataframe as dd
+from nsidc.iceflow import make_iceflow_parquet
+
+parquet_path = make_iceflow_parquet(
+    data_dir=Path("/path/to/data/dir/"),
+    target_itrf="ITRF2014",
+)
+df = dd.read_parquet(parquet_path)
+```
+
+Note that `make_iceflow_parquet` creates a parquet datastore for the data in the
+provided `data_dir` with the data transformed into a common
+[ITRF](https://itrf.ign.fr/) to facilitate analysis. Only datetime, lat, lon,
+and elevation fields are preserved in the parquet datastore.
+
+To access and analyze the full data record in the source files, use
+[`read_iceflow_datafiles`](nsidc.iceflow.read_iceflow_datafiles):
+
+```
+from nsidc.iceflow import read_iceflow_datafiles
+
+# Read all of the data in the source files - not just lat/lon/elev.
+df = read_iceflow_datafiles(downloaded_files)
+
+# Optional: transform lat/lon/elev to common ITRF:
+from nsidc.iceflow import transform_itrf
+df = transform_itrf(
+    data=df,
+    target_itrf="ITRF2014",
+)
+```
+
+Note that `read_iceflow_datafiles` reads all of the data from the given
+filepaths. This could be a large amount of data, and could cause your program to
+crash if physical memory limits are exceeded.
diff --git a/docs/index.md b/docs/index.md
index 7349773..34e380c 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -5,6 +5,7 @@
 :hidden:
 :caption: content
 
+getting-started.md
 iceflow-example.ipynb
 iceflow-with-icepyx.ipynb
 api/nsidc
diff --git a/notebooks/iceflow-example.ipynb b/notebooks/iceflow-example.ipynb
index e88c7cf..76b01b9 100644
--- a/notebooks/iceflow-example.ipynb
+++ b/notebooks/iceflow-example.ipynb
@@ -33,9 +33,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from nsidc.iceflow.api import fetch_iceflow_df\n",
-    "from nsidc.iceflow.data.models import DatasetSearchParameters, BoundingBox, ILATM1BDataset\n",
-    "\n",
+    "from nsidc.iceflow import (\n",
+    "    find_iceflow_data,\n",
+    "    download_iceflow_results,\n",
+    "    read_iceflow_datafiles,\n",
+    "    DatasetSearchParameters,\n",
+    "    BoundingBox,\n",
+    "    ILATM1BDataset,\n",
+    ")\n",
     "from pathlib import Path\n",
     "import datetime as dt\n",
     "import matplotlib.pyplot as plt\n",
@@ -80,25 +85,61 @@
    "id": "ada043ae-65ed-4f22-ba19-dc9da6b8e0d2",
    "metadata": {},
    "source": [
-    "Now we use the `fetch_iceflow_df` function to search for and download data matching our search parameters. The output is a `pandas` DataFrame containing the matching data."
+    "Next, we use the `find_iceflow_data` function to search for data matching our search parameters. "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "15c0633c-1812-45d7-a91f-36d627fdb3b5",
+   "id": "c440ba2d-0c4a-47ff-b41e-a7486709d3e0",
    "metadata": {},
    "outputs": [],
    "source": [
-    "iceflow_df = fetch_iceflow_df(\n",
+    "search_results = find_iceflow_data(\n",
     "    dataset_search_params=DatasetSearchParameters(\n",
     "        datasets=[atm1b_v1_dataset],\n",
     "        bounding_box=BBOX,\n",
     "        temporal=date_range,\n",
     "    ),\n",
-    "    output_dir=data_path,\n",
-    "    output_itrf=None,\n",
     ")\n",
+    "len(search_results)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "752d5a6a-27ec-42cc-9505-923df8b69549",
+   "metadata": {},
+   "source": [
+    "Once we have found data matching our area of interest, we can download the results with `download_iceflow_results`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e3b3b3bc-2d2e-49d3-bafc-3f9a4269ee57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "downloaded_files = download_iceflow_results(search_results, output_dir=data_path)\n",
+    "print(downloaded_files)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1526b5bb-c08a-43d1-84b4-a207d9db924c",
+   "metadata": {},
+   "source": [
+    "Finally, we can read the data we just downloaded with `read_iceflow_datafiles`. The output is a `pandas` DataFrame containing the matching data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "15c0633c-1812-45d7-a91f-36d627fdb3b5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iceflow_df = read_iceflow_datafiles(downloaded_files)\n",
     "\n",
     "iceflow_df.head()"
    ]
@@ -139,7 +180,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from nsidc.iceflow.itrf.converter import transform_itrf\n",
+    "from nsidc.iceflow import transform_itrf\n",
     "\n",
     "itrf2014_df = transform_itrf(data=iceflow_df, target_itrf=\"ITRF2014\")\n",
     "itrf2014_df.head()"
diff --git a/notebooks/iceflow-with-icepyx.ipynb b/notebooks/iceflow-with-icepyx.ipynb
index 4b10b90..1ba8d65 100644
--- a/notebooks/iceflow-with-icepyx.ipynb
+++ b/notebooks/iceflow-with-icepyx.ipynb
@@ -59,9 +59,14 @@
     "import pandas as pd\n",
     "import xarray as xr\n",
     "\n",
-    "from nsidc.iceflow.api import fetch_iceflow_df, create_iceflow_parquet\n",
-    "from nsidc.iceflow.data import ALL_DATASETS\n",
-    "from nsidc.iceflow.data.models import DatasetSearchParameters, BoundingBox, IceflowDataFrame"
+    "from nsidc.iceflow import (\n",
+    "    make_iceflow_parquet,\n",
+    "    DatasetSearchParameters,\n",
+    "    BoundingBox,\n",
+    "    find_iceflow_data,\n",
+    "    download_iceflow_results,\n",
+    "    IceflowDataFrame\n",
+    ")"
    ]
   },
   {
@@ -103,55 +108,72 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ac0b6bf-41f5-44b7-9703-fce6c4b5e589",
+   "id": "420bf37c-c5cb-4339-bd26-ebb91ecb3973",
    "metadata": {},
    "source": [
-    "Next we use the `create_iceflow_parquet` function from the `iceflow` API. This function:\n",
-    "\n",
-    "* Finds data matching our `BBOX`, `DATE_RANGE`, and desired datasets\n",
-    "* Downloads and reads the data from the datasets' native formats\n",
-    "* Transforms all of the lat/lon/elev data into a target ITRF\n",
-    "* Writes out the lat/lon/elev data to a parquet dataset that can be be read by e.g., `dask` for further processing. \n",
+    "Next we will use the `find_iceflow_data` function from the `iceflow` API to find data matching our area of interest.\n",
     "\n",
-    "Writing data to a parquet dataset allows `dask` (which we will use later!) to read the chunks of data it needs to do calculations (e.g., `mean`) without needing to read all of the data into memory at once. This is important because `iceflow` can find many millions of data points for even small areas of interest!\n",
-    "\n",
-    "**Note: This next step may take a while, and will download data to your local disk.**"
+    "By default, `DatasetSearchParameters` will include all `iceflow` supported datasets, unless one or more are specified as a filter with the `datasets` kwarg. There may be warnings raised about there not being search results for specific datasets supported by `iceflow`."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "713b93dd-d23b-422b-92dc-f9ed364a566c",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cfda36320ddb49dc860724b8e9aa4812",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "COLLECTING RESULTS | :   0%|          | 0/8 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "id": "ee315618-32ad-4710-9629-0a3d2e2ed26b",
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "parquet_path = create_iceflow_parquet(\n",
+    "search_results = find_iceflow_data(\n",
     "    dataset_search_params=DatasetSearchParameters(\n",
-    "        # `ALL_DATASETS` is a list that contains all of the datasets supported by iceflow.\n",
-    "        # This lets us find all the data iceflow supports for our area of interest.\n",
-    "        datasets=ALL_DATASETS,\n",
     "        bounding_box=BBOX,\n",
     "        temporal=DATE_RANGE,\n",
     "    ),\n",
+    ")\n",
+    "len(search_results)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b57c25fc-ebf1-4397-bcb7-076428855b7c",
+   "metadata": {},
+   "source": [
+    "Now download the matching files to disk using `download_iceflow_results`.\n",
+    "\n",
+    "**Note: This next step may take a while, and will download data to your local disk.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "84e53851-53a8-49e0-bce3-2789253498b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "downloaded_files = download_iceflow_results(search_results, output_dir=OUTPUT_DIR)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fee85cd6-522f-4352-86ea-9530add68000",
+   "metadata": {},
+   "source": [
+    "Finally, we will create a parquet dataset using `make_iceflow_parquet`.Writing data to a parquet dataset allows `dask` (which we will use later!) to read the chunks of data it needs to do calculations (e.g., `mean`) without needing to read all of the data into memory at once. This is important because `iceflow` can find many millions of data points for even small areas of interest!\n",
+    "\n",
+    "This function transforms all data found in the `data_dir` to the provided `target_itrf`, further facilitating analysis across many datasets. \n",
+    "\n",
+    "**Note: This next step may take a while**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17e03a49-405a-4d00-a08d-74e5890564da",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parquet_path = make_iceflow_parquet(\n",
+    "    data_dir=OUTPUT_DIR,\n",
     "    target_itrf=ICESAT2_ITRF,\n",
-    "    output_dir=OUTPUT_DIR,\n",
     "    overwrite=True,\n",
     ")"
    ]
@@ -219,7 +241,9 @@
    "id": "25fbed4b-beb7-41d8-a4fd-788e4821e505",
    "metadata": {},
    "source": [
-    "Now we download the results.  Note that this may take a while to download data to local disk."
+    "Now we download the results.  Note that this may take a while to download data to local disk.\n",
+    "\n",
+    "**Note: This next step may take a while**"
    ]
   },
   {
@@ -228,94 +252,6 @@
    "id": "0c146fa2-fdb9-4774-a6bf-481e2498948a",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "order ID:  5000005834161\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Initial status of your order request at NSIDC is:  processing\n",
-      "Your order status is still  processing  at NSIDC. Please continue waiting... this may take a few moments.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Your order status is still  processing  at NSIDC. Please continue waiting... this may take a few moments.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Your order is: complete\n",
-      "NSIDC returned these messages\n",
-      "['Granule 264536951 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 266305749 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 266291041 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 267817320 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 269300297 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 270749838 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 263383891 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 271785068 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 271784351 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 272056980 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 263469273 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 272503761 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 272965502 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 273763028 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 264480187 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 275879411 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 296508188 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 296978995 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 297158720 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 297156453 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 298067202 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 297232761 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 306864253 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 306923340 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed',\n",
-      " 'Granule 309516749 contained no data within the spatial and/or temporal '\n",
-      " 'subset constraints to be processed']\n",
-      "Beginning download of zipped output...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data request 5000005834161 of  1  order(s) is downloaded.\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -345,63 +281,7 @@
    "execution_count": null,
    "id": "081376b5-308b-43c3-bc6d-b9c4342586d0",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20220909222056_12221603_006_01.h5') contains an error and will not be read\n",
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20230503234538_06661905_006_03.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20240501062333_06662305_006_01.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20230908045912_12222003_006_02.h5') contains an error and will not be read\n",
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20220611024058_12221503_006_01.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20210806060645_06661205_006_01.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20200208080743_06660605_006_01.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20240702032717_02242405_006_01.h5') contains an error and will not be read\n",
-      "file=PosixPath('downloaded-data/ATL06/processed_ATL06_20210107161057_02241005_006_01.h5') contains an error and will not be read\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "49"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "datasets = []\n",
     "for file in Path(\"downloaded-data/ATL06/\").glob(\"*.h5\"):\n",
diff --git a/src/nsidc/iceflow/__init__.py b/src/nsidc/iceflow/__init__.py
index 8538a38..99b4541 100644
--- a/src/nsidc/iceflow/__init__.py
+++ b/src/nsidc/iceflow/__init__.py
@@ -2,13 +2,54 @@
 Copyright (c) 2024 NSIDC. All rights reserved.
 
 iceflow: Harmonized access to (pre)OIB/IceSAT/IceSAT2 data
+
+Users interact with `iceflow` by:
+
+* Searching for data that match an area of interest/time (`find_iceflow_data`)
+* Downloading data (`download_iceflow_results`)
+* (Optional) Creating a parquet datastore to facilitate reading the data (`make_iceflow_parquet`)
+* Reading and doing analysis with the data (`dask.dataframe.read_parquet`,
+  `read_iceflow_datafiles`)
+* (Optional, if using `read_iceflow_datafiles`) Transform the lat/lon/elev data
+  into a target International Terrestrial Reference Frame (ITRF) (`transform_itrf`)
+
 """
 
 from __future__ import annotations
 
+from nsidc.iceflow.api import make_iceflow_parquet
+from nsidc.iceflow.data.fetch import download_iceflow_results, find_iceflow_data
+from nsidc.iceflow.data.models import (
+    ALL_DATASETS,
+    BLATM1BDataset,
+    BoundingBox,
+    DatasetSearchParameters,
+    GLAH06Dataset,
+    IceflowDataFrame,
+    ILATM1BDataset,
+    ILVIS2Dataset,
+)
+from nsidc.iceflow.data.read import read_iceflow_datafiles
+from nsidc.iceflow.itrf.converter import transform_itrf
+
 # TODO: add bumpversion config to control this version number, and the conda
 # recipe/meta.yaml.
 __version__ = "v0.2.0"
 
 
-__all__ = ["__version__"]
+__all__ = [
+    "__version__",
+    "make_iceflow_parquet",
+    "download_iceflow_results",
+    "find_iceflow_data",
+    "read_iceflow_datafiles",
+    "transform_itrf",
+    "DatasetSearchParameters",
+    "BoundingBox",
+    "ALL_DATASETS",
+    "BLATM1BDataset",
+    "GLAH06Dataset",
+    "ILATM1BDataset",
+    "ILVIS2Dataset",
+    "IceflowDataFrame",
+]
diff --git a/src/nsidc/iceflow/api.py b/src/nsidc/iceflow/api.py
index e2e2163..989e98c 100644
--- a/src/nsidc/iceflow/api.py
+++ b/src/nsidc/iceflow/api.py
@@ -1,3 +1,5 @@
+"""Module with functions defining the user-facing API for iceflow."""
+
 from __future__ import annotations
 
 import shutil
@@ -8,6 +10,7 @@
 
 from nsidc.iceflow.data.fetch import download_iceflow_results, find_iceflow_data
 from nsidc.iceflow.data.models import (
+    ALL_DATASETS,
     DatasetSearchParameters,
     IceflowDataFrame,
 )
@@ -30,7 +33,7 @@ def fetch_iceflow_df(
     user requests a large spatial/temporal area across multiple datasets. The
     result may not even fit in memory!
 
-    Consider using `create_iceflow_parquet` to fetch and store data in parquet
+    Consider using `make_iceflow_parquet` to store downloaded data in parquet
     format.
     """
 
@@ -54,18 +57,19 @@ def fetch_iceflow_df(
     return iceflow_df
 
 
-def create_iceflow_parquet(
+def make_iceflow_parquet(
     *,
-    dataset_search_params: DatasetSearchParameters,
-    output_dir: Path,
+    data_dir: Path,
     target_itrf: str,
     overwrite: bool = False,
     target_epoch: str | None = None,
 ) -> Path:
-    """Create a parquet dataset containing the lat/lon/elev data matching the dataset search params.
+    """Create a parquet dataset containing the lat/lon/elev data in `data_dir`.
 
-    This function creates a parquet dataset that can be easily used alongside dask,
-    containing lat/lon/elev data.
+    This function creates a parquet dataset that can be easily used alongside
+    dask, containing lat/lon/elev data. Users who are interested in the full
+    data record with all fields provided by data in the `data_dir` should use
+    `read_iceflow_datafiles`.
 
     Note: this function writes a single `iceflow.parquet` to the output
     dir. This code does not currently support updates to the parquet after being
@@ -75,27 +79,24 @@ def create_iceflow_parquet(
     need to move/remove the existing `iceflow.parquet` first (e.g., with the
     `overwrite=True` kwarg).
     """
-    output_subdir = output_dir / "iceflow.parquet"
-    if output_subdir.exists():
+    parquet_subdir = data_dir / "iceflow.parquet"
+    if parquet_subdir.exists():
         if overwrite:
             logger.info("Removing existing iceflow.parquet")
-            shutil.rmtree(output_subdir)
+            shutil.rmtree(parquet_subdir)
         else:
             raise RuntimeError(
                 "An iceflow parquet file already exists. Use `overwrite=True` to overwrite."
             )
 
-    iceflow_search_results = find_iceflow_data(
-        dataset_search_params=dataset_search_params,
-    )
-
-    for iceflow_search_result in iceflow_search_results:
-        downloaded_files = download_iceflow_results(
-            iceflow_search_results=[iceflow_search_result],
-            output_dir=output_dir,
-        )
-
-        iceflow_df = read_iceflow_datafiles(downloaded_files)
+    all_subdirs = [
+        data_dir / ds.subdir_name
+        for ds in ALL_DATASETS
+        if (data_dir / ds.subdir_name).is_dir()
+    ]
+    for subdir in all_subdirs:
+        iceflow_filepaths = [path for path in subdir.iterdir() if path.is_file()]
+        iceflow_df = read_iceflow_datafiles(iceflow_filepaths)
 
         iceflow_df = transform_itrf(
             data=iceflow_df,
@@ -104,23 +105,21 @@ def create_iceflow_parquet(
         )
 
         # Add a string col w/ dataset name and version.
-        dataset = iceflow_search_result.dataset
-        iceflow_df["dataset"] = [f"{dataset.short_name}v{dataset.version}"] * len(
-            iceflow_df.latitude
-        )
+        short_name, version = subdir.name.split("_")
+        iceflow_df["dataset"] = [f"{short_name}v{version}"] * len(iceflow_df.latitude)
         common_columns = ["latitude", "longitude", "elevation", "dataset"]
         common_dask_df = dd.from_pandas(iceflow_df[common_columns])  # type: ignore[attr-defined]
-        if output_subdir.exists():
+        if parquet_subdir.exists():
             dd.to_parquet(  # type: ignore[attr-defined]
                 df=common_dask_df,
-                path=output_subdir,
+                path=parquet_subdir,
                 append=True,
                 ignore_divisions=True,
             )
         else:
             dd.to_parquet(  # type: ignore[attr-defined]
                 df=common_dask_df,
-                path=output_subdir,
+                path=parquet_subdir,
             )
 
-    return output_subdir
+    return parquet_subdir
diff --git a/src/nsidc/iceflow/data/fetch.py b/src/nsidc/iceflow/data/fetch.py
index 64f2817..ee64d9b 100644
--- a/src/nsidc/iceflow/data/fetch.py
+++ b/src/nsidc/iceflow/data/fetch.py
@@ -46,7 +46,7 @@ def _find_iceflow_data(
     num_results = len(granules_list)
 
     if not num_results:
-        logger.error(f"Found no results for {ctx_string}")
+        logger.warning(f"Found no results for {ctx_string}")
         granules_list = []
 
     iceflow_search_result = IceflowSearchResult(dataset=dataset, granules=granules_list)
@@ -58,6 +58,9 @@ def _download_iceflow_search_result(
     iceflow_search_result: IceflowSearchResult,
     output_dir: Path,
 ) -> list[Path]:
+    # No granules found for this search result object.
+    if not iceflow_search_result.granules:
+        return []
     # short_name and version-based subdir for data.
     subdir_name = f"{iceflow_search_result.dataset.short_name}_{iceflow_search_result.dataset.version}"
     output_subdir = output_dir / subdir_name
diff --git a/src/nsidc/iceflow/data/models.py b/src/nsidc/iceflow/data/models.py
index 1eb9ffb..d101b3d 100644
--- a/src/nsidc/iceflow/data/models.py
+++ b/src/nsidc/iceflow/data/models.py
@@ -196,6 +196,10 @@ class Dataset(pydantic.BaseModel):
     short_name: DatasetShortName
     version: str
 
+    @property
+    def subdir_name(self):
+        return f"{self.short_name}_{self.version}"
+
 
 class ATM1BDataset(Dataset):
     short_name: ATM1BShortName
diff --git a/tests/integration/test_e2e.py b/tests/integration/test_e2e.py
index 75f09b5..83bd93a 100644
--- a/tests/integration/test_e2e.py
+++ b/tests/integration/test_e2e.py
@@ -11,11 +11,17 @@
 from __future__ import annotations
 
 import datetime as dt
+from pathlib import Path
 
 import dask.dataframe as dd
 import pandas as pd
 
-from nsidc.iceflow.api import create_iceflow_parquet, fetch_iceflow_df
+from nsidc.iceflow import (
+    download_iceflow_results,
+    find_iceflow_data,
+    make_iceflow_parquet,
+)
+from nsidc.iceflow.api import fetch_iceflow_df
 from nsidc.iceflow.data.models import (
     BLATM1BDataset,
     BoundingBox,
@@ -147,6 +153,46 @@ def test_glah06(tmp_path):
     assert (results.ITRF == "ITRF2008").all()
 
 
+def _create_iceflow_parquet(
+    *,
+    dataset_search_params: DatasetSearchParameters,
+    output_dir: Path,
+    target_itrf: str,
+    overwrite: bool = False,
+    target_epoch: str | None = None,
+) -> Path:
+    """Create a parquet dataset containing the lat/lon/elev data matching the dataset search params.
+
+    This function creates a parquet dataset that can be easily used alongside dask,
+    containing lat/lon/elev data.
+
+    Note: this function writes a single `iceflow.parquet` to the output
+    dir. This code does not currently support updates to the parquet after being
+    written. This is intended to help facilitate analysis of a specific area
+    over time. If an existing `iceflow.parquet` exists and the user wants to
+    create a new `iceflow.parquet` for a different area or timespan, they will
+    need to move/remove the existing `iceflow.parquet` first (e.g., with the
+    `overwrite=True` kwarg).
+    """
+    iceflow_search_results = find_iceflow_data(
+        dataset_search_params=dataset_search_params,
+    )
+
+    download_iceflow_results(
+        iceflow_search_results=iceflow_search_results,
+        output_dir=output_dir,
+    )
+
+    parquet_path = make_iceflow_parquet(
+        data_dir=output_dir,
+        target_itrf=target_itrf,
+        overwrite=overwrite,
+        target_epoch=target_epoch,
+    )
+
+    return parquet_path
+
+
 def test_create_iceflow_parquet(tmp_path):
     target_itrf = "ITRF2014"
     common_bounding_box = BoundingBox(
@@ -157,7 +203,7 @@ def test_create_iceflow_parquet(tmp_path):
     )
 
     # This should finds 4 results for ILATM1B v1 and 3 results for v2.
-    parquet_path = create_iceflow_parquet(
+    parquet_path = _create_iceflow_parquet(
         dataset_search_params=DatasetSearchParameters(
             datasets=[ILATM1BDataset(version="1"), ILATM1BDataset(version="2")],
             bounding_box=common_bounding_box,

From cd1a323951cc7fc3bee0a6580239d3d18e8717fb Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Mon, 9 Dec 2024 10:47:16 -0700
Subject: [PATCH 08/10] Update notebooks for docs and fixup notebook rendering
 task

---
 docs/iceflow-example.ipynb     |  860 ++++----
 docs/iceflow-with-icepyx.ipynb | 3647 ++++++++++++++++----------------
 tasks/docs.py                  |    2 +-
 3 files changed, 2324 insertions(+), 2185 deletions(-)

diff --git a/docs/iceflow-example.ipynb b/docs/iceflow-example.ipynb
index 0c00078..9801a02 100644
--- a/docs/iceflow-example.ipynb
+++ b/docs/iceflow-example.ipynb
@@ -13,7 +13,7 @@
     "\n",
     "Finding, downloading, and reading ILATM1B v1 data with `nsidc-iceflow` is straightforward. ILATM1B data can be very large, so for the purposes of this example we will focus on just a small area near Pine Island Glacier along with a short date range in order to fetch a manageable amount of data.\n",
     "\n",
-    "To learn about how to download and manage larger amounts of data across many datasets with `iceflow`, see the [Using iceflow with icepyx to Generate an Elevation Timeseries](./iceflow-with-icepyx.ipynb) notebook."
+    "To learn about how to download and manage larger amounts of data across many datasets with `nsidc-iceflow`, see the [Using iceflow with icepyx to Generate an Elevation Timeseries](./iceflow-with-icepyx.ipynb) notebook."
    ]
   },
   {
@@ -32,17 +32,22 @@
    "id": "e29f9cf9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:50:55.406077Z",
-     "iopub.status.busy": "2024-11-08T18:50:55.405805Z",
-     "iopub.status.idle": "2024-11-08T18:50:56.410323Z",
-     "shell.execute_reply": "2024-11-08T18:50:56.410049Z"
+     "iopub.execute_input": "2024-12-09T17:35:39.880850Z",
+     "iopub.status.busy": "2024-12-09T17:35:39.880618Z",
+     "iopub.status.idle": "2024-12-09T17:35:40.959362Z",
+     "shell.execute_reply": "2024-12-09T17:35:40.959042Z"
     }
    },
    "outputs": [],
    "source": [
-    "from nsidc.iceflow.api import fetch_iceflow_df\n",
-    "from nsidc.iceflow.data.models import DatasetSearchParameters, BoundingBox, ILATM1BDataset\n",
-    "\n",
+    "from nsidc.iceflow import (\n",
+    "    find_iceflow_data,\n",
+    "    download_iceflow_results,\n",
+    "    read_iceflow_datafiles,\n",
+    "    DatasetSearchParameters,\n",
+    "    BoundingBox,\n",
+    "    ILATM1BDataset,\n",
+    ")\n",
     "from pathlib import Path\n",
     "import datetime as dt\n",
     "import matplotlib.pyplot as plt\n",
@@ -68,10 +73,10 @@
    "id": "f45d86d9-404a-4720-9ad0-9959114aa629",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:50:56.412183Z",
-     "iopub.status.busy": "2024-11-08T18:50:56.411964Z",
-     "iopub.status.idle": "2024-11-08T18:50:56.414396Z",
-     "shell.execute_reply": "2024-11-08T18:50:56.414176Z"
+     "iopub.execute_input": "2024-12-09T17:35:40.961329Z",
+     "iopub.status.busy": "2024-12-09T17:35:40.961091Z",
+     "iopub.status.idle": "2024-12-09T17:35:40.963836Z",
+     "shell.execute_reply": "2024-12-09T17:35:40.963457Z"
     }
    },
    "outputs": [],
@@ -94,19 +99,62 @@
    "id": "ada043ae-65ed-4f22-ba19-dc9da6b8e0d2",
    "metadata": {},
    "source": [
-    "Now we use the `fetch_iceflow_df` function to search for and download data matching our search parameters. The output is a `pandas` DataFrame containing the matching data."
+    "Next, we use the `find_iceflow_data` function to search for data matching our search parameters. "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "15c0633c-1812-45d7-a91f-36d627fdb3b5",
+   "id": "c440ba2d-0c4a-47ff-b41e-a7486709d3e0",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-12-09T17:35:40.965375Z",
+     "iopub.status.busy": "2024-12-09T17:35:40.965208Z",
+     "iopub.status.idle": "2024-12-09T17:35:45.058227Z",
+     "shell.execute_reply": "2024-12-09T17:35:45.057626Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_results = find_iceflow_data(\n",
+    "    dataset_search_params=DatasetSearchParameters(\n",
+    "        datasets=[atm1b_v1_dataset],\n",
+    "        bounding_box=BBOX,\n",
+    "        temporal=date_range,\n",
+    "    ),\n",
+    ")\n",
+    "len(search_results)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "752d5a6a-27ec-42cc-9505-923df8b69549",
+   "metadata": {},
+   "source": [
+    "Once we have found data matching our area of interest, we can download the results with `download_iceflow_results`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e3b3b3bc-2d2e-49d3-bafc-3f9a4269ee57",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:50:56.415884Z",
-     "iopub.status.busy": "2024-11-08T18:50:56.415795Z",
-     "iopub.status.idle": "2024-11-08T18:51:04.321836Z",
-     "shell.execute_reply": "2024-11-08T18:51:04.321263Z"
+     "iopub.execute_input": "2024-12-09T17:35:45.061192Z",
+     "iopub.status.busy": "2024-12-09T17:35:45.060953Z",
+     "iopub.status.idle": "2024-12-09T17:35:46.823554Z",
+     "shell.execute_reply": "2024-12-09T17:35:46.823171Z"
     }
    },
    "outputs": [
@@ -114,13 +162,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:51:00.613\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 1 granules for short_name='ILATM1B' version='1' with bounding_box=BoundingBox(lower_left_lon=-103.125559, lower_left_lat=-75.180563, upper_right_lon=-102.677327, upper_right_lat=-74.798063) temporal=(datetime.date(2009, 11, 1), datetime.date(2009, 12, 31)). Downloading to downloaded-data/ILATM1B.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:35:45.061\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 1 granules to downloaded-data/ILATM1B_1.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d52d51cba07c42e78a079d4e41ff9b6f",
+       "model_id": "b44e7f88a7ec45bfb9e3191d93f9ef0b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -134,7 +182,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7d0be797eeca4f7bb73cd5063650cc54",
+       "model_id": "687a6e75fcfc447c913563b1431b3e8f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -148,7 +196,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c12d9ee611ea4ecca0b7561cc616f137",
+       "model_id": "dd782e76e307437bb90a4afa7bac4827",
        "version_major": 2,
        "version_minor": 0
       },
@@ -159,6 +207,40 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[PosixPath('downloaded-data/ILATM1B_1/ILATM1B_20091109_203148.atm4cT3.qi')]\n"
+     ]
+    }
+   ],
+   "source": [
+    "downloaded_files = download_iceflow_results(search_results, output_dir=data_path)\n",
+    "print(downloaded_files)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1526b5bb-c08a-43d1-84b4-a207d9db924c",
+   "metadata": {},
+   "source": [
+    "Finally, we can read the data we just downloaded with `read_iceflow_datafiles`. The output is a `pandas` DataFrame containing the matching data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "15c0633c-1812-45d7-a91f-36d627fdb3b5",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-12-09T17:35:46.826168Z",
+     "iopub.status.busy": "2024-12-09T17:35:46.825807Z",
+     "iopub.status.idle": "2024-12-09T17:35:48.628664Z",
+     "shell.execute_reply": "2024-12-09T17:35:48.628054Z"
+    }
+   },
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -374,21 +456,13 @@
        "2009-11-09 20:31:49.001                                      NaN  ITRF2005  "
       ]
      },
-     "execution_count": 3,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "iceflow_df = fetch_iceflow_df(\n",
-    "    dataset_search_params=DatasetSearchParameters(\n",
-    "        datasets=[atm1b_v1_dataset],\n",
-    "        bounding_box=BBOX,\n",
-    "        temporal=date_range,\n",
-    "    ),\n",
-    "    output_dir=data_path,\n",
-    "    output_itrf=None,\n",
-    ")\n",
+    "iceflow_df = read_iceflow_datafiles(downloaded_files)\n",
     "\n",
     "iceflow_df.head()"
    ]
@@ -403,14 +477,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "id": "99e03fbd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:04.324287Z",
-     "iopub.status.busy": "2024-11-08T18:51:04.324040Z",
-     "iopub.status.idle": "2024-11-08T18:51:04.331175Z",
-     "shell.execute_reply": "2024-11-08T18:51:04.330860Z"
+     "iopub.execute_input": "2024-12-09T17:35:48.630798Z",
+     "iopub.status.busy": "2024-12-09T17:35:48.630364Z",
+     "iopub.status.idle": "2024-12-09T17:35:48.638029Z",
+     "shell.execute_reply": "2024-12-09T17:35:48.637720Z"
     }
    },
    "outputs": [
@@ -498,7 +572,7 @@
        "2009-11-09 20:31:49.001 -75.159051 -102.289878  136.298996  ITRF2005"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -520,14 +594,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "id": "6a0cd1e6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:04.332826Z",
-     "iopub.status.busy": "2024-11-08T18:51:04.332715Z",
-     "iopub.status.idle": "2024-11-08T18:51:05.918076Z",
-     "shell.execute_reply": "2024-11-08T18:51:05.917806Z"
+     "iopub.execute_input": "2024-12-09T17:35:48.639480Z",
+     "iopub.status.busy": "2024-12-09T17:35:48.639330Z",
+     "iopub.status.idle": "2024-12-09T17:35:50.311249Z",
+     "shell.execute_reply": "2024-12-09T17:35:50.310872Z"
     }
    },
    "outputs": [
@@ -615,13 +689,13 @@
        "2009-11-09 20:31:49.001 -75.159051 -102.289878  136.291354  ITRF2014"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "from nsidc.iceflow.itrf.converter import transform_itrf\n",
+    "from nsidc.iceflow import transform_itrf\n",
     "\n",
     "itrf2014_df = transform_itrf(data=iceflow_df, target_itrf=\"ITRF2014\")\n",
     "itrf2014_df.head()"
@@ -637,14 +711,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "id": "b64693c0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:05.919603Z",
-     "iopub.status.busy": "2024-11-08T18:51:05.919497Z",
-     "iopub.status.idle": "2024-11-08T18:51:05.925025Z",
-     "shell.execute_reply": "2024-11-08T18:51:05.924539Z"
+     "iopub.execute_input": "2024-12-09T17:35:50.313326Z",
+     "iopub.status.busy": "2024-12-09T17:35:50.313162Z",
+     "iopub.status.idle": "2024-12-09T17:35:50.319005Z",
+     "shell.execute_reply": "2024-12-09T17:35:50.318689Z"
     }
    },
    "outputs": [
@@ -685,14 +759,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "id": "14e431b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:05.927011Z",
-     "iopub.status.busy": "2024-11-08T18:51:05.926759Z",
-     "iopub.status.idle": "2024-11-08T18:51:07.512910Z",
-     "shell.execute_reply": "2024-11-08T18:51:07.512499Z"
+     "iopub.execute_input": "2024-12-09T17:35:50.320426Z",
+     "iopub.status.busy": "2024-12-09T17:35:50.320327Z",
+     "iopub.status.idle": "2024-12-09T17:35:52.054693Z",
+     "shell.execute_reply": "2024-12-09T17:35:52.054037Z"
     }
    },
    "outputs": [
@@ -780,7 +854,7 @@
        "2009-11-09 20:31:49.001 -75.159051 -102.289872  136.291266  ITRF2014"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -805,14 +879,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "id": "8c562732",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:07.514709Z",
-     "iopub.status.busy": "2024-11-08T18:51:07.514599Z",
-     "iopub.status.idle": "2024-11-08T18:51:07.520153Z",
-     "shell.execute_reply": "2024-11-08T18:51:07.519796Z"
+     "iopub.execute_input": "2024-12-09T17:35:52.056409Z",
+     "iopub.status.busy": "2024-12-09T17:35:52.056299Z",
+     "iopub.status.idle": "2024-12-09T17:35:52.062172Z",
+     "shell.execute_reply": "2024-12-09T17:35:52.061727Z"
     }
    },
    "outputs": [
@@ -843,14 +917,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "id": "5bafd254",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:07.521900Z",
-     "iopub.status.busy": "2024-11-08T18:51:07.521794Z",
-     "iopub.status.idle": "2024-11-08T18:51:07.530282Z",
-     "shell.execute_reply": "2024-11-08T18:51:07.530003Z"
+     "iopub.execute_input": "2024-12-09T17:35:52.064144Z",
+     "iopub.status.busy": "2024-12-09T17:35:52.064007Z",
+     "iopub.status.idle": "2024-12-09T17:35:52.073202Z",
+     "shell.execute_reply": "2024-12-09T17:35:52.072754Z"
     }
    },
    "outputs": [],
@@ -871,14 +945,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "id": "0ffce6d2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:51:07.531931Z",
-     "iopub.status.busy": "2024-11-08T18:51:07.531821Z",
-     "iopub.status.idle": "2024-11-08T18:51:07.625993Z",
-     "shell.execute_reply": "2024-11-08T18:51:07.625573Z"
+     "iopub.execute_input": "2024-12-09T17:35:52.074587Z",
+     "iopub.status.busy": "2024-12-09T17:35:52.074475Z",
+     "iopub.status.idle": "2024-12-09T17:35:52.195075Z",
+     "shell.execute_reply": "2024-12-09T17:35:52.194349Z"
     }
    },
    "outputs": [
@@ -952,23 +1026,7 @@
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
     "state": {
-     "095703066ff14ea4ab7e0c6a3af1f43c": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "0a328e07873d4855bd03775d797c8730": {
+     "018ba985ac6b4d5fb8600b76bc7d7b79": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1021,60 +1079,33 @@
        "width": null
       }
      },
-     "0ae4a39b1fbd4fa5bbf8f1478c0812ec": {
-      "model_module": "@jupyter-widgets/base",
+     "09c2f13b70c34e65804af9c933a3b14a": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "FloatProgressModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_6fbaa72f65f0430a95af5c23f008138b",
+       "max": 1.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_6a25b1935c374f6e9f807de3a599db35",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 1.0
       }
      },
-     "21e03aff26894b9aad15e1deaa3546ef": {
+     "0af9b5b2b1cc4798baafc8e1281910d6": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -1092,30 +1123,33 @@
        "text_color": null
       }
      },
-     "3367b617a09d4f00a1d7a258ff3f67f0": {
+     "1d1949510c9a438e8e9a45e21c7c724c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "FloatProgressModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_9242d1864c5f427d85a36119bc23ce36",
-       "placeholder": "​",
-       "style": "IPY_MODEL_cc773c0630824c43b68d4d3b15ebd5fb",
+       "layout": "IPY_MODEL_2fd00f9534774660a6d091e8d64e71a0",
+       "max": 1.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_4100ddb10e4247e6a63acaf605d1c38c",
        "tabbable": null,
        "tooltip": null,
-       "value": " 1/1 [00:00&lt;00:00, 156.22it/s]"
+       "value": 1.0
       }
      },
-     "39cd0dcdc92e4024b46048009aeb71b4": {
+     "2fd00f9534774660a6d091e8d64e71a0": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1168,7 +1202,23 @@
        "width": null
       }
      },
-     "3dee7879b63841f8a6ceb877ea0b35b9": {
+     "4100ddb10e4247e6a63acaf605d1c38c": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "435d337bceb44597bead638d5850e005": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -1183,15 +1233,15 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_4577fadf3b0c40a7a4d29d9f2cc2fb23",
+       "layout": "IPY_MODEL_6b1e3827cc4847dfabf524d2b83efe71",
        "placeholder": "​",
-       "style": "IPY_MODEL_21e03aff26894b9aad15e1deaa3546ef",
+       "style": "IPY_MODEL_c7b7b31f2c604a1196546e2997bc0c66",
        "tabbable": null,
        "tooltip": null,
-       "value": " 1/1 [00:01&lt;00:00,  1.74s/it]"
+       "value": "COLLECTING RESULTS | : 100%"
       }
      },
-     "42ae9f2d66634262824cade5b9e14e84": {
+     "4c5e9421191442c2a2c6ed2406fe422f": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -1209,7 +1259,57 @@
        "text_color": null
       }
      },
-     "4514de7881bc486c9cddf90e085c7fdb": {
+     "541c1134ac454078b4989985e6df8fb9": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "FloatProgressModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_018ba985ac6b4d5fb8600b76bc7d7b79",
+       "max": 1.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_7284d68562514cd5bed97a15775788ca",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 1.0
+      }
+     },
+     "687a6e75fcfc447c913563b1431b3e8f": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_75e3c4f701b54e9aa879e8519997bc93",
+        "IPY_MODEL_09c2f13b70c34e65804af9c933a3b14a",
+        "IPY_MODEL_97ec1eae1c9c4c88865cd95082a58c88"
+       ],
+       "layout": "IPY_MODEL_95b0d07ea55a40c08fb1f7df827bf4fc",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "6a25b1935c374f6e9f807de3a599db35": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "ProgressStyleModel",
@@ -1225,7 +1325,7 @@
        "description_width": ""
       }
      },
-     "4577fadf3b0c40a7a4d29d9f2cc2fb23": {
+     "6b1e3827cc4847dfabf524d2b83efe71": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1278,23 +1378,30 @@
        "width": null
       }
      },
-     "6dccbe75ff4747d381864550ebce72eb": {
+     "6e859ebf434c461caff7a96afcb64407": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_cb66396c16f74903af9d2c98515b3594",
+       "placeholder": "​",
+       "style": "IPY_MODEL_e9b28f4d23134ae8ab8f7d45bd8ed8c2",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 1/1 [00:00&lt;00:00, 160.86it/s]"
       }
      },
-     "74999bb22aca465696abfdaaa380fbd7": {
+     "6fbaa72f65f0430a95af5c23f008138b": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1347,49 +1454,46 @@
        "width": null
       }
      },
-     "7748851a2ae048a4b89a167f28dace99": {
+     "7284d68562514cd5bed97a15775788ca": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "ProgressStyleModel",
       "state": {
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "ProgressStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
+       "bar_color": null,
+       "description_width": ""
+      }
      },
-     "7d0be797eeca4f7bb73cd5063650cc54": {
+     "75e3c4f701b54e9aa879e8519997bc93": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_b7999bd16748473996d328d4f13fe362",
-        "IPY_MODEL_d337f9a0ef2348d08835c6742a269707",
-        "IPY_MODEL_3dee7879b63841f8a6ceb877ea0b35b9"
-       ],
-       "layout": "IPY_MODEL_74999bb22aca465696abfdaaa380fbd7",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_c94e80905dbd4467a66eb15c5337b874",
+       "placeholder": "​",
+       "style": "IPY_MODEL_0af9b5b2b1cc4798baafc8e1281910d6",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": "PROCESSING TASKS | : 100%"
       }
      },
-     "7ff2be226e374d739011b7e26dc8cab9": {
+     "8fca8a66fcea4d7ca20111b2d0262d23": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -1404,15 +1508,15 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_0ae4a39b1fbd4fa5bbf8f1478c0812ec",
+       "layout": "IPY_MODEL_c4f39810508446018b5384d6de373afa",
        "placeholder": "​",
-       "style": "IPY_MODEL_42ae9f2d66634262824cade5b9e14e84",
+       "style": "IPY_MODEL_4c5e9421191442c2a2c6ed2406fe422f",
        "tabbable": null,
        "tooltip": null,
        "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "874a71279f88456ea2febf8df9292b00": {
+     "95b0d07ea55a40c08fb1f7df827bf4fc": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1465,7 +1569,77 @@
        "width": null
       }
      },
-     "8f9e30349a6c4445b1efc001d4386ed3": {
+     "97ec1eae1c9c4c88865cd95082a58c88": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_b8c1e2aaa184409d8a02ad33e9b6fc38",
+       "placeholder": "​",
+       "style": "IPY_MODEL_c3c6c220ad6c4168bcdc717f195fa4d1",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 1/1 [00:01&lt;00:00,  1.74s/it]"
+      }
+     },
+     "a714d6206c934b0583c5572d7d84376d": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_ee19d40b63aa4ef691061b855ac3b64e",
+       "placeholder": "​",
+       "style": "IPY_MODEL_eb2aa718055f4037afea898c891bac39",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 1/1 [00:00&lt;00:00, 133.50it/s]"
+      }
+     },
+     "b44e7f88a7ec45bfb9e3191d93f9ef0b": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_8fca8a66fcea4d7ca20111b2d0262d23",
+        "IPY_MODEL_1d1949510c9a438e8e9a45e21c7c724c",
+        "IPY_MODEL_a714d6206c934b0583c5572d7d84376d"
+       ],
+       "layout": "IPY_MODEL_c918b740c0fb460488a6f657ba79e328",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "b8c1e2aaa184409d8a02ad33e9b6fc38": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1518,7 +1692,25 @@
        "width": null
       }
      },
-     "9242d1864c5f427d85a36119bc23ce36": {
+     "c3c6c220ad6c4168bcdc717f195fa4d1": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "c4f39810508446018b5384d6de373afa": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1571,7 +1763,25 @@
        "width": null
       }
      },
-     "93fbc32b63da46d384de5f39548125bb": {
+     "c7b7b31f2c604a1196546e2997bc0c66": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "c918b740c0fb460488a6f657ba79e328": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1624,7 +1834,7 @@
        "width": null
       }
      },
-     "9c71b1b4a11f45968df0d0c29019a597": {
+     "c94e80905dbd4467a66eb15c5337b874": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1677,139 +1887,60 @@
        "width": null
       }
      },
-     "9f1849010d834788aa304a0758ae0a1a": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_93fbc32b63da46d384de5f39548125bb",
-       "placeholder": "​",
-       "style": "IPY_MODEL_7748851a2ae048a4b89a167f28dace99",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "COLLECTING RESULTS | : 100%"
-      }
-     },
-     "b7999bd16748473996d328d4f13fe362": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_874a71279f88456ea2febf8df9292b00",
-       "placeholder": "​",
-       "style": "IPY_MODEL_c0f4e46c194d483eb43a4668d9519b12",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
-      }
-     },
-     "c0f4e46c194d483eb43a4668d9519b12": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "c12d9ee611ea4ecca0b7561cc616f137": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_9f1849010d834788aa304a0758ae0a1a",
-        "IPY_MODEL_f7d538f191d04c1ab10c2c3ffc430b96",
-        "IPY_MODEL_e27320ba73684091af234f5b9930eb7e"
-       ],
-       "layout": "IPY_MODEL_39cd0dcdc92e4024b46048009aeb71b4",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "cc773c0630824c43b68d4d3b15ebd5fb": {
-      "model_module": "@jupyter-widgets/controls",
+     "cb66396c16f74903af9d2c98515b3594": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "d337f9a0ef2348d08835c6742a269707": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_8f9e30349a6c4445b1efc001d4386ed3",
-       "max": 1.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_095703066ff14ea4ab7e0c6a3af1f43c",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 1.0
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "d52d51cba07c42e78a079d4e41ff9b6f": {
+     "dd782e76e307437bb90a4afa7bac4827": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HBoxModel",
@@ -1824,16 +1955,16 @@
        "_view_name": "HBoxView",
        "box_style": "",
        "children": [
-        "IPY_MODEL_7ff2be226e374d739011b7e26dc8cab9",
-        "IPY_MODEL_dea132fc5f1f4c17b10e73fcf175c8f4",
-        "IPY_MODEL_3367b617a09d4f00a1d7a258ff3f67f0"
+        "IPY_MODEL_435d337bceb44597bead638d5850e005",
+        "IPY_MODEL_541c1134ac454078b4989985e6df8fb9",
+        "IPY_MODEL_6e859ebf434c461caff7a96afcb64407"
        ],
-       "layout": "IPY_MODEL_0a328e07873d4855bd03775d797c8730",
+       "layout": "IPY_MODEL_e07ad106fbd8464ea3a1e74d56a549cb",
        "tabbable": null,
        "tooltip": null
       }
      },
-     "de71d5f46cca4bf0a65b89fcf588f002": {
+     "e07ad106fbd8464ea3a1e74d56a549cb": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1886,56 +2017,43 @@
        "width": null
       }
      },
-     "dea132fc5f1f4c17b10e73fcf175c8f4": {
+     "e9b28f4d23134ae8ab8f7d45bd8ed8c2": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_f053133ab52647458863991c49f0c68e",
-       "max": 1.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_6dccbe75ff4747d381864550ebce72eb",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 1.0
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "e27320ba73684091af234f5b9930eb7e": {
+     "eb2aa718055f4037afea898c891bac39": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_de71d5f46cca4bf0a65b89fcf588f002",
-       "placeholder": "​",
-       "style": "IPY_MODEL_f27416801cb049c3a170298199434e85",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 1/1 [00:00&lt;00:00, 133.70it/s]"
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "f053133ab52647458863991c49f0c68e": {
+     "ee19d40b63aa4ef691061b855ac3b64e": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1987,50 +2105,6 @@
        "visibility": null,
        "width": null
       }
-     },
-     "f27416801cb049c3a170298199434e85": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "f7d538f191d04c1ab10c2c3ffc430b96": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_9c71b1b4a11f45968df0d0c29019a597",
-       "max": 1.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_4514de7881bc486c9cddf90e085c7fdb",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 1.0
-      }
      }
     },
     "version_major": 2,
diff --git a/docs/iceflow-with-icepyx.ipynb b/docs/iceflow-with-icepyx.ipynb
index ae63d99..b1cf1ae 100644
--- a/docs/iceflow-with-icepyx.ipynb
+++ b/docs/iceflow-with-icepyx.ipynb
@@ -47,10 +47,10 @@
    "id": "2ad99b0d-4e15-466c-b9aa-7bfa75ef5f26",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:18:25.101422Z",
-     "iopub.status.busy": "2024-11-08T18:18:25.100773Z",
-     "iopub.status.idle": "2024-11-08T18:18:27.894676Z",
-     "shell.execute_reply": "2024-11-08T18:18:27.894150Z"
+     "iopub.execute_input": "2024-12-09T17:35:54.192543Z",
+     "iopub.status.busy": "2024-12-09T17:35:54.192247Z",
+     "iopub.status.idle": "2024-12-09T17:35:56.824194Z",
+     "shell.execute_reply": "2024-12-09T17:35:56.823710Z"
     }
    },
    "outputs": [
@@ -58,7 +58,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_138573/2137618702.py:6: FutureWarning: icepyx v1.x is being deprecated; the back-end systems on which it relies\n",
+      "/tmp/ipykernel_163498/2248149546.py:6: FutureWarning: icepyx v1.x is being deprecated; the back-end systems on which it relies\n",
       "will be shut down as of late 2024. At that time, upgrade to icepyx v2.x, which uses the\n",
       "new NASA Harmony back-end, will be required. Please see\n",
       "<https://icepyx.readthedocs.io/en/latest/user_guide/changelog/v1.3.0.html> for more\n",
@@ -599,11 +599,11 @@
       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
        "<div id='p1002'>\n",
-       "  <div id=\"a06a2184-bae9-479e-bfe6-82f4c6c91982\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
+       "  <div id=\"fd5fa07b-2a41-4632-a2ba-e551570685fd\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
-       "  var docs_json = {\"0fc49caf-21f8-46df-9636-a054861db746\":{\"version\":\"3.6.0\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"e36e6e4e536146679bb46d60242127a8\",\"client_comm_id\":\"d991b5ecfe9d4068945eb5a3f7b5253c\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\"},{\"type\":\"model\",\"name\":\"JSComponent1\"},{\"type\":\"model\",\"name\":\"ReactComponent1\"},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\"},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
-       "  var render_items = [{\"docid\":\"0fc49caf-21f8-46df-9636-a054861db746\",\"roots\":{\"p1002\":\"a06a2184-bae9-479e-bfe6-82f4c6c91982\"},\"root_ids\":[\"p1002\"]}];\n",
+       "  var docs_json = {\"c07d0974-a8ec-4e01-bb71-fc1684d0464b\":{\"version\":\"3.6.0\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"b98e7aa8a42346c6bd9d4cadf60c53f4\",\"client_comm_id\":\"69d7d2094d434330ad2c82a2c47d576f\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\"},{\"type\":\"model\",\"name\":\"JSComponent1\"},{\"type\":\"model\",\"name\":\"ReactComponent1\"},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\"},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
+       "  var render_items = [{\"docid\":\"c07d0974-a8ec-4e01-bb71-fc1684d0464b\",\"roots\":{\"p1002\":\"fd5fa07b-2a41-4632-a2ba-e551570685fd\"},\"root_ids\":[\"p1002\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -780,9 +780,14 @@
     "import pandas as pd\n",
     "import xarray as xr\n",
     "\n",
-    "from nsidc.iceflow.api import fetch_iceflow_df, create_iceflow_parquet\n",
-    "from nsidc.iceflow.data import ALL_DATASETS\n",
-    "from nsidc.iceflow.data.models import DatasetSearchParameters, BoundingBox, IceflowDataFrame"
+    "from nsidc.iceflow import (\n",
+    "    make_iceflow_parquet,\n",
+    "    DatasetSearchParameters,\n",
+    "    BoundingBox,\n",
+    "    find_iceflow_data,\n",
+    "    download_iceflow_results,\n",
+    "    IceflowDataFrame\n",
+    ")"
    ]
   },
   {
@@ -803,10 +808,10 @@
    "id": "d7143806-d23d-421a-8b7a-3ca15b05f7cf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:18:27.896437Z",
-     "iopub.status.busy": "2024-11-08T18:18:27.896322Z",
-     "iopub.status.idle": "2024-11-08T18:18:27.899000Z",
-     "shell.execute_reply": "2024-11-08T18:18:27.898405Z"
+     "iopub.execute_input": "2024-12-09T17:35:56.825775Z",
+     "iopub.status.busy": "2024-12-09T17:35:56.825623Z",
+     "iopub.status.idle": "2024-12-09T17:35:56.828247Z",
+     "shell.execute_reply": "2024-12-09T17:35:56.827900Z"
     }
    },
    "outputs": [],
@@ -831,46 +836,89 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ac0b6bf-41f5-44b7-9703-fce6c4b5e589",
+   "id": "420bf37c-c5cb-4339-bd26-ebb91ecb3973",
    "metadata": {},
    "source": [
-    "Next we use the `create_iceflow_parquet` function from the `iceflow` API. This function:\n",
-    "\n",
-    "* Finds data matching our `BBOX`, `DATE_RANGE`, and desired datasets\n",
-    "* Downloads and reads the data from the datasets' native formats\n",
-    "* Transforms all of the lat/lon/elev data into a target ITRF\n",
-    "* Writes out the lat/lon/elev data to a parquet dataset that can be be read by e.g., `dask` for further processing. \n",
+    "Next we will use the `find_iceflow_data` function from the `iceflow` API to find data matching our area of interest.\n",
     "\n",
-    "Writing data to a parquet dataset allows `dask` (which we will use later!) to read the chunks of data it needs to do calculations (e.g., `mean`) without needing to read all of the data into memory at once. This is important because `iceflow` can find many millions of data points for even small areas of interest!\n",
-    "\n",
-    "**Note: This next step may take a while, and will download data to your local disk.**"
+    "By default, `DatasetSearchParameters` will include all `iceflow` supported datasets, unless one or more are specified as a filter with the `datasets` kwarg. There may be warnings raised about there not being search results for specific datasets supported by `iceflow`."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "713b93dd-d23b-422b-92dc-f9ed364a566c",
+   "id": "ee315618-32ad-4710-9629-0a3d2e2ed26b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:18:27.900384Z",
-     "iopub.status.busy": "2024-11-08T18:18:27.900268Z",
-     "iopub.status.idle": "2024-11-08T18:24:50.195202Z",
-     "shell.execute_reply": "2024-11-08T18:24:50.194544Z"
+     "iopub.execute_input": "2024-12-09T17:35:56.829407Z",
+     "iopub.status.busy": "2024-12-09T17:35:56.829265Z",
+     "iopub.status.idle": "2024-12-09T17:36:13.320654Z",
+     "shell.execute_reply": "2024-12-09T17:36:13.320060Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2024-12-09 10:36:09.114\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_find_iceflow_data\u001b[0m:\u001b[36m49\u001b[0m - \u001b[33m\u001b[1mFound no results for dataset.short_name='ILVIS2' dataset.version='1' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28))\u001b[0m\n"
+     ]
     },
-    "scrolled": true
+    {
+     "data": {
+      "text/plain": [
+       "6"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_results = find_iceflow_data(\n",
+    "    dataset_search_params=DatasetSearchParameters(\n",
+    "        bounding_box=BBOX,\n",
+    "        temporal=DATE_RANGE,\n",
+    "    ),\n",
+    ")\n",
+    "len(search_results)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b57c25fc-ebf1-4397-bcb7-076428855b7c",
+   "metadata": {},
+   "source": [
+    "Now download the matching files to disk using `download_iceflow_results`.\n",
+    "\n",
+    "**Note: This next step may take a while, and will download data to your local disk.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "84e53851-53a8-49e0-bce3-2789253498b6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-12-09T17:36:13.323061Z",
+     "iopub.status.busy": "2024-12-09T17:36:13.322806Z",
+     "iopub.status.idle": "2024-12-09T17:37:50.625700Z",
+     "shell.execute_reply": "2024-12-09T17:37:50.625180Z"
+    }
    },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:18:34.613\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 4 granules for short_name='ILATM1B' version='1' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28)). Downloading to downloaded-data/ILATM1B.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:36:13.324\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 4 granules to downloaded-data/ILATM1B_1.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "18e148d672b74e8e972bf6b64c91a98d",
+       "model_id": "53df9e177168414490ccff53eb90e7de",
        "version_major": 2,
        "version_minor": 0
       },
@@ -884,7 +932,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b1ad7a617ff84c2091192f13e2d5b064",
+       "model_id": "f67f65d982d74f4fb6532b8660ada12c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -898,7 +946,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "173ea4543899491a961a8f6d8c19f841",
+       "model_id": "d488657e901d40fbbc87f151a4a4529e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -913,13 +961,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:19:34.015\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 14 granules for short_name='ILATM1B' version='2' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28)). Downloading to downloaded-data/ILATM1B.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:36:30.946\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 14 granules to downloaded-data/ILATM1B_2.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "662a8975e3414745957e8d8f54d0dc57",
+       "model_id": "3ecb098dfac34ee0bcfabe422b3aba88",
        "version_major": 2,
        "version_minor": 0
       },
@@ -933,7 +981,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1b401e8bd9fb4ece9b604ea7866693e2",
+       "model_id": "d365480879ee46e68db80d46cb40444e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -947,7 +995,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "aa6a8719dbc04f17863173f186a454f8",
+       "model_id": "72f5a56fadaa40b2a8904fe86e3f333d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -962,13 +1010,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:21:35.976\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 13 granules for short_name='BLATM1B' version='1' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28)). Downloading to downloaded-data/BLATM1B.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:36:47.008\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 13 granules to downloaded-data/BLATM1B_1.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b46b84e797ba4451a1105861f08c554b",
+       "model_id": "d44038cacc8d42e8abfd86d0a4e826c6",
        "version_major": 2,
        "version_minor": 0
       },
@@ -982,7 +1030,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "907981d2e2064d04819ee2c8868e7dea",
+       "model_id": "8ac62732d56b427b8b117d0bbe51aa98",
        "version_major": 2,
        "version_minor": 0
       },
@@ -996,7 +1044,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "785dba9c597540aca19a9ee6cfb1f390",
+       "model_id": "5c543e0ea83243e58bcb9469a0dacedb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1011,20 +1059,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:24:12.875\u001b[0m | \u001b[31m\u001b[1mERROR   \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m45\u001b[0m - \u001b[31m\u001b[1mFound no results for short_name='ILVIS2' version='1' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28))\u001b[0m\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[32m2024-11-08 11:24:17.157\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 2 granules for short_name='ILVIS2' version='2' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28)). Downloading to downloaded-data/ILVIS2.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:37:28.317\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 2 granules to downloaded-data/ILVIS2_2.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "da747d77e487435eb2b472021bc4da5b",
+       "model_id": "1804ec2ca7fa4c5195d439dada4eba1c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1038,7 +1079,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "84bbd4eac9d9407aaba7ca651dcb80dc",
+       "model_id": "b5449ac16c6e4fb7b1945fda779f515b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1052,7 +1093,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e3206794d112407883b49ceba87baad4",
+       "model_id": "c21cbd2f6343466eb15bc229b4fd245f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1067,13 +1108,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-11-08 11:24:45.420\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36msearch_and_download\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound 8 granules for short_name='GLAH06' version='034' with bounding_box=BoundingBox(lower_left_lon=-49.149, lower_left_lat=69.186, upper_right_lon=-48.949, upper_right_lat=69.238) temporal=(datetime.date(2007, 1, 1), datetime.date(2024, 10, 28)). Downloading to downloaded-data/GLAH06.\u001b[0m\n"
+      "\u001b[32m2024-12-09 10:37:46.713\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mnsidc.iceflow.data.fetch\u001b[0m:\u001b[36m_download_iceflow_search_result\u001b[0m:\u001b[36m68\u001b[0m - \u001b[1mDownloading 8 granules to downloaded-data/GLAH06_034.\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "790079f3073b4943bb70452c35b62013",
+       "model_id": "93b5a434ba33408fb7284a1a5a268b60",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1087,7 +1128,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "eb4ddd4c29a844939c8970f9f5404f7a",
+       "model_id": "fb935d04a3fa4d70b17eecf880d6f78e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1101,7 +1142,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "04d61391e332496c8db06205f0c722d3",
+       "model_id": "fd5ccd1dca8a4bf5aff667fe5e46d41e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1114,16 +1155,38 @@
     }
    ],
    "source": [
-    "parquet_path = create_iceflow_parquet(\n",
-    "    dataset_search_params=DatasetSearchParameters(\n",
-    "        # `ALL_DATASETS` is a list that contains all of the datasets supported by iceflow.\n",
-    "        # This lets us find all the data iceflow supports for our area of interest.\n",
-    "        datasets=ALL_DATASETS,\n",
-    "        bounding_box=BBOX,\n",
-    "        temporal=DATE_RANGE,\n",
-    "    ),\n",
+    "downloaded_files = download_iceflow_results(search_results, output_dir=OUTPUT_DIR)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fee85cd6-522f-4352-86ea-9530add68000",
+   "metadata": {},
+   "source": [
+    "Finally, we will create a parquet dataset using `make_iceflow_parquet`.Writing data to a parquet dataset allows `dask` (which we will use later!) to read the chunks of data it needs to do calculations (e.g., `mean`) without needing to read all of the data into memory at once. This is important because `iceflow` can find many millions of data points for even small areas of interest!\n",
+    "\n",
+    "This function transforms all data found in the `data_dir` to the provided `target_itrf`, further facilitating analysis across many datasets. \n",
+    "\n",
+    "**Note: This next step may take a while**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "17e03a49-405a-4d00-a08d-74e5890564da",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-12-09T17:37:50.627629Z",
+     "iopub.status.busy": "2024-12-09T17:37:50.627365Z",
+     "iopub.status.idle": "2024-12-09T17:42:56.593466Z",
+     "shell.execute_reply": "2024-12-09T17:42:56.592058Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "parquet_path = make_iceflow_parquet(\n",
+    "    data_dir=OUTPUT_DIR,\n",
     "    target_itrf=ICESAT2_ITRF,\n",
-    "    output_dir=OUTPUT_DIR,\n",
     "    overwrite=True,\n",
     ")"
    ]
@@ -1138,14 +1201,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "id": "e29f9cf9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:24:50.197205Z",
-     "iopub.status.busy": "2024-11-08T18:24:50.197012Z",
-     "iopub.status.idle": "2024-11-08T18:24:51.931464Z",
-     "shell.execute_reply": "2024-11-08T18:24:51.931118Z"
+     "iopub.execute_input": "2024-12-09T17:42:56.613781Z",
+     "iopub.status.busy": "2024-12-09T17:42:56.613570Z",
+     "iopub.status.idle": "2024-12-09T17:43:01.607748Z",
+     "shell.execute_reply": "2024-12-09T17:43:01.607275Z"
     }
    },
    "outputs": [
@@ -1233,7 +1296,7 @@
        "2007-03-12 06:40:00.520415  50.200840 -41.988417  39.976656  GLAH06v034"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1263,24 +1326,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "id": "bda00a2c-51dd-4d01-8ba4-4dcb0985931d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:24:51.933593Z",
-     "iopub.status.busy": "2024-11-08T18:24:51.933439Z",
-     "iopub.status.idle": "2024-11-08T18:24:52.181367Z",
-     "shell.execute_reply": "2024-11-08T18:24:52.180651Z"
+     "iopub.execute_input": "2024-12-09T17:43:01.615992Z",
+     "iopub.status.busy": "2024-12-09T17:43:01.615838Z",
+     "iopub.status.idle": "2024-12-09T17:43:02.136180Z",
+     "shell.execute_reply": "2024-12-09T17:43:02.135900Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<icepyx.core.query.Query at 0x783e1ef3e420>"
+       "<icepyx.core.query.Query at 0x7299a33de930>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1305,19 +1368,21 @@
    "id": "25fbed4b-beb7-41d8-a4fd-788e4821e505",
    "metadata": {},
    "source": [
-    "Now we download the results.  Note that this may take a while to download data to local disk."
+    "Now we download the results.  Note that this may take a while to download data to local disk.\n",
+    "\n",
+    "**Note: This next step may take a while**"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "id": "0c146fa2-fdb9-4774-a6bf-481e2498948a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:24:52.184830Z",
-     "iopub.status.busy": "2024-11-08T18:24:52.184502Z",
-     "iopub.status.idle": "2024-11-08T18:25:38.300377Z",
-     "shell.execute_reply": "2024-11-08T18:25:38.299806Z"
+     "iopub.execute_input": "2024-12-09T17:43:02.137768Z",
+     "iopub.status.busy": "2024-12-09T17:43:02.137627Z",
+     "iopub.status.idle": "2024-12-09T17:43:35.631894Z",
+     "shell.execute_reply": "2024-12-09T17:43:35.631432Z"
     }
    },
    "outputs": [
@@ -1333,7 +1398,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "order ID:  5000005843104\n"
+      "order ID:  5000005880685\n"
      ]
     },
     {
@@ -1414,7 +1479,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Data request 5000005843104 of  1  order(s) is downloaded.\n"
+      "Data request 5000005880685 of  1  order(s) is downloaded.\n"
      ]
     },
     {
@@ -1443,14 +1508,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "id": "081376b5-308b-43c3-bc6d-b9c4342586d0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:38.302725Z",
-     "iopub.status.busy": "2024-11-08T18:25:38.302512Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.566633Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.566028Z"
+     "iopub.execute_input": "2024-12-09T17:43:35.633698Z",
+     "iopub.status.busy": "2024-12-09T17:43:35.633528Z",
+     "iopub.status.idle": "2024-12-09T17:43:53.899294Z",
+     "shell.execute_reply": "2024-12-09T17:43:53.898753Z"
     }
    },
    "outputs": [
@@ -1519,7 +1584,7 @@
        "49"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1541,14 +1606,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "id": "dc7fc4b2-37ee-4f44-a21e-d6225eccc0f8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.568790Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.568661Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.632074Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.631336Z"
+     "iopub.execute_input": "2024-12-09T17:43:53.901216Z",
+     "iopub.status.busy": "2024-12-09T17:43:53.901069Z",
+     "iopub.status.idle": "2024-12-09T17:43:53.980260Z",
+     "shell.execute_reply": "2024-12-09T17:43:53.979962Z"
     }
    },
    "outputs": [
@@ -1946,12 +2011,12 @@
        "Attributes:\n",
        "    data_product:  ATL06\n",
        "    Description:   The land_ice_height group contains the primary set of deri...\n",
-       "    data_rate:     Data within this group are sparse.  Data values are provid...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c700df15-a206-47da-94a0-c7d500cc1c10' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c700df15-a206-47da-94a0-c7d500cc1c10' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 5</li><li><span class='xr-has-index'>spot</span>: 5</li><li><span class='xr-has-index'>photon_idx</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7040fa9c-198b-4f07-aa5f-d6ec27a45936' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7040fa9c-198b-4f07-aa5f-d6ec27a45936' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-f4cf7851-aca8-4838-b50e-2ec96f0ac05c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f4cf7851-aca8-4838-b50e-2ec96f0ac05c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3d152fe-d80d-4495-b181-6ad094803cfe' class='xr-var-data-in' type='checkbox'><label for='data-a3d152fe-d80d-4495-b181-6ad094803cfe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2 3 4 5</div><input id='attrs-7271f38e-4ada-4ac1-a381-ff9238aadb90' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7271f38e-4ada-4ac1-a381-ff9238aadb90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-564161e8-7157-4815-8307-f6c726fb94ba' class='xr-var-data-in' type='checkbox'><label for='data-564161e8-7157-4815-8307-f6c726fb94ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>uint64</div><div class='xr-var-preview xr-preview'>122207 66614 122201 22418 22404</div><input id='attrs-a0fa8729-f546-4c92-bd9b-2d79ff39c8ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0fa8729-f546-4c92-bd9b-2d79ff39c8ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-427325c4-7f6b-43c9-bc43-5da2414e833a' class='xr-var-data-in' type='checkbox'><label for='data-427325c4-7f6b-43c9-bc43-5da2414e833a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([122207,  66614, 122201,  22418,  22404], dtype=uint64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U71</div><div class='xr-var-preview xr-preview'>&#x27;downloaded-data/ATL06/processed...</div><input id='attrs-acdb5c50-cad5-4d78-9f7e-d2307e721fbe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acdb5c50-cad5-4d78-9f7e-d2307e721fbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-916a1c82-247e-4408-9072-e3047c585f2b' class='xr-var-data-in' type='checkbox'><label for='data-916a1c82-247e-4408-9072-e3047c585f2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;downloaded-data/ATL06/processed_ATL06_20200913090149_12220803_006_02.h5&#x27;,\n",
+       "    data_rate:     Data within this group are sparse.  Data values are provid...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c05e0464-bb6a-4500-9b4a-b23c95eeb519' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c05e0464-bb6a-4500-9b4a-b23c95eeb519' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 5</li><li><span class='xr-has-index'>spot</span>: 5</li><li><span class='xr-has-index'>photon_idx</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5cb26bfe-b4ee-423e-a512-1ad33ed0d5c4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5cb26bfe-b4ee-423e-a512-1ad33ed0d5c4' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-aad1955a-bfaf-471a-87c7-95eade336bd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aad1955a-bfaf-471a-87c7-95eade336bd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21768111-2029-4ef2-bab0-b9b3d729e77a' class='xr-var-data-in' type='checkbox'><label for='data-21768111-2029-4ef2-bab0-b9b3d729e77a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2 3 4 5</div><input id='attrs-8056edb7-575b-40a5-a828-c0adf13035ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8056edb7-575b-40a5-a828-c0adf13035ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a9fafdc-86ff-4ccf-bb1d-7db29eb0ac99' class='xr-var-data-in' type='checkbox'><label for='data-0a9fafdc-86ff-4ccf-bb1d-7db29eb0ac99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4, 5], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>uint64</div><div class='xr-var-preview xr-preview'>122207 66614 122201 22418 22404</div><input id='attrs-eefa7514-2cf6-4089-b0b8-0813c87574d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eefa7514-2cf6-4089-b0b8-0813c87574d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e03c6d8-c67a-431f-b65f-df18d2dfe9ed' class='xr-var-data-in' type='checkbox'><label for='data-6e03c6d8-c67a-431f-b65f-df18d2dfe9ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([122207,  66614, 122201,  22418,  22404], dtype=uint64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U71</div><div class='xr-var-preview xr-preview'>&#x27;downloaded-data/ATL06/processed...</div><input id='attrs-d660cc46-5ead-4508-8c92-57abc32365bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d660cc46-5ead-4508-8c92-57abc32365bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee5678ef-2f6c-4b45-b4b1-b2b19a7a99f5' class='xr-var-data-in' type='checkbox'><label for='data-ee5678ef-2f6c-4b45-b4b1-b2b19a7a99f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;downloaded-data/ATL06/processed_ATL06_20200913090149_12220803_006_02.h5&#x27;,\n",
        "       &#x27;downloaded-data/ATL06/processed_ATL06_20220505170624_06661505_006_01.h5&#x27;,\n",
        "       &#x27;downloaded-data/ATL06/processed_ATL06_20190318110313_12220203_006_02.h5&#x27;,\n",
        "       &#x27;downloaded-data/ATL06/processed_ATL06_20230405010947_02241905_006_02.h5&#x27;,\n",
        "       &#x27;downloaded-data/ATL06/processed_ATL06_20191011135158_02240505_006_02.h5&#x27;],\n",
-       "      dtype=&#x27;&lt;U71&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(gran_idx, photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:04:22.172388928 .....</div><input id='attrs-b080b524-ea6f-4ee3-8fd5-d8d54f1102ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b080b524-ea6f-4ee3-8fd5-d8d54f1102ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7502af7-77d2-4a95-a0a0-9660121c8aa4' class='xr-var-data-in' type='checkbox'><label for='data-f7502af7-77d2-4a95-a0a0-9660121c8aa4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Number of GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd><dt><span>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2020-09-13T09:04:22.172388928&#x27;, &#x27;2020-09-13T09:04:22.175207936&#x27;,\n",
+       "      dtype=&#x27;&lt;U71&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(gran_idx, photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:04:22.172388928 .....</div><input id='attrs-cfb8cb82-2486-4f8d-b54d-ce741e5eca30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfb8cb82-2486-4f8d-b54d-ce741e5eca30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38c5488d-c812-473c-877e-aee985bcd927' class='xr-var-data-in' type='checkbox'><label for='data-38c5488d-c812-473c-877e-aee985bcd927' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Number of GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd><dt><span>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2020-09-13T09:04:22.172388928&#x27;, &#x27;2020-09-13T09:04:22.175207936&#x27;,\n",
        "        &#x27;2020-09-13T09:04:22.178032944&#x27;, &#x27;2020-09-13T09:04:22.180859024&#x27;,\n",
        "        &#x27;2020-09-13T09:04:22.183685712&#x27;],\n",
        "       [&#x27;2022-05-05T17:09:19.400209344&#x27;, &#x27;2022-05-05T17:09:19.403033312&#x27;,\n",
@@ -1965,13 +2030,13 @@
        "        &#x27;2023-04-05T01:12:36.659772672&#x27;],\n",
        "       [&#x27;2019-10-11T13:54:48.679390608&#x27;, &#x27;2019-10-11T13:54:48.738590504&#x27;,\n",
        "        &#x27;2019-10-11T13:54:48.741417288&#x27;, &#x27;2019-10-11T13:54:48.755482168&#x27;,\n",
-       "                                  &#x27;NaT&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-038d228e-6932-400c-9c29-826cca48e55d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-038d228e-6932-400c-9c29-826cca48e55d' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0 0 0 0 1</div><input id='attrs-e52fe204-8268-4779-b217-e22e88f3f444' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e52fe204-8268-4779-b217-e22e88f3f444' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f6c7728-7505-417e-b383-76b5c3980c57' class='xr-var-data-in' type='checkbox'><label for='data-9f6c7728-7505-417e-b383-76b5c3980c57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, 0, 1], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>8 15 2 19 5</div><input id='attrs-9433b709-d685-4d79-98a4-c573268ecd93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9433b709-d685-4d79-98a4-c573268ecd93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95c59049-9660-48a8-9659-5eb5fbeb0128' class='xr-var-data-in' type='checkbox'><label for='data-95c59049-9660-48a8-9659-5eb5fbeb0128' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 8, 15,  2, 19,  5], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>1222 666 1222 224 224</div><input id='attrs-26d0f064-ce92-482c-8ff6-560b6399414a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26d0f064-ce92-482c-8ff6-560b6399414a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5caecfdb-e404-43cb-9335-3cc3e4be75f9' class='xr-var-data-in' type='checkbox'><label for='data-5caecfdb-e404-43cb-9335-3cc3e4be75f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1222,  666, 1222,  224,  224], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18 ... 2018-01-...</div><input id='attrs-05c9ce2a-4d80-45f2-ac66-24635de469fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-05c9ce2a-4d80-45f2-ac66-24635de469fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cde2db9e-75ad-4397-97b4-907e13a2b484' class='xr-var-data-in' type='checkbox'><label for='data-cde2db9e-75ad-4397-97b4-907e13a2b484' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;, &#x27;2018-01-01T00:00:18.000000000&#x27;,\n",
+       "                                  &#x27;NaT&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4edbc1ee-2eda-4684-9a6e-2ac5bace2fee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4edbc1ee-2eda-4684-9a6e-2ac5bace2fee' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0 0 0 0 1</div><input id='attrs-a033c5cb-9bb5-41ab-bbc6-ebfc7c93b286' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a033c5cb-9bb5-41ab-bbc6-ebfc7c93b286' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-087393dc-618c-4884-979c-966a3a4caa64' class='xr-var-data-in' type='checkbox'><label for='data-087393dc-618c-4884-979c-966a3a4caa64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, 0, 1], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>8 15 2 19 5</div><input id='attrs-5f318f22-ecc2-4a52-a267-db0516b3ef46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f318f22-ecc2-4a52-a267-db0516b3ef46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f72fe1e2-24fe-4d95-bc50-867c3f5d4871' class='xr-var-data-in' type='checkbox'><label for='data-f72fe1e2-24fe-4d95-bc50-867c3f5d4871' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 8, 15,  2, 19,  5], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>1222 666 1222 224 224</div><input id='attrs-a4961e42-0ec4-4d97-af07-71e25d0bb7d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4961e42-0ec4-4d97-af07-71e25d0bb7d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8a08ad3-426b-490d-abc5-328fd49d10aa' class='xr-var-data-in' type='checkbox'><label for='data-c8a08ad3-426b-490d-abc5-328fd49d10aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1222,  666, 1222,  224,  224], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18 ... 2018-01-...</div><input id='attrs-3c1af49d-a042-47c6-bc1e-a00cc1a88215' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c1af49d-a042-47c6-bc1e-a00cc1a88215' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30326f61-964b-4cd4-b883-8742ff59e562' class='xr-var-data-in' type='checkbox'><label for='data-30326f61-964b-4cd4-b883-8742ff59e562' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;, &#x27;2018-01-01T00:00:18.000000000&#x27;,\n",
        "       &#x27;2018-01-01T00:00:18.000000000&#x27;, &#x27;2018-01-01T00:00:18.000000000&#x27;,\n",
-       "       &#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:02:02.965879 ... 2...</div><input id='attrs-f016b7dc-6f8d-40eb-aeb4-d1909ac8cea0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f016b7dc-6f8d-40eb-aeb4-d1909ac8cea0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d7d8273-b973-41ce-88f3-45e5da4d0bca' class='xr-var-data-in' type='checkbox'><label for='data-0d7d8273-b973-41ce-88f3-45e5da4d0bca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-09-13T09:02:02.965879000&#x27;, &#x27;2022-05-05T17:06:28.197561000&#x27;,\n",
+       "       &#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:02:02.965879 ... 2...</div><input id='attrs-3d386509-f7bb-4f1a-ae5c-b9fb8f9f0d44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d386509-f7bb-4f1a-ae5c-b9fb8f9f0d44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68a8a1c8-74a1-4e9e-a0f4-b1d5ce4b896e' class='xr-var-data-in' type='checkbox'><label for='data-68a8a1c8-74a1-4e9e-a0f4-b1d5ce4b896e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-09-13T09:02:02.965879000&#x27;, &#x27;2022-05-05T17:06:28.197561000&#x27;,\n",
        "       &#x27;2019-03-18T11:03:27.347613000&#x27;, &#x27;2023-04-05T01:09:45.201298000&#x27;,\n",
-       "       &#x27;2019-10-11T13:51:57.388971000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:07:14.250132 ... 2...</div><input id='attrs-17e6adcd-656d-450c-be57-dd912cc7c641' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17e6adcd-656d-450c-be57-dd912cc7c641' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce0c5abf-a245-4851-b814-30fa5ac94af4' class='xr-var-data-in' type='checkbox'><label for='data-ce0c5abf-a245-4851-b814-30fa5ac94af4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-09-13T09:07:14.250132000&#x27;, &#x27;2022-05-05T17:11:08.953275000&#x27;,\n",
+       "       &#x27;2019-10-11T13:51:57.388971000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-09-13T09:07:14.250132 ... 2...</div><input id='attrs-5219aae4-e700-480c-bc53-01b28704861c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5219aae4-e700-480c-bc53-01b28704861c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6207463-cf99-4f45-add3-1017eb4aea5f' class='xr-var-data-in' type='checkbox'><label for='data-d6207463-cf99-4f45-add3-1017eb4aea5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-09-13T09:07:14.250132000&#x27;, &#x27;2022-05-05T17:11:08.953275000&#x27;,\n",
        "       &#x27;2019-03-18T11:08:38.956207000&#x27;, &#x27;2023-04-05T01:14:22.410260000&#x27;,\n",
-       "       &#x27;2019-10-11T13:56:34.156353000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3d9542d1-9d32-4ce6-90e3-56e11cdc1a1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d9542d1-9d32-4ce6-90e3-56e11cdc1a1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2110601e-97b5-4b61-9718-ea8336340bb2' class='xr-var-data-in' type='checkbox'><label for='data-2110601e-97b5-4b61-9718-ea8336340bb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Standard land-ice segment height determined by land ice algorithm, corrected for first-photon bias, representing the median- based height of the selected PEs</dd><dt><span>long_name :</span></dt><dd>Land Ice height</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[[      nan,       nan,       nan,       nan,       nan],\n",
+       "       &#x27;2019-10-11T13:56:34.156353000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3ad45cac-fe4a-4173-8372-e4b34fcfcbce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ad45cac-fe4a-4173-8372-e4b34fcfcbce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7eddfc83-9a97-4b47-bd91-9892ebfbeb21' class='xr-var-data-in' type='checkbox'><label for='data-7eddfc83-9a97-4b47-bd91-9892ebfbeb21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Standard land-ice segment height determined by land ice algorithm, corrected for first-photon bias, representing the median- based height of the selected PEs</dd><dt><span>long_name :</span></dt><dd>Land Ice height</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[[      nan,       nan,       nan,       nan,       nan],\n",
        "        [      nan,       nan,       nan,       nan,       nan],\n",
        "        [      nan,       nan,       nan,       nan,       nan],\n",
        "        [791.1915 , 791.431  , 791.43225, 791.37   , 791.3978 ],\n",
@@ -2000,7 +2065,7 @@
        "        [815.0689 , 810.5152 , 806.9575 , 806.5851 , 808.393  ],\n",
        "        [      nan,       nan,       nan,       nan,       nan],\n",
        "        [      nan,       nan,       nan,       nan,       nan]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-11cc9ca6-7b9a-43e2-9320-f86b42dee50b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11cc9ca6-7b9a-43e2-9320-f86b42dee50b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6ea07a7-a960-454e-a2fa-91bf55ed6fd2' class='xr-var-data-in' type='checkbox'><label for='data-a6ea07a7-a960-454e-a2fa-91bf55ed6fd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Latitude of segment center, WGS84, North=+,</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[        nan,         nan,         nan,         nan,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-89b0df19-106f-41e9-a6bd-c84130294547' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89b0df19-106f-41e9-a6bd-c84130294547' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f30d2872-bc7e-41d8-840f-112b81757cbf' class='xr-var-data-in' type='checkbox'><label for='data-f30d2872-bc7e-41d8-840f-112b81757cbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Latitude of segment center, WGS84, North=+,</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[        nan,         nan,         nan,         nan,\n",
        "                 nan],\n",
        "        [        nan,         nan,         nan,         nan,\n",
        "                 nan],\n",
@@ -2040,7 +2105,7 @@
        "        [        nan,         nan,         nan,         nan,\n",
        "                 nan],\n",
        "        [        nan,         nan,         nan,         nan,\n",
-       "                 nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7d38a8d-3f3a-458b-afd8-60856ec83ca4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7d38a8d-3f3a-458b-afd8-60856ec83ca4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9039bd31-df43-4857-8dfd-b9b38191c771' class='xr-var-data-in' type='checkbox'><label for='data-9039bd31-df43-4857-8dfd-b9b38191c771' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Longitude of segment center, , WGS84, East=+</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[         nan,          nan,          nan,          nan,\n",
+       "                 nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3164896e-e401-40f7-96a5-8a69e88222df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3164896e-e401-40f7-96a5-8a69e88222df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-380f809d-2273-4062-9c0a-7696fe569709' class='xr-var-data-in' type='checkbox'><label for='data-380f809d-2273-4062-9c0a-7696fe569709' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Longitude of segment center, , WGS84, East=+</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[         nan,          nan,          nan,          nan,\n",
        "                  nan],\n",
        "        [         nan,          nan,          nan,          nan,\n",
        "                  nan],\n",
@@ -2080,11 +2145,11 @@
        "        [         nan,          nan,          nan,          nan,\n",
        "                  nan],\n",
        "        [         nan,          nan,          nan,          nan,\n",
-       "                  nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>nan nan &#x27;gt2l&#x27; ... nan nan nan</div><input id='attrs-1ebc6158-1919-468d-8e17-1d23390be802' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ebc6158-1919-468d-8e17-1d23390be802' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cbbe8fd-1cf1-4461-a124-cd6b26514b5a' class='xr-var-data-in' type='checkbox'><label for='data-0cbbe8fd-1cf1-4461-a124-cd6b26514b5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, &#x27;gt2l&#x27;, &#x27;gt2r&#x27;, &#x27;gt3l&#x27;],\n",
+       "                  nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>nan nan &#x27;gt2l&#x27; ... nan nan nan</div><input id='attrs-d7375128-e2ad-4457-a215-e5cf07595c37' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7375128-e2ad-4457-a215-e5cf07595c37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2b2d331-2f21-4031-9b07-501c60ccb0ba' class='xr-var-data-in' type='checkbox'><label for='data-c2b2d331-2f21-4031-9b07-501c60ccb0ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, &#x27;gt2l&#x27;, &#x27;gt2r&#x27;, &#x27;gt3l&#x27;],\n",
        "       [nan, nan, &#x27;gt2l&#x27;, &#x27;gt2r&#x27;, &#x27;gt3l&#x27;],\n",
        "       [nan, nan, nan, nan, &#x27;gt3l&#x27;],\n",
        "       [&#x27;gt1l&#x27;, &#x27;gt1r&#x27;, nan, nan, nan],\n",
-       "       [nan, nan, nan, nan, nan]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f0555c58-8dac-4ce0-81c8-f175a103786a' class='xr-section-summary-in' type='checkbox'  ><label for='section-f0555c58-8dac-4ce0-81c8-f175a103786a' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-140d79a3-67e1-4713-aef7-916af02ff848' class='xr-index-data-in' type='checkbox'/><label for='index-140d79a3-67e1-4713-aef7-916af02ff848' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48934a1e-ae8d-479d-b7cb-72739c50c363' class='xr-index-data-in' type='checkbox'/><label for='index-48934a1e-ae8d-479d-b7cb-72739c50c363' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5], dtype=&#x27;uint8&#x27;, name=&#x27;spot&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-41d432e7-1209-4ca1-a20c-b618d9dd3b7c' class='xr-index-data-in' type='checkbox'/><label for='index-41d432e7-1209-4ca1-a20c-b618d9dd3b7c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([122207, 66614, 122201, 22418, 22404], dtype=&#x27;uint64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81542c4a-ee86-4be9-b3ac-86cf1daf5fd8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-81542c4a-ee86-4be9-b3ac-86cf1daf5fd8' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL06</dd><dt><span>Description :</span></dt><dd>The land_ice_height group contains the primary set of derived ATL06 products. This includes geolocation, height, and standard error and quality measures for each segment. This group is sparse, meaning that parameters are provided only for pairs of segments for which at least one beam has a valid surface-height measurement.</dd><dt><span>data_rate :</span></dt><dd>Data within this group are sparse.  Data values are provided only for those ICESat-2 20m segments where at least one beam has a valid land ice height measurement.</dd></dl></div></li></ul></div></div>"
+       "       [nan, nan, nan, nan, nan]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2cbc249f-df24-43ea-ba19-842623d5e788' class='xr-section-summary-in' type='checkbox'  ><label for='section-2cbc249f-df24-43ea-ba19-842623d5e788' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b456f067-3899-43a2-8b75-4b400cc0c4a2' class='xr-index-data-in' type='checkbox'/><label for='index-b456f067-3899-43a2-8b75-4b400cc0c4a2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fd648681-679d-4f8d-bfe4-6a3da7278b07' class='xr-index-data-in' type='checkbox'/><label for='index-fd648681-679d-4f8d-bfe4-6a3da7278b07' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5], dtype=&#x27;uint8&#x27;, name=&#x27;spot&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ea1e17a4-4a4c-4f63-9033-eb2d53975907' class='xr-index-data-in' type='checkbox'/><label for='index-ea1e17a4-4a4c-4f63-9033-eb2d53975907' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([122207, 66614, 122201, 22418, 22404], dtype=&#x27;uint64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e62617f-9351-4ca9-ba20-16b28b1c8206' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e62617f-9351-4ca9-ba20-16b28b1c8206' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL06</dd><dt><span>Description :</span></dt><dd>The land_ice_height group contains the primary set of derived ATL06 products. This includes geolocation, height, and standard error and quality measures for each segment. This group is sparse, meaning that parameters are provided only for pairs of segments for which at least one beam has a valid surface-height measurement.</dd><dt><span>data_rate :</span></dt><dd>Data within this group are sparse.  Data values are provided only for those ICESat-2 20m segments where at least one beam has a valid land ice height measurement.</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 5kB\n",
@@ -2112,7 +2177,7 @@
        "    data_rate:     Data within this group are sparse.  Data values are provid..."
       ]
      },
-     "execution_count": 8,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2134,14 +2199,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "id": "09a51188-be09-486d-be10-a7bede9d02ce",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.633968Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.633818Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.636906Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.636171Z"
+     "iopub.execute_input": "2024-12-09T17:43:53.982508Z",
+     "iopub.status.busy": "2024-12-09T17:43:53.982391Z",
+     "iopub.status.idle": "2024-12-09T17:43:53.984774Z",
+     "shell.execute_reply": "2024-12-09T17:43:53.984480Z"
     }
    },
    "outputs": [],
@@ -2159,14 +2224,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "id": "422d0a32-b676-4fe2-89ba-14f31bba6e80",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.638690Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.638287Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.761795Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.761330Z"
+     "iopub.execute_input": "2024-12-09T17:43:53.986401Z",
+     "iopub.status.busy": "2024-12-09T17:43:53.986299Z",
+     "iopub.status.idle": "2024-12-09T17:43:54.090326Z",
+     "shell.execute_reply": "2024-12-09T17:43:54.090006Z"
     },
     "scrolled": true
    },
@@ -2270,7 +2335,7 @@
        "2023-04-05 01:12:36.659772672     1  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2312,14 +2377,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "id": "826ace9e-0638-4240-8769-5b0a1385b173",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.763238Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.763110Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.766887Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.766569Z"
+     "iopub.execute_input": "2024-12-09T17:43:54.092439Z",
+     "iopub.status.busy": "2024-12-09T17:43:54.092322Z",
+     "iopub.status.idle": "2024-12-09T17:43:54.095901Z",
+     "shell.execute_reply": "2024-12-09T17:43:54.095616Z"
     }
    },
    "outputs": [
@@ -2350,14 +2415,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "id": "fb60aa6c-4b9d-4592-95be-4687636ccd1b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.768225Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.768096Z",
-     "iopub.status.idle": "2024-11-08T18:25:55.786342Z",
-     "shell.execute_reply": "2024-11-08T18:25:55.786021Z"
+     "iopub.execute_input": "2024-12-09T17:43:54.097460Z",
+     "iopub.status.busy": "2024-12-09T17:43:54.097358Z",
+     "iopub.status.idle": "2024-12-09T17:43:54.116308Z",
+     "shell.execute_reply": "2024-12-09T17:43:54.115790Z"
     }
    },
    "outputs": [
@@ -2424,7 +2489,7 @@
        "2019-05-12    877.559574"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2445,14 +2510,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "id": "c5a76ba1-d2b1-49fd-96f7-bf41264c26a6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:25:55.788120Z",
-     "iopub.status.busy": "2024-11-08T18:25:55.787981Z",
-     "iopub.status.idle": "2024-11-08T18:26:21.514938Z",
-     "shell.execute_reply": "2024-11-08T18:26:21.514585Z"
+     "iopub.execute_input": "2024-12-09T17:43:54.118442Z",
+     "iopub.status.busy": "2024-12-09T17:43:54.118334Z",
+     "iopub.status.idle": "2024-12-09T17:44:22.375600Z",
+     "shell.execute_reply": "2024-12-09T17:44:22.375277Z"
     }
    },
    "outputs": [
@@ -2526,7 +2591,7 @@
        "2008-07-06    879.285982   BLATM1Bv1"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2560,30 +2625,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "id": "5e733fe6-cc28-4696-aadf-272fe755ad2c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-11-08T18:26:21.516783Z",
-     "iopub.status.busy": "2024-11-08T18:26:21.516637Z",
-     "iopub.status.idle": "2024-11-08T18:26:21.650263Z",
-     "shell.execute_reply": "2024-11-08T18:26:21.649780Z"
+     "iopub.execute_input": "2024-12-09T17:44:22.377566Z",
+     "iopub.status.busy": "2024-12-09T17:44:22.377381Z",
+     "iopub.status.idle": "2024-12-09T17:44:22.537385Z",
+     "shell.execute_reply": "2024-12-09T17:44:22.536628Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x783ddd567530>"
+       "<matplotlib.legend.Legend at 0x7299a0717da0>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1000x800 with 1 Axes>"
       ]
@@ -2660,7 +2725,59 @@
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
     "state": {
-     "01770cc92319437da696deec5b7174fd": {
+     "021908baf2db408698e5345a8a7dc741": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "FloatProgressModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_ea20a0a062984094885095a68938074c",
+       "max": 2.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_ffdd290fffb943b8b76793f28e17a0b8",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 2.0
+      }
+     },
+     "02c79c10bf5247e08a75f687330e4c33": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "FloatProgressModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_2b1e3498eeed41edb5f7d3b1d6cc3f72",
+       "max": 4.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_9cfa3e4e2e5a4a1884aa4570bbaf1fd3",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 4.0
+      }
+     },
+     "032f9568a78046a8aeb185d5a9aea001": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2713,31 +2830,7 @@
        "width": null
       }
      },
-     "04d61391e332496c8db06205f0c722d3": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_5c9f2ee490dd4bd0a66e8ec68c53a0ce",
-        "IPY_MODEL_11c501032abf4393ad8b13faa76d71d0",
-        "IPY_MODEL_5c850d5fb4e44e718214f3069b6b0ff1"
-       ],
-       "layout": "IPY_MODEL_c9ef6c38d1654b88958dada134e0eb44",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "09c661dd053047f4a143d5cfa8f83900": {
+     "056aa89ed3ad4d2da1203c831368622d": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2790,25 +2883,7 @@
        "width": null
       }
      },
-     "0a17167091ac418a8cdd463730c4ed9a": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "0a2ba616f12a478eb61cec54f12dc8d4": {
+     "06c326d8371843c2bad4a7ff77b8d8e9": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2861,7 +2936,30 @@
        "width": null
       }
      },
-     "0a90533d66fe41bca1a20b34e94879ab": {
+     "0b255b5981e54b13b80fab5c9920792a": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_2a93272882a14277ad69a5bf26a3d115",
+       "placeholder": "​",
+       "style": "IPY_MODEL_b0f7297d875b49f5b97ede53fd8c2d77",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "COLLECTING RESULTS | : 100%"
+      }
+     },
+     "0b66b9d4af1e41c6a527cf97746844b4": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2914,7 +3012,46 @@
        "width": null
       }
      },
-     "0d96d4f5f35f42f7a867122c00a65b60": {
+     "0ceefa68a59a47cca003f4c4e3ef5006": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_f1629a69f36a487da20b06f98f95e791",
+       "placeholder": "​",
+       "style": "IPY_MODEL_c529dea64e364c278f32f1c127c46b61",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 13/13 [00:00&lt;00:00, 1629.10it/s]"
+      }
+     },
+     "0ee1b729b5a44ca0bb367c15fc2aae25": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "0fee663d8b574bc3b8306611dda3a587": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2967,81 +3104,14 @@
        "width": null
       }
      },
-     "0f23257b3cf64b4a8c4754a2d3d2a0ba": {
-      "model_module": "@jupyter-widgets/controls",
+     "11df310392f742ac91393ba950fd6227": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "11c501032abf4393ad8b13faa76d71d0": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_d2f8c54b6c2246c392b2602cd0dfa22c",
-       "max": 8.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_4f1e5001a8cb408ab01b289a17b368eb",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 8.0
-      }
-     },
-     "13f870e4dd494f39b29371028cf1e83a": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_0a90533d66fe41bca1a20b34e94879ab",
-       "placeholder": "​",
-       "style": "IPY_MODEL_91fe9ab3caae45a38bf58efd2a94f0ec",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "COLLECTING RESULTS | : 100%"
-      }
-     },
-     "1490353944a34458b81b78e98dc3c7cf": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/base",
-       "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
@@ -3087,7 +3157,7 @@
        "width": null
       }
      },
-     "152edf9bf1b1450e88064902b0c16350": {
+     "1393e1010a34470692dbf787b36150a8": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3140,112 +3210,74 @@
        "width": null
       }
      },
-     "170e4bbe3abe4052afc2dab79127bc0b": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "173ea4543899491a961a8f6d8c19f841": {
+     "15585819ecc94832b9bd24cf9d125dc6": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_37f19fa6224f49c193e267f2135d22c2",
-        "IPY_MODEL_2ac88fd134c24b239d30c963b19c981e",
-        "IPY_MODEL_6908b7792c814296a5b773ef18f6916f"
-       ],
-       "layout": "IPY_MODEL_1edacff1b66b415a976e8417baba2ea9",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_a7fea6410c984d55b62563b4122f1b3b",
+       "placeholder": "​",
+       "style": "IPY_MODEL_6d22c67196fb4927a56228a4315b1a7d",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": " 4/4 [00:00&lt;00:00, 666.37it/s]"
       }
      },
-     "18e148d672b74e8e972bf6b64c91a98d": {
+     "1664f1347a1a4fa6a5af11d24cb1a77e": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "FloatProgressModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_40e12e0658ec42b3a46ec86924fcf0cb",
-        "IPY_MODEL_c26ad71d0f4e4c9dab40de0ce2e9aa92",
-        "IPY_MODEL_fa48572a000d4b48aa18c1ea6ba766d4"
-       ],
-       "layout": "IPY_MODEL_4d775b1c517640efbc637a7fc29a931c",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_3e94c8c11c3843d2936ed6521ce02778",
+       "max": 14.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_38306038699c4ae2a03eb188eaba8e9b",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": 14.0
       }
      },
-     "198375fea33a488180d4dbd48db52fe0": {
+     "177eeab90e2c44ddaf704ed406711184": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLStyleModel",
       "state": {
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "19a1cb60cdfd46a4bacb1560e4f4ad83": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_c5570bb295cb4f86adf550e83fb3cd52",
-       "placeholder": "​",
-       "style": "IPY_MODEL_50d009629d1a4cf39100f55517a8aa50",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "COLLECTING RESULTS | : 100%"
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "1b401e8bd9fb4ece9b604ea7866693e2": {
+     "1804ec2ca7fa4c5195d439dada4eba1c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HBoxModel",
@@ -3260,39 +3292,16 @@
        "_view_name": "HBoxView",
        "box_style": "",
        "children": [
-        "IPY_MODEL_e647c1d281c44c60931c03522f370369",
-        "IPY_MODEL_21cf0d2cee1944d2a079834db558ed59",
-        "IPY_MODEL_abbfb67a0bb647adbe78ed2cc1c18b31"
+        "IPY_MODEL_4c82abd77bf44cf7878ca8be91d743e9",
+        "IPY_MODEL_b7c5f5be45a94968af1bb9dcf1812c3d",
+        "IPY_MODEL_7d00468fa88e4918b920c018e9d79047"
        ],
-       "layout": "IPY_MODEL_427068a270cb4f36a61e11a843659fc7",
+       "layout": "IPY_MODEL_a9ccd45b2cfc4c58a151b02fa3125447",
        "tabbable": null,
        "tooltip": null
       }
      },
-     "1dfc9d88ef3f449baaa4efab6dae134f": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_ee0bf5343a0c48f99e77b01a43193990",
-       "placeholder": "​",
-       "style": "IPY_MODEL_e93dd159472d4a0d972b5e06c42eeffc",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 2/2 [00:00&lt;00:00, 266.09it/s]"
-      }
-     },
-     "1edacff1b66b415a976e8417baba2ea9": {
+     "1dd73d6311e345efa855d5396af5d1a1": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3345,30 +3354,7 @@
        "width": null
       }
      },
-     "210a3ad1e31d4a32af5b8c1c668a144d": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_4330a66f4f3f43c29b5f1d59d7437efb",
-       "placeholder": "​",
-       "style": "IPY_MODEL_3bbda24f02f14461b22c80b74e2dacdf",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "QUEUEING TASKS | : 100%"
-      }
-     },
-     "21cf0d2cee1944d2a079834db558ed59": {
+     "1df55c409a6e407c929aa6bdfc0b02dc": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "FloatProgressModel",
@@ -3384,17 +3370,17 @@
        "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_1490353944a34458b81b78e98dc3c7cf",
+       "layout": "IPY_MODEL_11df310392f742ac91393ba950fd6227",
        "max": 14.0,
        "min": 0.0,
        "orientation": "horizontal",
-       "style": "IPY_MODEL_5e4de4f922d742ae9d5308d8ea16cc45",
+       "style": "IPY_MODEL_87dd63ab441f4e0580b5c6ffd1d4ad57",
        "tabbable": null,
        "tooltip": null,
        "value": 14.0
       }
      },
-     "21eb6c06f39b4e9090b0e8c3e00e791a": {
+     "201e28628be34c2e8e062e018b9b9fd7": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -3409,15 +3395,69 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_94066b985c26452a919122d7cf1612d3",
+       "layout": "IPY_MODEL_7f2713e075bb485a8c4bccd234fb40d3",
        "placeholder": "​",
-       "style": "IPY_MODEL_ec3dc65a4cbd4a2f9ac95ca387cd550f",
+       "style": "IPY_MODEL_4c69ab2b84934ba0bcc50b7891845606",
        "tabbable": null,
        "tooltip": null,
-       "value": " 13/13 [00:00&lt;00:00, 405.52it/s]"
+       "value": " 13/13 [00:00&lt;00:00, 1580.92it/s]"
+      }
+     },
+     "20feb4ec43944e7db3f32a539f628d5a": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "249629b3d64645b8b2fc16cf38d2c8b0": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "2632e115d8bc49438acfdce4300a22a2": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "238e7ee07b154f46823a0d7452ee8228": {
+     "265a2a74cc9e47b8ad6e77f51af85e8c": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3470,91 +3510,16 @@
        "width": null
       }
      },
-     "24ba7c7864b2450b9a87e8b514403fe5": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_a7d0ba49c9c14a55a910421e1be8b429",
-       "placeholder": "​",
-       "style": "IPY_MODEL_a8f364d346a345a6815bc15eb33e39a9",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "QUEUEING TASKS | : 100%"
-      }
-     },
-     "2a2358c985a7455db00aaabc13d00e4e": {
-      "model_module": "@jupyter-widgets/controls",
+     "278563371dee4439a4aa5a3372d99dcf": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_44feb61600d64b70b67636dc304aad8e",
-       "max": 14.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_ec0cba70bf7b451dab82ae6b681cc8da",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 14.0
-      }
-     },
-     "2ac88fd134c24b239d30c963b19c981e": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_d526779ccbcc4e2ab5de82e039075745",
-       "max": 4.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_c1e37b447503420a92baf503436f3667",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 4.0
-      }
-     },
-     "33fc74e007d84d9ebdc65472e1655c33": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/base",
-       "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "LayoutView",
        "align_content": null,
@@ -3598,25 +3563,7 @@
        "width": null
       }
      },
-     "3543db56e6404f6cb905f8088c4bbceb": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "37f19fa6224f49c193e267f2135d22c2": {
+     "292f29f68ac34c2092adde9245abdf43": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -3631,31 +3578,38 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_97652109a0d84135a1c8e30d43586789",
+       "layout": "IPY_MODEL_5d2e4eb68ba140f7a27240013c6dba54",
        "placeholder": "​",
-       "style": "IPY_MODEL_3543db56e6404f6cb905f8088c4bbceb",
+       "style": "IPY_MODEL_4f9b25ded9a6461b887fe6bae9329763",
        "tabbable": null,
        "tooltip": null,
-       "value": "COLLECTING RESULTS | : 100%"
+       "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "38f80a36ece540ecb890d104de90632d": {
+     "2a29f22150974df288fb68791ee79353": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_f095a4328ef6452ab12496a1cd38a7d3",
+       "placeholder": "​",
+       "style": "IPY_MODEL_8779fbb960aa42fcb96a72baf42dd2f5",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 8/8 [00:00&lt;00:00, 981.35it/s]"
       }
      },
-     "3a637204f44b44eda06c15012981e659": {
+     "2a93272882a14277ad69a5bf26a3d115": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3708,25 +3662,7 @@
        "width": null
       }
      },
-     "3a920acb2d3343e5aa79d87e4209eb53": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "3b5c749479034a83ae323499fe1a63c3": {
+     "2a9d0bce14704123a51c85cf2a60b730": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3779,41 +3715,30 @@
        "width": null
       }
      },
-     "3bbda24f02f14461b22c80b74e2dacdf": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "3cce9fa278204e4e9df5a2305116f315": {
+     "2ad2cbf23c6c4e798099d23fac8c8b47": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_ccc1918d9baf4c399e2870f003ada556",
+       "placeholder": "​",
+       "style": "IPY_MODEL_72b642bed6a440558551aae04f9960b9",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 2/2 [00:00&lt;00:00, 333.84it/s]"
       }
      },
-     "3fdc447e71564e49b242a759d9ae4ac4": {
+     "2b1e3498eeed41edb5f7d3b1d6cc3f72": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3866,66 +3791,60 @@
        "width": null
       }
      },
-     "40e12e0658ec42b3a46ec86924fcf0cb": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_852af97a59334746b70eaf3c2798aae1",
-       "placeholder": "​",
-       "style": "IPY_MODEL_170e4bbe3abe4052afc2dab79127bc0b",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "QUEUEING TASKS | : 100%"
-      }
-     },
-     "4114f48a9fb54404976f913c003b94fc": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "415cdf7cbda544448791cf3278a7e830": {
-      "model_module": "@jupyter-widgets/controls",
+     "2b5e689b89b24e1c93407264167ac7c4": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "427068a270cb4f36a61e11a843659fc7": {
+     "2b6865e4e2cb42c49b7c1d69db0d8f36": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -3978,30 +3897,51 @@
        "width": null
       }
      },
-     "431d6fa1028b4a80af9586a356e50d54": {
+     "2c1764f3fb044a7387f558c5340f17d6": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "FloatProgressModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_72bff48392fd46dba82f60260c2d1253",
-       "placeholder": "​",
-       "style": "IPY_MODEL_ee597dc7346241e4ae03cacf6e23f267",
+       "layout": "IPY_MODEL_bdb5057b3f744812a10c323d388a4074",
+       "max": 14.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_356e160731634486ad7911a6be0cac4d",
        "tabbable": null,
        "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
+       "value": 14.0
+      }
+     },
+     "2c536966088d40d097cb239b382b832c": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "4330a66f4f3f43c29b5f1d59d7437efb": {
+     "2db16fc705e24a2dae3482b9c7cbba70": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4054,7 +3994,7 @@
        "width": null
       }
      },
-     "44feb61600d64b70b67636dc304aad8e": {
+     "2e2b8fbe44064482a88364a3b597318c": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4107,7 +4047,7 @@
        "width": null
       }
      },
-     "46f533814b9d4e5e9f4471141ace10af": {
+     "2ef72853c00c4a0aa081b1712b0e4b6c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -4122,68 +4062,33 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_c9b3d82af17b4559a984c7a4733dd5b4",
+       "layout": "IPY_MODEL_1393e1010a34470692dbf787b36150a8",
        "placeholder": "​",
-       "style": "IPY_MODEL_58aad0a49a1c49429441d1ac85e14f3b",
+       "style": "IPY_MODEL_3671508f6b344387a2c0484346cacfff",
        "tabbable": null,
        "tooltip": null,
-       "value": " 8/8 [00:03&lt;00:00,  2.42it/s]"
+       "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "488c2910003146fc9842f19d968c2661": {
-      "model_module": "@jupyter-widgets/base",
+     "307c375c0fe0460cbafac5b3a2cfae6d": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "4d775b1c517640efbc637a7fc29a931c": {
+     "3210c7a10215407796c072741fd698d0": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4236,23 +4141,30 @@
        "width": null
       }
      },
-     "4f1e5001a8cb408ab01b289a17b368eb": {
+     "32299b95ffcf4eedb2cf2d14380b0691": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_5873b249e1194f84ad25dbae9981cc9a",
+       "placeholder": "​",
+       "style": "IPY_MODEL_97d02ab751ef479c96347c1f0291b5e4",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 14/14 [00:00&lt;00:00, 2041.24it/s]"
       }
      },
-     "509ea400969f4b39aa873a024e57a386": {
+     "32fda6dbeb094ab199ef026b57b445ef": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4305,7 +4217,7 @@
        "width": null
       }
      },
-     "50d009629d1a4cf39100f55517a8aa50": {
+     "34eed8f15833425c9726eb6fd966c3a8": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -4323,7 +4235,7 @@
        "text_color": null
       }
      },
-     "553e43a31121414c807d0bf286f5737a": {
+     "356c81c7253e40b488b1a7a7be7a1a09": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4376,7 +4288,73 @@
        "width": null
       }
      },
-     "58aad0a49a1c49429441d1ac85e14f3b": {
+     "356e160731634486ad7911a6be0cac4d": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "3671508f6b344387a2c0484346cacfff": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "36f0417f4608440a8f162664147663ea": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "38306038699c4ae2a03eb188eaba8e9b": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "39fd9ab6e627483f921be1b80172632a": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -4394,7 +4372,7 @@
        "text_color": null
       }
      },
-     "59355a840a684eebb9f442a1687792a6": {
+     "3c8d43c6215f4c38bf6c276717b3a0d2": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -4409,15 +4387,33 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_6cbc99a27dc2433e8896b87d26634703",
+       "layout": "IPY_MODEL_fbc06ed872314ab7aea6daf42fa18343",
        "placeholder": "​",
-       "style": "IPY_MODEL_df8cc118fd8c4ef585a1356089ed6f1e",
+       "style": "IPY_MODEL_6b117a3c67434834b3a1d8202a7287c0",
        "tabbable": null,
        "tooltip": null,
        "value": "COLLECTING RESULTS | : 100%"
       }
      },
-     "5a873dfda6514059a3b6c9d5447ab39e": {
+     "3cdda99fbac542a8947717cce31d0195": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "3e94c8c11c3843d2936ed6521ce02778": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4470,103 +4466,80 @@
        "width": null
       }
      },
-     "5c850d5fb4e44e718214f3069b6b0ff1": {
+     "3ecb098dfac34ee0bcfabe422b3aba88": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HBoxModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_a69efe9f4688418ab2cf001a047f833f",
-       "placeholder": "​",
-       "style": "IPY_MODEL_7bc28816773548f089ace4ffda39844c",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_292f29f68ac34c2092adde9245abdf43",
+        "IPY_MODEL_1664f1347a1a4fa6a5af11d24cb1a77e",
+        "IPY_MODEL_930117f9ee8f4311a72a77712d45db17"
+       ],
+       "layout": "IPY_MODEL_707efb1e83ba43fbb495b953ecc90cac",
        "tabbable": null,
-       "tooltip": null,
-       "value": " 8/8 [00:00&lt;00:00, 1454.21it/s]"
+       "tooltip": null
       }
      },
-     "5c9f2ee490dd4bd0a66e8ec68c53a0ce": {
+     "477ba2e67dfd4717924c5f7608d52e53": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "FloatProgressModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_e708771cec524aa3bdad31e9fdc78da4",
-       "placeholder": "​",
-       "style": "IPY_MODEL_6da7b65581a543fcbf3915033fc137b8",
+       "layout": "IPY_MODEL_1dd73d6311e345efa855d5396af5d1a1",
+       "max": 13.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_6bcc8fe14f8047938c78176938b5d586",
        "tabbable": null,
        "tooltip": null,
-       "value": "COLLECTING RESULTS | : 100%"
-      }
-     },
-     "5d6f5f53c3ce4497ba7bbc4baf7bde06": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "5e4de4f922d742ae9d5308d8ea16cc45": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "value": 13.0
       }
      },
-     "5e517652a0b248018c5028b8b724d456": {
+     "4a2089d910544ba6839a306f9c449f04": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_b76baeb4a7964637b55dd51ffc49677b",
+       "placeholder": "​",
+       "style": "IPY_MODEL_7e1de09784d14d9e9213b9c00c29aa51",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 14/14 [00:16&lt;00:00,  1.49s/it]"
       }
      },
-     "6089d1da4e064de68179493ab6ddf356": {
+     "4c69ab2b84934ba0bcc50b7891845606": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -4584,57 +4557,30 @@
        "text_color": null
       }
      },
-     "662a8975e3414745957e8d8f54d0dc57": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_8988a53c99f744179e3fa0c3be2f1c33",
-        "IPY_MODEL_f95487f3733e41c48bc5844d720ba78c",
-        "IPY_MODEL_6b2fc2e10e0c42908096c70b0fc23d41"
-       ],
-       "layout": "IPY_MODEL_dad8e424f1884d26a055fcd28c5123aa",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "66c9ecfca6274545bf746e08b54e4be2": {
+     "4c82abd77bf44cf7878ca8be91d743e9": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
+       "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_3fdc447e71564e49b242a759d9ae4ac4",
-       "max": 8.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_f8fbd2f91bb84f27aab228f586f8c6c1",
+       "layout": "IPY_MODEL_e5ddb5cbcd1b4203aa27d9aed508a4bf",
+       "placeholder": "​",
+       "style": "IPY_MODEL_39fd9ab6e627483f921be1b80172632a",
        "tabbable": null,
        "tooltip": null,
-       "value": 8.0
+       "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "672e6cd1dd3b40c2beeeaed79f1efeb4": {
+     "4ef3986f0c4a4eb09ff76b533ec7afe2": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4687,53 +4633,78 @@
        "width": null
       }
      },
-     "67a18bc0e1d34eb595357d13cdbee2a3": {
-      "model_module": "@jupyter-widgets/controls",
+     "4f78bbd42a87441bbd0a82129cd307f7": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_a9ec0e018fc44dc08337a2a5b06a118d",
-       "placeholder": "​",
-       "style": "IPY_MODEL_3a920acb2d3343e5aa79d87e4209eb53",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "QUEUEING TASKS | : 100%"
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "680bdb4a11604566a309bce5bf7fc1f6": {
+     "4f9b25ded9a6461b887fe6bae9329763": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_c3724c3bca434950a8ef4fe13ba95a0f",
-       "placeholder": "​",
-       "style": "IPY_MODEL_0f23257b3cf64b4a8c4754a2d3d2a0ba",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 13/13 [00:38&lt;00:00,  1.58s/it]"
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "6908b7792c814296a5b773ef18f6916f": {
+     "5349c35dae514abea71f51d8f09cac45": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -4748,38 +4719,39 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_e94d6af4d70b4e1bac63dee7dae0821c",
+       "layout": "IPY_MODEL_2e2b8fbe44064482a88364a3b597318c",
        "placeholder": "​",
-       "style": "IPY_MODEL_8c71837689724f75be9405aa68b68774",
+       "style": "IPY_MODEL_a74aea13d7c441bb97f1ebdb52bf2842",
        "tabbable": null,
        "tooltip": null,
-       "value": " 4/4 [00:00&lt;00:00, 770.30it/s]"
+       "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "6b2fc2e10e0c42908096c70b0fc23d41": {
+     "53df9e177168414490ccff53eb90e7de": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HBoxModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_7e1d393b18f64e80970208cd96031a3b",
-       "placeholder": "​",
-       "style": "IPY_MODEL_77104402e24643858b246a0a8b82ce29",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_60d2aff8210546f9937c2b829fb96ea6",
+        "IPY_MODEL_b205287f40524a239d5ccd9601d07c99",
+        "IPY_MODEL_15585819ecc94832b9bd24cf9d125dc6"
+       ],
+       "layout": "IPY_MODEL_0fee663d8b574bc3b8306611dda3a587",
        "tabbable": null,
-       "tooltip": null,
-       "value": " 14/14 [00:00&lt;00:00, 964.68it/s]"
+       "tooltip": null
       }
      },
-     "6ca9851356704321bfb348f7e35ed982": {
+     "574d4ec55e9e4cafbd82dcdc9c5a02dd": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4832,7 +4804,30 @@
        "width": null
       }
      },
-     "6cbc99a27dc2433e8896b87d26634703": {
+     "576b5c8e1f684d89871e519adfd4dca3": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_a4f2caaeeb8f426483de79879ba35a89",
+       "placeholder": "​",
+       "style": "IPY_MODEL_6ffd9366e636440581b0a9c813e42518",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "PROCESSING TASKS | : 100%"
+      }
+     },
+     "5873b249e1194f84ad25dbae9981cc9a": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4885,7 +4880,7 @@
        "width": null
       }
      },
-     "6da7b65581a543fcbf3915033fc137b8": {
+     "5a1922ee6fd140fdbe9fe62ff9c8fab2": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -4903,7 +4898,54 @@
        "text_color": null
       }
      },
-     "72bff48392fd46dba82f60260c2d1253": {
+     "5c543e0ea83243e58bcb9469a0dacedb": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_ca08b158c8644a8ca170c1041fdcaec2",
+        "IPY_MODEL_8820ae08b7454edd97abeec5ed7b4a85",
+        "IPY_MODEL_0ceefa68a59a47cca003f4c4e3ef5006"
+       ],
+       "layout": "IPY_MODEL_ebbc50fd3a364b72bc4da24b64080777",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "5d2c2bc4f4b44e1bad38ea5e8d33a462": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_97bfccf0865f4f0a94059a37aac69c5d",
+       "placeholder": "​",
+       "style": "IPY_MODEL_3cdda99fbac542a8947717cce31d0195",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "PROCESSING TASKS | : 100%"
+      }
+     },
+     "5d2e4eb68ba140f7a27240013c6dba54": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -4956,41 +4998,48 @@
        "width": null
       }
      },
-     "73bf46924c2c46d0b07ec03d31bd47fe": {
+     "5e4e6b624ac6446faf4107c058767525": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLStyleModel",
       "state": {
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "77104402e24643858b246a0a8b82ce29": {
+     "60d2aff8210546f9937c2b829fb96ea6": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_a0a30286165e416f9f90ea8a51b73e99",
+       "placeholder": "​",
+       "style": "IPY_MODEL_b4d36c5a28664c95b328be6c577dca65",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "QUEUEING TASKS | : 100%"
       }
      },
-     "77f413c18d4e4d3a894392895d92f1ed": {
+     "68e958a6b6274ae4bed729bd49262241": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5043,55 +5092,64 @@
        "width": null
       }
      },
-     "785dba9c597540aca19a9ee6cfb1f390": {
+     "68f78f13ec1449519176b367bbbab96b": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_59355a840a684eebb9f442a1687792a6",
-        "IPY_MODEL_aecb260f17734a5cbe6a016425775ad0",
-        "IPY_MODEL_ede433c7d3ea4445b5afc7890ce1a318"
-       ],
-       "layout": "IPY_MODEL_509ea400969f4b39aa873a024e57a386",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_efb0842a6d164ffa9bb61f574f9bd688",
+       "placeholder": "​",
+       "style": "IPY_MODEL_177eeab90e2c44ddaf704ed406711184",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": "PROCESSING TASKS | : 100%"
       }
      },
-     "790079f3073b4943bb70452c35b62013": {
+     "6b117a3c67434834b3a1d8202a7287c0": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_67a18bc0e1d34eb595357d13cdbee2a3",
-        "IPY_MODEL_cbb26dd5dab9447b9183e7df55b94c49",
-        "IPY_MODEL_e59d9f4919e843b5b7c0bc2b96e969f8"
-       ],
-       "layout": "IPY_MODEL_c5085414716249ceb48057f655b11485",
-       "tabbable": null,
-       "tooltip": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "6bcc8fe14f8047938c78176938b5d586": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
       }
      },
-     "7a1741c1b6854866ad69d0c5f9906d36": {
+     "6d22c67196fb4927a56228a4315b1a7d": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -5109,7 +5167,23 @@
        "text_color": null
       }
      },
-     "7bc28816773548f089ace4ffda39844c": {
+     "6f93db0fc92c4cc3bc19c805ab6feba2": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "6ffd9366e636440581b0a9c813e42518": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -5127,7 +5201,7 @@
        "text_color": null
       }
      },
-     "7e1d393b18f64e80970208cd96031a3b": {
+     "707efb1e83ba43fbb495b953ecc90cac": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5180,7 +5254,7 @@
        "width": null
       }
      },
-     "7f02b48ee2404301b4b395fb08b8150b": {
+     "72b642bed6a440558551aae04f9960b9": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -5198,86 +5272,16 @@
        "text_color": null
       }
      },
-     "842c43492e6449bf8bc7b1be1fe779a1": {
-      "model_module": "@jupyter-widgets/controls",
+     "72e751b026fa42f88e137125bf1fe913": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_33fc74e007d84d9ebdc65472e1655c33",
-       "placeholder": "​",
-       "style": "IPY_MODEL_0a17167091ac418a8cdd463730c4ed9a",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
-      }
-     },
-     "84bbd4eac9d9407aaba7ca651dcb80dc": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_431d6fa1028b4a80af9586a356e50d54",
-        "IPY_MODEL_91ffba018f714296b84de4f894dfc11e",
-        "IPY_MODEL_84da1f19ca7c45b4a3e24440585d3c90"
-       ],
-       "layout": "IPY_MODEL_bb6cf6e8002244bea1242327b46cf595",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "84da1f19ca7c45b4a3e24440585d3c90": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_0d96d4f5f35f42f7a867122c00a65b60",
-       "placeholder": "​",
-       "style": "IPY_MODEL_98f7312360b24e97b32a5a30538312f3",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 2/2 [00:19&lt;00:00,  8.34s/it]"
-      }
-     },
-     "852af97a59334746b70eaf3c2798aae1": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/base",
-       "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "LayoutView",
        "align_content": null,
@@ -5321,30 +5325,31 @@
        "width": null
       }
      },
-     "8988a53c99f744179e3fa0c3be2f1c33": {
+     "72f5a56fadaa40b2a8904fe86e3f333d": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HBoxModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_e036c10ebcfe4bec9b7b3389ba834879",
-       "placeholder": "​",
-       "style": "IPY_MODEL_e9395468c16241589a2280cc8a3274d9",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_0b255b5981e54b13b80fab5c9920792a",
+        "IPY_MODEL_2c1764f3fb044a7387f558c5340f17d6",
+        "IPY_MODEL_32299b95ffcf4eedb2cf2d14380b0691"
+       ],
+       "layout": "IPY_MODEL_3210c7a10215407796c072741fd698d0",
        "tabbable": null,
-       "tooltip": null,
-       "value": "QUEUEING TASKS | : 100%"
+       "tooltip": null
       }
      },
-     "8a67375d76b44412b1920f9d5b44d790": {
+     "7660ac5fc8804a1d950e4cdb61a78fd4": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5397,49 +5402,82 @@
        "width": null
       }
      },
-     "8c71837689724f75be9405aa68b68774": {
+     "7b8f7c16dfb34595af13f52974c70506": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "FloatProgressModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_99d34c25ed884227a0a8250e4d96d62b",
+       "max": 4.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_6f93db0fc92c4cc3bc19c805ab6feba2",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 4.0
       }
      },
-     "907981d2e2064d04819ee2c8868e7dea": {
+     "7c5b994a5dc34ce2a42ee354bdd0bc2d": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "FloatProgressModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_98249c3b86ab48b089a789d5ba5490c4",
-        "IPY_MODEL_dfe73c4906ec4e378217e95f946ae822",
-        "IPY_MODEL_680bdb4a11604566a309bce5bf7fc1f6"
-       ],
-       "layout": "IPY_MODEL_0a2ba616f12a478eb61cec54f12dc8d4",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_4f78bbd42a87441bbd0a82129cd307f7",
+       "max": 8.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_fc4b59a25baf4921b46c620ed2ad4db1",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": 8.0
+      }
+     },
+     "7d00468fa88e4918b920c018e9d79047": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_278563371dee4439a4aa5a3372d99dcf",
+       "placeholder": "​",
+       "style": "IPY_MODEL_34eed8f15833425c9726eb6fd966c3a8",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 2/2 [00:00&lt;00:00, 306.09it/s]"
       }
      },
-     "91fe9ab3caae45a38bf58efd2a94f0ec": {
+     "7e1de09784d14d9e9213b9c00c29aa51": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -5457,33 +5495,60 @@
        "text_color": null
       }
      },
-     "91ffba018f714296b84de4f894dfc11e": {
-      "model_module": "@jupyter-widgets/controls",
+     "7f2713e075bb485a8c4bccd234fb40d3": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_09c661dd053047f4a143d5cfa8f83900",
-       "max": 2.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_38f80a36ece540ecb890d104de90632d",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 2.0
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "94066b985c26452a919122d7cf1612d3": {
+     "82e69b7b377c45829e46969d7b952a62": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5536,7 +5601,57 @@
        "width": null
       }
      },
-     "963b84d2a94249fa93e9f6760664a3e9": {
+     "85b52e15d022474ab742ce25210de368": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "8779fbb960aa42fcb96a72baf42dd2f5": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "87dd63ab441f4e0580b5c6ffd1d4ad57": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "87f794efe7fb4c3a9d6118714a0d5bae": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -5551,15 +5666,15 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_d0a3d2356ac244aca0129125da157d94",
+       "layout": "IPY_MODEL_2db16fc705e24a2dae3482b9c7cbba70",
        "placeholder": "​",
-       "style": "IPY_MODEL_ac103dcfec9f4f3a8128d179587689e9",
+       "style": "IPY_MODEL_2c536966088d40d097cb239b382b832c",
        "tabbable": null,
        "tooltip": null,
-       "value": " 14/14 [00:00&lt;00:00, 1597.57it/s]"
+       "value": " 4/4 [00:17&lt;00:00,  4.31s/it]"
       }
      },
-     "965d7ce149674ae289f64d0801fa9070": {
+     "8820ae08b7454edd97abeec5ed7b4a85": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "FloatProgressModel",
@@ -5575,17 +5690,41 @@
        "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_152edf9bf1b1450e88064902b0c16350",
-       "max": 2.0,
+       "layout": "IPY_MODEL_82e69b7b377c45829e46969d7b952a62",
+       "max": 13.0,
        "min": 0.0,
        "orientation": "horizontal",
-       "style": "IPY_MODEL_b450ff0254ff488ea142bdb0d3328d3e",
+       "style": "IPY_MODEL_e42cd8df540b48999438b1b8582bf35d",
        "tabbable": null,
        "tooltip": null,
-       "value": 2.0
+       "value": 13.0
+      }
+     },
+     "8ac62732d56b427b8b117d0bbe51aa98": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_5d2c2bc4f4b44e1bad38ea5e8d33a462",
+        "IPY_MODEL_f3c5c6baeff344dfa91a59f364dfbce7",
+        "IPY_MODEL_a902ccaf632f44beb5924ec89e9f6610"
+       ],
+       "layout": "IPY_MODEL_4ef3986f0c4a4eb09ff76b533ec7afe2",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "97652109a0d84135a1c8e30d43586789": {
+     "8c3b9aac6689443ba212d0e8f67322ac": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5638,7 +5777,7 @@
        "width": null
       }
      },
-     "98249c3b86ab48b089a789d5ba5490c4": {
+     "930117f9ee8f4311a72a77712d45db17": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -5653,33 +5792,39 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_efe2a151adea421fb2715722acd6087d",
+       "layout": "IPY_MODEL_056aa89ed3ad4d2da1203c831368622d",
        "placeholder": "​",
-       "style": "IPY_MODEL_4114f48a9fb54404976f913c003b94fc",
+       "style": "IPY_MODEL_5e4e6b624ac6446faf4107c058767525",
        "tabbable": null,
        "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
+       "value": " 14/14 [00:00&lt;00:00, 1365.11it/s]"
       }
      },
-     "98f7312360b24e97b32a5a30538312f3": {
+     "93b5a434ba33408fb7284a1a5a268b60": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "HBoxModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_2ef72853c00c4a0aa081b1712b0e4b6c",
+        "IPY_MODEL_c8fa2ce9e2f94310afdc221f9c6c9e42",
+        "IPY_MODEL_2a29f22150974df288fb68791ee79353"
+       ],
+       "layout": "IPY_MODEL_06c326d8371843c2bad4a7ff77b8d8e9",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "a69efe9f4688418ab2cf001a047f833f": {
+     "95859d460d094816af6c3f26b7df8f2d": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5732,7 +5877,7 @@
        "width": null
       }
      },
-     "a7d0ba49c9c14a55a910421e1be8b429": {
+     "97bfccf0865f4f0a94059a37aac69c5d": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5785,7 +5930,7 @@
        "width": null
       }
      },
-     "a8f364d346a345a6815bc15eb33e39a9": {
+     "97d02ab751ef479c96347c1f0291b5e4": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -5803,7 +5948,7 @@
        "text_color": null
       }
      },
-     "a9ec0e018fc44dc08337a2a5b06a118d": {
+     "99d34c25ed884227a0a8250e4d96d62b": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5856,31 +6001,7 @@
        "width": null
       }
      },
-     "aa6a8719dbc04f17863173f186a454f8": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_19a1cb60cdfd46a4bacb1560e4f4ad83",
-        "IPY_MODEL_2a2358c985a7455db00aaabc13d00e4e",
-        "IPY_MODEL_963b84d2a94249fa93e9f6760664a3e9"
-       ],
-       "layout": "IPY_MODEL_c15220434fa64f1cb05506cd409f0ce2",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "abbfb67a0bb647adbe78ed2cc1c18b31": {
+     "9a77d05e4af64a9089be21ec0147ca7a": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -5895,33 +6016,15 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_c81228ce32eb4023a4ecb270fab53abf",
+       "layout": "IPY_MODEL_2b5e689b89b24e1c93407264167ac7c4",
        "placeholder": "​",
-       "style": "IPY_MODEL_415cdf7cbda544448791cf3278a7e830",
+       "style": "IPY_MODEL_307c375c0fe0460cbafac5b3a2cfae6d",
        "tabbable": null,
        "tooltip": null,
-       "value": " 14/14 [00:10&lt;00:00,  2.26it/s]"
-      }
-     },
-     "ac103dcfec9f4f3a8128d179587689e9": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "value": "PROCESSING TASKS | : 100%"
       }
      },
-     "aecb260f17734a5cbe6a016425775ad0": {
+     "9b9e6d8e5c6b43aa98a6ff07ca445ba5": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "FloatProgressModel",
@@ -5937,115 +6040,17 @@
        "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_01770cc92319437da696deec5b7174fd",
-       "max": 13.0,
+       "layout": "IPY_MODEL_ff29b139d598449c8402639f09358b82",
+       "max": 8.0,
        "min": 0.0,
        "orientation": "horizontal",
-       "style": "IPY_MODEL_198375fea33a488180d4dbd48db52fe0",
+       "style": "IPY_MODEL_85b52e15d022474ab742ce25210de368",
        "tabbable": null,
        "tooltip": null,
-       "value": 13.0
-      }
-     },
-     "b04778b8536d4f65a4efcd61806c82a6": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "b1ad7a617ff84c2091192f13e2d5b064": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_842c43492e6449bf8bc7b1be1fe779a1",
-        "IPY_MODEL_d76aedce62ac45319a05652755769fcb",
-        "IPY_MODEL_c1cf93d13e39445193ebfe5057960629"
-       ],
-       "layout": "IPY_MODEL_238e7ee07b154f46823a0d7452ee8228",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "b450ff0254ff488ea142bdb0d3328d3e": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "b46b84e797ba4451a1105861f08c554b": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_24ba7c7864b2450b9a87e8b514403fe5",
-        "IPY_MODEL_bd8cef64d3ec4e0895e06e7e727c0677",
-        "IPY_MODEL_21eb6c06f39b4e9090b0e8c3e00e791a"
-       ],
-       "layout": "IPY_MODEL_cd9658c8d8a34ba082410ebdb301b151",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "b5e1a99ce98b4b97987af4936a2d5072": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "value": 8.0
       }
      },
-     "ba89b6be360c4cd6aef6cfea07e5f446": {
+     "9cfa3e4e2e5a4a1884aa4570bbaf1fd3": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "ProgressStyleModel",
@@ -6061,7 +6066,7 @@
        "description_width": ""
       }
      },
-     "bb6cf6e8002244bea1242327b46cf595": {
+     "a0a30286165e416f9f90ea8a51b73e99": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6114,33 +6119,7 @@
        "width": null
       }
      },
-     "bd8cef64d3ec4e0895e06e7e727c0677": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_c60c8701fe2f46979ef1a7341fff2ee0",
-       "max": 13.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_fc595229161344dcb6af6ad2a9856932",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 13.0
-      }
-     },
-     "c15220434fa64f1cb05506cd409f0ce2": {
+     "a4f2caaeeb8f426483de79879ba35a89": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6193,72 +6172,25 @@
        "width": null
       }
      },
-     "c1cf93d13e39445193ebfe5057960629": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_553e43a31121414c807d0bf286f5737a",
-       "placeholder": "​",
-       "style": "IPY_MODEL_7a1741c1b6854866ad69d0c5f9906d36",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 4/4 [00:15&lt;00:00,  2.49s/it]"
-      }
-     },
-     "c1e37b447503420a92baf503436f3667": {
+     "a74aea13d7c441bb97f1ebdb52bf2842": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HTMLStyleModel",
       "state": {
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "c26ad71d0f4e4c9dab40de0ce2e9aa92": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_672e6cd1dd3b40c2beeeaed79f1efeb4",
-       "max": 4.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_ba89b6be360c4cd6aef6cfea07e5f446",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 4.0
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "c3724c3bca434950a8ef4fe13ba95a0f": {
+     "a7fea6410c984d55b62563b4122f1b3b": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6311,7 +6243,30 @@
        "width": null
       }
      },
-     "c5085414716249ceb48057f655b11485": {
+     "a902ccaf632f44beb5924ec89e9f6610": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_032f9568a78046a8aeb185d5a9aea001",
+       "placeholder": "​",
+       "style": "IPY_MODEL_dec6c0dc17cd4c51b2d72208aee3499b",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 13/13 [00:41&lt;00:00,  1.52s/it]"
+      }
+     },
+     "a9ccd45b2cfc4c58a151b02fa3125447": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6364,7 +6319,7 @@
        "width": null
       }
      },
-     "c5570bb295cb4f86adf550e83fb3cd52": {
+     "aa631d07f1014b72a72762498db5d8c3": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6417,7 +6372,23 @@
        "width": null
       }
      },
-     "c60c8701fe2f46979ef1a7341fff2ee0": {
+     "ab9559e082aa484db84c11b197baf334": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "ae4fb999d7894239863176332db55fab": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6470,113 +6441,77 @@
        "width": null
       }
      },
-     "c7890f1b518c42768db31a90dda9e6c2": {
-      "model_module": "@jupyter-widgets/base",
+     "b00250d8126b44d9b588ea74a128cc40": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "FloatProgressModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_cd820a3122484834ba93b9709d428613",
+       "max": 2.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_ab9559e082aa484db84c11b197baf334",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 2.0
       }
      },
-     "c81228ce32eb4023a4ecb270fab53abf": {
-      "model_module": "@jupyter-widgets/base",
+     "b0f7297d875b49f5b97ede53fd8c2d77": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "b205287f40524a239d5ccd9601d07c99": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "FloatProgressModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_aa631d07f1014b72a72762498db5d8c3",
+       "max": 4.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_0ee1b729b5a44ca0bb367c15fc2aae25",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 4.0
       }
      },
-     "c9b3d82af17b4559a984c7a4733dd5b4": {
+     "b4b2c859c45e45548515f0fb55ecad58": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6629,7 +6564,67 @@
        "width": null
       }
      },
-     "c9ef6c38d1654b88958dada134e0eb44": {
+     "b4d36c5a28664c95b328be6c577dca65": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "b534fe47907e4567987c4de20149a110": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "b5449ac16c6e4fb7b1945fda779f515b": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_c21a71bb3721415ebf1a094d81a73426",
+        "IPY_MODEL_b00250d8126b44d9b588ea74a128cc40",
+        "IPY_MODEL_d8b43dcfce0c4702be3a4668b21b113c"
+       ],
+       "layout": "IPY_MODEL_2a9d0bce14704123a51c85cf2a60b730",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "b76baeb4a7964637b55dd51ffc49677b": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6682,7 +6677,7 @@
        "width": null
       }
      },
-     "cbb26dd5dab9447b9183e7df55b94c49": {
+     "b7c5f5be45a94968af1bb9dcf1812c3d": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "FloatProgressModel",
@@ -6698,70 +6693,35 @@
        "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_5a873dfda6514059a3b6c9d5447ab39e",
-       "max": 8.0,
+       "layout": "IPY_MODEL_2b6865e4e2cb42c49b7c1d69db0d8f36",
+       "max": 2.0,
        "min": 0.0,
        "orientation": "horizontal",
-       "style": "IPY_MODEL_e656028f0da6402aad23a38e176dfeb7",
+       "style": "IPY_MODEL_36f0417f4608440a8f162664147663ea",
        "tabbable": null,
        "tooltip": null,
-       "value": 8.0
+       "value": 2.0
       }
      },
-     "cd9658c8d8a34ba082410ebdb301b151": {
-      "model_module": "@jupyter-widgets/base",
+     "bc793225325243cb94628279e125795a": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "d0a3d2356ac244aca0129125da157d94": {
+     "bdb5057b3f744812a10c323d388a4074": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6814,113 +6774,90 @@
        "width": null
       }
      },
-     "d2a9027221a64178b5081e8597e0b9e2": {
-      "model_module": "@jupyter-widgets/base",
+     "bf7bc477add842449c0768c6971beb19": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "HTMLStyleModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "d2f8c54b6c2246c392b2602cd0dfa22c": {
-      "model_module": "@jupyter-widgets/base",
+     "c21a71bb3721415ebf1a094d81a73426": {
+      "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "LayoutModel",
+      "model_name": "HTMLModel",
       "state": {
-       "_model_module": "@jupyter-widgets/base",
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "LayoutModel",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_0b66b9d4af1e41c6a527cf97746844b4",
+       "placeholder": "​",
+       "style": "IPY_MODEL_249629b3d64645b8b2fc16cf38d2c8b0",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "PROCESSING TASKS | : 100%"
+      }
+     },
+     "c21cbd2f6343466eb15bc229b4fd245f": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_e6732a50301448349d86f0a991df0f37",
+        "IPY_MODEL_021908baf2db408698e5345a8a7dc741",
+        "IPY_MODEL_2ad2cbf23c6c4e798099d23fac8c8b47"
+       ],
+       "layout": "IPY_MODEL_cf74a9fb4f804d2da36e7976fe1948a8",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "c529dea64e364c278f32f1c127c46b61": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "LayoutView",
-       "align_content": null,
-       "align_items": null,
-       "align_self": null,
-       "border_bottom": null,
-       "border_left": null,
-       "border_right": null,
-       "border_top": null,
-       "bottom": null,
-       "display": null,
-       "flex": null,
-       "flex_flow": null,
-       "grid_area": null,
-       "grid_auto_columns": null,
-       "grid_auto_flow": null,
-       "grid_auto_rows": null,
-       "grid_column": null,
-       "grid_gap": null,
-       "grid_row": null,
-       "grid_template_areas": null,
-       "grid_template_columns": null,
-       "grid_template_rows": null,
-       "height": null,
-       "justify_content": null,
-       "justify_items": null,
-       "left": null,
-       "margin": null,
-       "max_height": null,
-       "max_width": null,
-       "min_height": null,
-       "min_width": null,
-       "object_fit": null,
-       "object_position": null,
-       "order": null,
-       "overflow": null,
-       "padding": null,
-       "right": null,
-       "top": null,
-       "visibility": null,
-       "width": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "d526779ccbcc4e2ab5de82e039075745": {
+     "c6e6ac368c5a4449873a98219c8661cb": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -6973,7 +6910,46 @@
        "width": null
       }
      },
-     "d76aedce62ac45319a05652755769fcb": {
+     "c72f9c8d00e94b4b8e7ea23fb7020485": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_e1d66222d5064e64b4c1ed3190e995f7",
+       "placeholder": "​",
+       "style": "IPY_MODEL_5a1922ee6fd140fdbe9fe62ff9c8fab2",
+       "tabbable": null,
+       "tooltip": null,
+       "value": " 4/4 [00:00&lt;00:00, 498.42it/s]"
+      }
+     },
+     "c756f388b892437786c3af7b73dadd5d": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "c8fa2ce9e2f94310afdc221f9c6c9e42": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "FloatProgressModel",
@@ -6989,41 +6965,40 @@
        "bar_style": "success",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_fe95884dc1cf4bafabd054ca6d93578e",
-       "max": 4.0,
+       "layout": "IPY_MODEL_cb7c8a43c14f490da386509d6907af65",
+       "max": 8.0,
        "min": 0.0,
        "orientation": "horizontal",
-       "style": "IPY_MODEL_b04778b8536d4f65a4efcd61806c82a6",
+       "style": "IPY_MODEL_decb33eabdcb4fc7ba7483570c236bd0",
        "tabbable": null,
        "tooltip": null,
-       "value": 4.0
+       "value": 8.0
       }
      },
-     "da747d77e487435eb2b472021bc4da5b": {
+     "ca08b158c8644a8ca170c1041fdcaec2": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_210a3ad1e31d4a32af5b8c1c668a144d",
-        "IPY_MODEL_dd1b9a719dfe4979bf58db582fddf1f0",
-        "IPY_MODEL_f388d7eec7074dd9bf1d708c3bc2eb8b"
-       ],
-       "layout": "IPY_MODEL_c7890f1b518c42768db31a90dda9e6c2",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_72e751b026fa42f88e137125bf1fe913",
+       "placeholder": "​",
+       "style": "IPY_MODEL_b534fe47907e4567987c4de20149a110",
        "tabbable": null,
-       "tooltip": null
+       "tooltip": null,
+       "value": "COLLECTING RESULTS | : 100%"
       }
      },
-     "dad8e424f1884d26a055fcd28c5123aa": {
+     "cb7c8a43c14f490da386509d6907af65": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7076,51 +7051,7 @@
        "width": null
       }
      },
-     "dd1b9a719dfe4979bf58db582fddf1f0": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_ea3dc3af3d4d46e497494f48af4a2375",
-       "max": 2.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_5d6f5f53c3ce4497ba7bbc4baf7bde06",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 2.0
-      }
-     },
-     "de422c87c3ae4c2eb70874d63a1bb006": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "dea047af89b54f028876e10ec888264a": {
+     "ccc1918d9baf4c399e2870f003ada556": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7173,25 +7104,7 @@
        "width": null
       }
      },
-     "df8cc118fd8c4ef585a1356089ed6f1e": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "df9355f8c89841d7ad568f36ae03c24c": {
+     "cd820a3122484834ba93b9709d428613": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7244,33 +7157,7 @@
        "width": null
       }
      },
-     "dfe73c4906ec4e378217e95f946ae822": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_fa0e9d2659ca4a3d975485769392b441",
-       "max": 13.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_3cce9fa278204e4e9df5a2305116f315",
-       "tabbable": null,
-       "tooltip": null,
-       "value": 13.0
-      }
-     },
-     "e036c10ebcfe4bec9b7b3389ba834879": {
+     "cf74a9fb4f804d2da36e7976fe1948a8": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7323,7 +7210,25 @@
        "width": null
       }
      },
-     "e3206794d112407883b49ceba87baad4": {
+     "d17abe4537c7407c98b0e7ef7f42b965": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "d365480879ee46e68db80d46cb40444e": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HBoxModel",
@@ -7338,39 +7243,64 @@
        "_view_name": "HBoxView",
        "box_style": "",
        "children": [
-        "IPY_MODEL_13f870e4dd494f39b29371028cf1e83a",
-        "IPY_MODEL_965d7ce149674ae289f64d0801fa9070",
-        "IPY_MODEL_1dfc9d88ef3f449baaa4efab6dae134f"
+        "IPY_MODEL_9a77d05e4af64a9089be21ec0147ca7a",
+        "IPY_MODEL_1df55c409a6e407c929aa6bdfc0b02dc",
+        "IPY_MODEL_4a2089d910544ba6839a306f9c449f04"
        ],
-       "layout": "IPY_MODEL_6ca9851356704321bfb348f7e35ed982",
+       "layout": "IPY_MODEL_c6e6ac368c5a4449873a98219c8661cb",
        "tabbable": null,
        "tooltip": null
       }
      },
-     "e59d9f4919e843b5b7c0bc2b96e969f8": {
+     "d44038cacc8d42e8abfd86d0a4e826c6": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "HBoxModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_77f413c18d4e4d3a894392895d92f1ed",
-       "placeholder": "​",
-       "style": "IPY_MODEL_de422c87c3ae4c2eb70874d63a1bb006",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_5349c35dae514abea71f51d8f09cac45",
+        "IPY_MODEL_477ba2e67dfd4717924c5f7608d52e53",
+        "IPY_MODEL_201e28628be34c2e8e062e018b9b9fd7"
+       ],
+       "layout": "IPY_MODEL_68e958a6b6274ae4bed729bd49262241",
        "tabbable": null,
-       "tooltip": null,
-       "value": " 8/8 [00:00&lt;00:00, 671.09it/s]"
+       "tooltip": null
+      }
+     },
+     "d488657e901d40fbbc87f151a4a4529e": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_ec66c595522142caa7ca54c5168d3a60",
+        "IPY_MODEL_7b8f7c16dfb34595af13f52974c70506",
+        "IPY_MODEL_c72f9c8d00e94b4b8e7ea23fb7020485"
+       ],
+       "layout": "IPY_MODEL_574d4ec55e9e4cafbd82dcdc9c5a02dd",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "e647c1d281c44c60931c03522f370369": {
+     "d8b43dcfce0c4702be3a4668b21b113c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -7385,15 +7315,33 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_8a67375d76b44412b1920f9d5b44d790",
+       "layout": "IPY_MODEL_95859d460d094816af6c3f26b7df8f2d",
        "placeholder": "​",
-       "style": "IPY_MODEL_f77d4380d5b84054b3446084f5855e1d",
+       "style": "IPY_MODEL_20feb4ec43944e7db3f32a539f628d5a",
        "tabbable": null,
        "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
+       "value": " 2/2 [00:18&lt;00:00,  7.62s/it]"
+      }
+     },
+     "dec6c0dc17cd4c51b2d72208aee3499b": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLStyleModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
       }
      },
-     "e656028f0da6402aad23a38e176dfeb7": {
+     "decb33eabdcb4fc7ba7483570c236bd0": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "ProgressStyleModel",
@@ -7409,7 +7357,7 @@
        "description_width": ""
       }
      },
-     "e708771cec524aa3bdad31e9fdc78da4": {
+     "e1d66222d5064e64b4c1ed3190e995f7": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7462,43 +7410,152 @@
        "width": null
       }
      },
-     "e9395468c16241589a2280cc8a3274d9": {
+     "e42cd8df540b48999438b1b8582bf35d": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "ProgressStyleModel",
       "state": {
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "ProgressStyleModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
        "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "bar_color": null,
+       "description_width": ""
+      }
+     },
+     "e4a0496246364a9ca9e6499645b620a5": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/base",
+       "_model_module_version": "2.0.0",
+       "_model_name": "LayoutModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
+      }
+     },
+     "e5ddb5cbcd1b4203aa27d9aed508a4bf": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {
+       "_model_module": "@jupyter-widgets/base",
+       "_model_module_version": "2.0.0",
+       "_model_name": "LayoutModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "e93dd159472d4a0d972b5e06c42eeffc": {
+     "e6732a50301448349d86f0a991df0f37": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "HTMLModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_7660ac5fc8804a1d950e4cdb61a78fd4",
+       "placeholder": "​",
+       "style": "IPY_MODEL_d17abe4537c7407c98b0e7ef7f42b965",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "COLLECTING RESULTS | : 100%"
       }
      },
-     "e94d6af4d70b4e1bac63dee7dae0821c": {
+     "ea20a0a062984094885095a68938074c": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7551,7 +7608,7 @@
        "width": null
       }
      },
-     "ea3dc3af3d4d46e497494f48af4a2375": {
+     "ebbc50fd3a364b72bc4da24b64080777": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7604,65 +7661,7 @@
        "width": null
       }
      },
-     "eb4ddd4c29a844939c8970f9f5404f7a": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HBoxModel",
-      "state": {
-       "_dom_classes": [],
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HBoxModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
-       "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_fea963935a7041c89b34c38b4b4bc44d",
-        "IPY_MODEL_66c9ecfca6274545bf746e08b54e4be2",
-        "IPY_MODEL_46f533814b9d4e5e9f4471141ace10af"
-       ],
-       "layout": "IPY_MODEL_df9355f8c89841d7ad568f36ae03c24c",
-       "tabbable": null,
-       "tooltip": null
-      }
-     },
-     "ec0cba70bf7b451dab82ae6b681cc8da": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "ec3dc65a4cbd4a2f9ac95ca387cd550f": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
-     },
-     "ede433c7d3ea4445b5afc7890ce1a318": {
+     "ec66c595522142caa7ca54c5168d3a60": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -7677,15 +7676,15 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_dea047af89b54f028876e10ec888264a",
+       "layout": "IPY_MODEL_b4b2c859c45e45548515f0fb55ecad58",
        "placeholder": "​",
-       "style": "IPY_MODEL_5e517652a0b248018c5028b8b724d456",
+       "style": "IPY_MODEL_2632e115d8bc49438acfdce4300a22a2",
        "tabbable": null,
        "tooltip": null,
-       "value": " 13/13 [00:00&lt;00:00, 1717.35it/s]"
+       "value": "COLLECTING RESULTS | : 100%"
       }
      },
-     "ee0bf5343a0c48f99e77b01a43193990": {
+     "efb0842a6d164ffa9bb61f574f9bd688": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7738,25 +7737,60 @@
        "width": null
       }
      },
-     "ee597dc7346241e4ae03cacf6e23f267": {
-      "model_module": "@jupyter-widgets/controls",
+     "f095a4328ef6452ab12496a1cd38a7d3": {
+      "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "LayoutModel",
       "state": {
-       "_model_module": "@jupyter-widgets/controls",
+       "_model_module": "@jupyter-widgets/base",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "LayoutModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "LayoutView",
+       "align_content": null,
+       "align_items": null,
+       "align_self": null,
+       "border_bottom": null,
+       "border_left": null,
+       "border_right": null,
+       "border_top": null,
+       "bottom": null,
+       "display": null,
+       "flex": null,
+       "flex_flow": null,
+       "grid_area": null,
+       "grid_auto_columns": null,
+       "grid_auto_flow": null,
+       "grid_auto_rows": null,
+       "grid_column": null,
+       "grid_gap": null,
+       "grid_row": null,
+       "grid_template_areas": null,
+       "grid_template_columns": null,
+       "grid_template_rows": null,
+       "height": null,
+       "justify_content": null,
+       "justify_items": null,
+       "left": null,
+       "margin": null,
+       "max_height": null,
+       "max_width": null,
+       "min_height": null,
+       "min_width": null,
+       "object_fit": null,
+       "object_position": null,
+       "order": null,
+       "overflow": null,
+       "padding": null,
+       "right": null,
+       "top": null,
+       "visibility": null,
+       "width": null
       }
      },
-     "efe2a151adea421fb2715722acd6087d": {
+     "f1629a69f36a487da20b06f98f95e791": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7809,7 +7843,7 @@
        "width": null
       }
      },
-     "f388d7eec7074dd9bf1d708c3bc2eb8b": {
+     "f2d044437208464d878d0cd256392ad5": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLModel",
@@ -7824,75 +7858,112 @@
        "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_3b5c749479034a83ae323499fe1a63c3",
+       "layout": "IPY_MODEL_265a2a74cc9e47b8ad6e77f51af85e8c",
        "placeholder": "​",
-       "style": "IPY_MODEL_6089d1da4e064de68179493ab6ddf356",
+       "style": "IPY_MODEL_bc793225325243cb94628279e125795a",
        "tabbable": null,
        "tooltip": null,
-       "value": " 2/2 [00:00&lt;00:00, 213.83it/s]"
+       "value": " 8/8 [00:00&lt;00:00, 1179.96it/s]"
       }
      },
-     "f77d4380d5b84054b3446084f5855e1d": {
+     "f3c5c6baeff344dfa91a59f364dfbce7": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "FloatProgressModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "FloatProgressModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_ae4fb999d7894239863176332db55fab",
+       "max": 13.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_c756f388b892437786c3af7b73dadd5d",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 13.0
       }
      },
-     "f8fbd2f91bb84f27aab228f586f8c6c1": {
+     "f67f65d982d74f4fb6532b8660ada12c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HBoxModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_68f78f13ec1449519176b367bbbab96b",
+        "IPY_MODEL_02c79c10bf5247e08a75f687330e4c33",
+        "IPY_MODEL_87f794efe7fb4c3a9d6118714a0d5bae"
+       ],
+       "layout": "IPY_MODEL_32fda6dbeb094ab199ef026b57b445ef",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "f95487f3733e41c48bc5844d720ba78c": {
+     "f7304182ac6548259e02512c0e47680c": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "FloatProgressModel",
+      "model_name": "HTMLModel",
       "state": {
        "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "FloatProgressModel",
+       "_model_name": "HTMLModel",
        "_view_count": null,
        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "ProgressView",
-       "bar_style": "success",
+       "_view_name": "HTMLView",
        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_488c2910003146fc9842f19d968c2661",
-       "max": 14.0,
-       "min": 0.0,
-       "orientation": "horizontal",
-       "style": "IPY_MODEL_73bf46924c2c46d0b07ec03d31bd47fe",
+       "layout": "IPY_MODEL_8c3b9aac6689443ba212d0e8f67322ac",
+       "placeholder": "​",
+       "style": "IPY_MODEL_bf7bc477add842449c0768c6971beb19",
        "tabbable": null,
        "tooltip": null,
-       "value": 14.0
+       "value": " 8/8 [00:03&lt;00:00,  2.47it/s]"
+      }
+     },
+     "fb935d04a3fa4d70b17eecf880d6f78e": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_576b5c8e1f684d89871e519adfd4dca3",
+        "IPY_MODEL_9b9e6d8e5c6b43aa98a6ff07ca445ba5",
+        "IPY_MODEL_f7304182ac6548259e02512c0e47680c"
+       ],
+       "layout": "IPY_MODEL_e4a0496246364a9ca9e6499645b620a5",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "fa0e9d2659ca4a3d975485769392b441": {
+     "fbc06ed872314ab7aea6daf42fa18343": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -7945,46 +8016,47 @@
        "width": null
       }
      },
-     "fa48572a000d4b48aa18c1ea6ba766d4": {
+     "fc4b59a25baf4921b46c620ed2ad4db1": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "ProgressStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "ProgressStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_d2a9027221a64178b5081e8597e0b9e2",
-       "placeholder": "​",
-       "style": "IPY_MODEL_7f02b48ee2404301b4b395fb08b8150b",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 4/4 [00:00&lt;00:00, 351.93it/s]"
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
       }
      },
-     "fc595229161344dcb6af6ad2a9856932": {
+     "fd5ccd1dca8a4bf5aff667fe5e46d41e": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
+      "model_name": "HBoxModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_3c8d43c6215f4c38bf6c276717b3a0d2",
+        "IPY_MODEL_7c5b994a5dc34ce2a42ee354bdd0bc2d",
+        "IPY_MODEL_f2d044437208464d878d0cd256392ad5"
+       ],
+       "layout": "IPY_MODEL_356c81c7253e40b488b1a7a7be7a1a09",
+       "tabbable": null,
+       "tooltip": null
       }
      },
-     "fe95884dc1cf4bafabd054ca6d93578e": {
+     "ff29b139d598449c8402639f09358b82": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -8037,27 +8109,20 @@
        "width": null
       }
      },
-     "fea963935a7041c89b34c38b4b4bc44d": {
+     "ffdd290fffb943b8b76793f28e17a0b8": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLModel",
+      "model_name": "ProgressStyleModel",
       "state": {
-       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
+       "_model_name": "ProgressStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
-       "description": "",
-       "description_allow_html": false,
-       "layout": "IPY_MODEL_3a637204f44b44eda06c15012981e659",
-       "placeholder": "​",
-       "style": "IPY_MODEL_b5e1a99ce98b4b97987af4936a2d5072",
-       "tabbable": null,
-       "tooltip": null,
-       "value": "PROCESSING TASKS | : 100%"
+       "_view_name": "StyleView",
+       "bar_color": null,
+       "description_width": ""
       }
      }
     },
diff --git a/tasks/docs.py b/tasks/docs.py
index a5ca972..e163c56 100644
--- a/tasks/docs.py
+++ b/tasks/docs.py
@@ -53,6 +53,6 @@ def watch(_ctx):
 def render_notebooks_for_docs(_ctx):
     """Render jupyter notebooks for docs."""
     print_and_run(
-        (f"{PROJECT_DIR}/notebooks/generate_rendered_notebook_for_docs.sh"),
+        (f"{PROJECT_DIR}/notebooks/generate_rendered_notebooks_for_docs.sh"),
         pty=True,
     )

From a01cbf6e33f125075bf9e8c807956d82a7d67871 Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Mon, 9 Dec 2024 10:59:22 -0700
Subject: [PATCH 09/10] Update README usage info

---
 README.md | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index dacf646..3680274 100644
--- a/README.md
+++ b/README.md
@@ -47,11 +47,9 @@ pip install nsidc-iceflow
 
 ### Using `iceflow`
 
-```python
-from nsidc import iceflow
-
-# TODO
-```
+See
+[Getting started with iceflow](https://iceflow.readthedocs.io/en/latest/getting-started.html)
+for information and examples about how to use `iceflow`.
 
 ## Credit
 

From 8e035a4823a184b8003e6766be2d92988d0441ab Mon Sep 17 00:00:00 2001
From: Trey Stafford <trey.stafford@colorado.edu>
Date: Mon, 9 Dec 2024 11:10:40 -0700
Subject: [PATCH 10/10] Tweak pandera dep pin in `pyproject.toml`

Newer version breaks some things...
---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 531ff05..ca95d65 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -31,7 +31,7 @@ dependencies = [
   "gps-timemachine >=1.1.4",
   "pyproj >=3.6.1",
   "shapely >=2.0.5",
-  "pandera[mypy] >= 0.20.3",
+  "pandera[mypy] ~= 0.20.3",
   "pydantic >=2.8.2",
   "loguru >=0.7.2",
   "dask[dataframe] >=2024.10.0",