Merge pull request #243 from agilescientific/develop

release v0.5.3

tests/test_plots.py

@@ -9,6 +9,7 @@
 
 https://pypi.python.org/pypi/pytest-mpl/0.3
 """
+import matplotlib.pyplot as plt
 import pytest
 
 from welly import Well
@@ -114,7 +115,8 @@ def test_synthetic_plot():
     test_params = {'dt': 0.004}
     s = Synthetic(data, params=test_params)
 
-    fig = s.plot().get_figure()
+    fig, ax = plt.subplots(figsize=(2, 10))
+    s.plot(ax)
 
     return fig
 
@@ -127,7 +129,8 @@ def test_well_synthetic_plot():
     w = Well.from_las(FNAME)
     w.make_synthetic()
 
-    fig = w.data['Synthetic'].plot().get_figure()
+    fig, ax = plt.subplots(figsize=(2, 10))
+    w.data['Synthetic'].plot(ax)
 
     return fig
 

tests/test_synthetic.py

@@ -1,6 +1,6 @@
 # -*- coding: utf 8 -*-
 """
-Define a suite a tests for the Curve module.
+Define a suite a tests for the Synthetic class.
 """
 import numpy as np
 
@@ -17,3 +17,18 @@ def test_synthetic():
 
     assert s.dt == 0.004
     assert s.name == 'Synthetic'
+
+
+def test_synthetic_as_curve():
+    """
+    Test synthetic to curve.
+    """
+    data = np.array([4, 2, 0, -4, -2, 1, 3, 6, 3, 1, -2, -5, -1, 0])
+    params = {'dt': 0.004}
+    s = Synthetic(data, params=params)
+
+    crv = s.as_curve(0, 500, 0.1, mnemonic="SYNTH_CRV")
+
+    assert crv.index[0] == 0
+    assert round((crv.index[1]-crv.index[0]),2) == 0.1
+    assert crv.mnemonic == 'SYNTH_CRV'

welly/location.py

@@ -338,7 +338,7 @@ def trajectory(self, datum=None, elev=True, points=1000, **kwargs):
 
         Returns:
             ndarray. An array with shape (`points` x 3) representing the well
-                trajectory. Columns are (x, y, z). 
+                trajectory. Columns are (x, y, z).
         """
         pos = self.position.copy()
 

welly/synthetic.py

@@ -55,14 +55,22 @@ def basis(self):
         precision_adj = self.dt / 100
         return np.arange(self.start, self.stop - precision_adj, self.dt)
 
-    def as_curve(self, data):
+    def as_curve(self, depth_start=0., depth_stop=99999., depth_step=0.1524, mnemonic="SYN"):
         """
         Get the synthetic as a Curve, in depth. Facilitates plotting along-
         side other curve data.
         """
-        params = {'mnemonic': 'SYN'}
+        if depth_stop <= 0.:
+            depth_stop = 99999.
 
-        return Curve(data, **params)
+        new_crv = None
+        if depth_stop > depth_start:
+            depth_basis = np.arange(depth_start, depth_stop+depth_step, depth_step)
+            data = np.interp(depth_basis, self.basis, self)
+
+            new_crv = Curve(data, mnemonic=mnemonic, index=depth_basis)
+
+        return new_crv
 
     def plot(self, ax=None, **kwargs):
         """
@@ -93,5 +101,5 @@ def plot(self, ax=None, **kwargs):
 
         if return_ax:
             return ax
-
-        return fig
+        else:
+            return None

welly/utils.py

@@ -84,7 +84,7 @@ def bbox(points):
 
 def aspect(points):
     """
-    Aspect like 2:1 is twice as wide as high.
+    Aspect like 2:1 is shape like |___ (twice as wide as high).
 
     This function returns the WIDTH per unit height.
     """
@@ -542,16 +542,16 @@ def ricker(f, length, dt):
     A Ricker wavelet.
 
     Args:
-        f (float): frequency in Haz, e.g. 25 Hz.
+        f (float): frequency in Hz, e.g. 25 Hz.
         length (float): Length in s, e.g. 0.128.
         dt (float): sample interval in s, e.g. 0.001.
 
     Returns:
         tuple. time basis, amplitude values.
     """
-    t = np.linspace(-int(length / 2), int((length - dt) / 2), int(length / dt))
-    y = (1. - 2. * (np.pi ** 2) * (f ** 2) * (t ** 2)) * np.exp(-(np.pi ** 2) * (f ** 2) * (t ** 2))
-    return t, y
+    time = np.arange(-length/2, length/2, dt)
+    amp = (1. - 2.*(np.pi**2)*(f**2)*(time**2))*np.exp(-(np.pi**2)*(f**2)*(time**2))
+    return time, amp
 
 
 def hex_to_rgb(hexx):

welly/well.py

@@ -935,27 +935,33 @@ def is_complete(self, keys=None, alias=None):
     def alias_has_multiple(self, mnemonic, alias):
         return 1 < len([a for a in alias[mnemonic] if a in self.data])
 
-    def make_synthetic(self, srd=0, v_repl_seismic=2000, v_repl_log=2000, f=50,
+    def make_synthetic(self,
+                       srd=0,
+                       sonic_mnemonic="DT",
+                       density_mnemonic="RHOB",
+                       v_repl_seismic=2000,
+                       v_repl_log=2000,
+                       f=50,
                        dt=0.001):
         """
         Early hack. Use with extreme caution.
 
         Hands-free. There'll be a more granualr version in synthetic.py.
 
-        Assumes DT is in µs/m and RHOB is kg/m3.
+        Assumes Sonic is in µs/m and Density is kg/m3.
 
         There is no handling yet for TVD.
 
         The datum handling is probably sketchy.
         """
         kb = getattr(self.location, 'kb', None) or 0
-        data0 = self.data['DT'].start
+        data0 = self.data[sonic_mnemonic].start
         log_start_time = ((srd - kb) / v_repl_seismic) + (data0 / v_repl_log)
 
         # Basic log values.
-        dt_log = self.data['DT'].despike()  # assume µs/m
-        rho_log = self.data['RHOB'].despike()  # assume kg/m3
-        if not np.allclose(dt_log.df.index, rho_log.df.index):
+        dt_log = self.data[sonic_mnemonic].despike()  # assume µs/m
+        rho_log = self.data[density_mnemonic].despike()  # assume kg/m3
+        if not np.allclose(dt_log.basis, rho_log.basis):
             rho_log = rho_log.to_basis_like(dt_log)
         Z = (1e6 / dt_log.df.values) * rho_log.df.values
 
@@ -977,12 +983,13 @@ def make_synthetic(self, srd=0, v_repl_seismic=2000, v_repl_log=2000, f=50,
 
         # Convolve.
         _, ricker = utils.ricker(f=f, length=0.128, dt=dt)
-        synth = np.convolve(ricker, rc_t, mode='same')
+        synth = np.convolve(rc_t, ricker, mode='same')
 
-        params = {'dt': dt, 'z start': dt_log.start, 'z stop': dt_log.stop}
+        params = {'dt': dt,
+                  'start': dt_log.start,
+                  }
 
         self.data['Synthetic'] = Synthetic(synth, basis=t_reg, params=params)
-
         return None
 
     def qc_curve_group(self, tests, keys=None, alias=None):