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Plotting.py
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"""
Package of custom plotting functions
"""
import itertools
import matplotlib as mpl
import matplotlib.pyplot as mplt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import copy
import pandas as pd
import numpy as np
import numpy.ma as ma
__author__ = 'Michael N Rossol'
__all__ = ["COLORS", "change_tick_style", "get_COLORS", "def_linestyles",
"def_markers", "riffle", "line_plot", "dual_plot", "error_plot",
"bar_chart", "contour_plot", "scatter_plot", "surface_plot",
"colorbar"]
COLORS = {
"red": (0.7176, 0.1098, 0.1098),
"green": (0.65 * 0.298, 0.65 * 0.6863, 0.65 * 0.3137),
"blue": (0.9 * 0.0824, 0.9 * 0.3961, 0.9 * 0.7529),
"orange": (0.85 * 1.0, 0.85 * 0.5961, 0.0),
"purple": (0.49412, 0.3412, 0.7608),
"grey": (0.45, 0.45, 0.45),
"cyan": (0.0, 0.7373, 0.8314),
"teal": (0.0, 0.5882, 0.5333),
"lime": (0.8039, 0.8627, 0.2235),
"brown": (0.4745, 0.3333, 0.2824),
"black": (0.0, 0.0, 0.0)
}
def change_tick_style(style):
if style == 'classic':
mpl.rcParams['xtick.direction'] = 'in'
mpl.rcParams['ytick.direction'] = 'in'
mpl.rcParams['xtick.top'] = True
mpl.rcParams['ytick.right'] = True
else:
mpl.rcParams['xtick.direction'] = 'out'
mpl.rcParams['ytick.direction'] = 'out'
mpl.rcParams['xtick.top'] = False
mpl.rcParams['ytick.right'] = False
def get_COLORS(colors, n=None):
"""
Parameters
----------
colors : 'list'
List of strings of color names
n : 'int'
repeat each color in colors n times
Returns
-------
RGB color codes for plotting functions
"""
if n is not None:
colors = np.asarray([[color, ] * n for color in colors]).flatten()
return [COLORS[color] for color in colors]
def_linestyles = ('-', '--', '-.', ':')
def_markers = (u'o', u'v', u'^', u'<', u'>', u'8', u's', u'p', u'*', u'h',
u'H', u'D', u'd')
def riffle(*args):
"""
Parameters
----------
*args : 'Tuple'
set of lists to be riffled together
Returns
-------
Flattened list of lists such that entries are riffled
"""
return [item for sublist in zip(*args) for item in sublist]
def line_plot(data, xlabel=None, ylabel=None, xlim=None, ylim=None,
xticks=None, yticks=None, ticksize=(8, 2),
xtick_labels=None, ytick_labels=None,
colors=None, linestyles='Automatic', linewidth=2, markers=None,
markersize=5, markeredge=['k', 0.5], font='Arial',
fontsize_axes=18, fontsize_other=16, borderwidth=2,
add_legend=None, legend_location=0, figsize=(6.4, 4.8),
resolution=100, showfig=True, filename=None):
"""
Parameters
----------
data : 'ndarray', shape(data[i]) = (n,2)
Either a tuple or list of nx2 arrays or a single nx2 array.
xlabel : 'String'
Label for x-axis.
ylabel : 'String'
Label for y-axis.
xlim : 'tuple', len(xlim) == 2
Upper and lower limits for the x-axis.
ylim : 'tuple', len(ylim) == 2
Upper and lower limits for the y-axis.
xticks : 'ndarray'
List of ticks to use on the x-axis. Should be within the bounds set by
xlim.
yticks : 'ndarray'
List of ticks to use on the y-axis. Should be within the bound set by
ylim.
ticksize : 'ndarray', default '[8,2]'
Length and width of ticks.
xtick_labels : 'list'
List of custome xticks. Note len(xticks) == len(xtick_labels)
ytick_labels : 'list'
List of custome yticks. Note len(yticks) == len(ytick_labels)
colors : 'ndarray'
Iterable list of colors to plot for each line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
linestyles : 'ndarray'
Iterable list of Matplotlib designations for the linestyle for each
line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
linewidth : 'Int'
Line width for each line in 'data'.
markersize : 'Float'
Marker size for each marker in 'data'.
markeredge : 'list'
[marker edge color, marker edge width]
markers : 'ndarray'
Iterable list of Matplotlib designations for the marker for each line
in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
font : 'String'
Font to be used.
fontsize_axes : 'Int'
Font size to be used for axes labels.
fontsize_other : 'Int'
Font size to be used for all other text (legend, axis numbers, etc.).
boarderwidth : 'Int'
Linewidth of plot frame
add_legend : 'Bool', default = 'False'
If 'True' a legend will be added at 'legendlocation'.
legend_location : 'String' or 'Int', default = '0'
Matplotlib designator for legend location, default is 'best'.
figsize : 'Tuple', default = '(8,6)'
Width and height of figure
resolution : 'Int', default = '300'
DPI resolution of figure.
showfig : 'Bool', default = 'True'
Whether to show figure.
filename : 'String', default = None.
Name of file/path to save the figure to.
Returns
-------
Plots the lines in 'data'.
"""
if not isinstance(data, (list, tuple)):
lines = (data,)
else:
lines = data
if colors is not None:
colors = itertools.cycle(colors)
else:
colors = itertools.cycle((COLORS["blue"],
COLORS["green"],
COLORS["red"],
COLORS["orange"],
COLORS["purple"],
COLORS["grey"],
COLORS["cyan"],
COLORS["teal"],
COLORS["lime"],
COLORS["brown"]))
if linestyles is None:
linestyles = itertools.cycle(('',))
elif linestyles == 'Automatic':
linestyles = itertools.cycle(def_linestyles)
else:
linestyles = itertools.cycle(linestyles)
if markers is None:
markers = itertools.cycle(('',))
elif markers == 'Automatic':
markers = itertools.cycle(def_markers)
else:
markers = itertools.cycle(markers)
if markeredge is not None:
mec, mew = markeredge
else:
mec = None
mew = None
fig = mplt.figure(figsize=figsize, dpi=resolution)
axis = fig.add_subplot(111)
for line in lines:
axis.plot(line[:, 0], line[:, 1], markersize=markersize,
marker=next(markers), mec=mec, mew=mew, color=next(colors),
linestyle=next(linestyles), linewidth=linewidth)
mpl.rcParams['font.sans-serif'] = font
mpl.rcParams['pdf.fonttype'] = 42
# update plot labels and format based on user input
for ax in ['top', 'bottom', 'left', 'right']:
axis.spines[ax].set_linewidth(borderwidth)
if xlabel is not None:
axis.set_xlabel(xlabel, fontsize=fontsize_axes)
if ylabel is not None:
axis.set_ylabel(ylabel, fontsize=fontsize_axes)
if xlim is not None:
axis.set_xlim(xlim)
if ylim is not None:
axis.set_ylim(ylim)
axis.tick_params(axis='both', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0])
if xticks is not None:
axis.set_xticks(xticks)
if xtick_labels is not None:
axis.set_xticklabels(xtick_labels)
if yticks is not None:
axis.set_yticks(yticks)
if ytick_labels is not None:
axis.set_yticklabels(ytick_labels)
if add_legend is not None:
mplt.legend(add_legend, prop={'size': 12}, loc=legend_location)
fig.tight_layout()
if filename is not None:
mplt.savefig(filename, dpi=resolution, transparent=True,
bbox_inches='tight')
if showfig:
mplt.show()
mplt.close()
def bar_chart(data, bar_gap=0.1, xlabel=None, ylabel=None, xlim=None,
ylim=None, xticks=None, yticks=None, ticksize=(8, 2),
colors=None, orientation='vertical', font='Arial',
fontsize_axes=18, fontsize_other=16, borderwidth=2,
add_legend=None, legend_location=0, figsize=(6.4, 4.8),
resolution=100, showfig=True, filename=None):
"""
Parameters
----------
data : 'pandas Series or DataFrame',
Either a pandas Series or DataFrame. Bars are values, xlabels are
indeces.
bar_gap : 'float'
Spacing between bars as percentage of full width
xlabel : 'String'
Label for x-axis.
ylabel : 'String'
Label for y-axis.
xlim : 'tuple', len(xlim) == 2
Upper and lower limits for the x-axis.
ylim : 'tuple', len(ylim) == 2
Upper and lower limits for the y-axis.
xticks : 'ndarray'
List of ticks to use on the x-axis. Default is the index of the Series
or DataFrame.
yticks : 'ndarray'
List of ticks to use on the y-axis. Should be within the bound set by
ylim.
ticksize : 'ndarray', default '[8,2]'
Length and width of ticks.
colors : 'ndarray'
Iterable list of colors to plot for each line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
font : 'String'
Font to be used.
fontsize_axes : 'Int'
Font size to be used for axes labels.
fontsize_other : 'Int'
Font size to be used for all other text (legend, axis numbers, etc.).
boarderwidth : 'Int'
Linewidth of plot frame
add_legend : 'Bool', default = 'False'
If 'True' a legend will be added at 'legendlocation'.
legend_location : 'String' or 'Int', default = '0'
Matplotlib designator for legend location, default is 'best'.
figsize : 'Tuple', default = '(8,6)'
Width and height of figure
resolution : 'Int', default = '300'
DPI resolution of figure.
showfig : 'Bool', default = 'True'
Whether to show figure.
filename : 'String', default = None.
Name of file/path to save the figure to.
Returns
-------
Plots a bar chart from the Series or DataFrame in 'data'.
"""
if isinstance(data, pd.Series):
bars = (data,)
else:
bars = [data[col].values for col in data.columns]
xs = np.arange(len(data))
if colors is not None:
colors = itertools.cycle(colors)
else:
colors = itertools.cycle((COLORS["blue"],
COLORS["green"],
COLORS["red"],
COLORS["orange"],
COLORS["purple"],
COLORS["grey"],
COLORS["cyan"],
COLORS["teal"],
COLORS["lime"],
COLORS["brown"]))
bar_width = (1 - bar_gap * 2) / len(bars)
s_width = bar_gap
c_shift = 0.5
fig = mplt.figure(figsize=figsize, dpi=resolution)
axis = fig.add_subplot(111)
for i, yheight in enumerate(bars):
axis.bar(xs + s_width + bar_width * i, yheight, bar_width,
color=next(colors), orientation=orientation)
mpl.rcParams['font.sans-serif'] = font
mpl.rcParams['pdf.fonttype'] = 42
# update plot labels and format based on user input
for ax in ['top', 'bottom', 'left', 'right']:
axis.spines[ax].set_linewidth(borderwidth)
if xlabel is not None:
axis.set_xlabel(xlabel, fontsize=fontsize_axes)
if ylabel is not None:
axis.set_ylabel(ylabel, fontsize=fontsize_axes)
if xlim is None:
axis.set_xlim(xs[0], xs[-1] + 1)
else:
axis.set_xlim(xlim)
if ylim is not None:
axis.set_ylim(ylim)
axis.tick_params(axis='both', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0])
axis.set_xticks(xs + c_shift)
if xticks is None:
axis.set_xticklabels(data.index, rotation=orientation)
else:
axis.set_xticklabels(xticks, rotation=orientation)
if yticks is not None:
axis.set_yticks(yticks)
if add_legend is not None:
mplt.legend(add_legend, prop={'size': 12}, loc=legend_location)
fig.tight_layout()
if filename is not None:
mplt.savefig(filename, dpi=resolution, transparent=True,
bbox_inches='tight')
if showfig:
mplt.show()
mplt.close()
def dual_plot(data1, data2, xlabel=None, ylabel=None, xlim=None, ylim=None,
xticks=None, yticks=None, ticksize=(8, 2),
xtick_labels=None, ytick_labels=None, axis_colors='k',
colors=None, linestyles='Automatic', linewidth=2, markers=None,
markersize=5, markeredge=['k', 0.5], font='Arial',
fontsize_axes=18, fontsize_other=16, borderwidth=2,
add_legend=None, legend_location=0, figsize=(6.4, 4.8),
resolution=100, showfig=True, filename=None):
"""
Parameters
----------
data1 : 'ndarray', shape(data2[i]) = (n,2)
Either a tuple or list of nx2 arrays or a single nx2 array.
data2 : 'ndarray', shape(data2[i]) = (n,2)
Either a tuple or list of nx2 arrays or a single nx2 array.
xlabel : 'String'
Label for x-axis.
ylabel : 'String'
Label for y-axis.
xlim : 'tuple', len(xlim) == 2
Upper and lower limits for the x-axis.
ylim : 'tuple', len(ylim) == 2
Upper and lower limits for the y-axis.
xticks : 'ndarray'
List of ticks to use on the x-axis. Should be within the bounds set by
xlim.
yticks : 'ndarray'
List of ticks to use on the y-axis. Should be within the bound set by
ylim.
ticksize : 'ndarray', default '[8,2]'
Length and width of ticks.
xtick_labels : 'list'
List of custome xticks. Note len(xticks) == len(xtick_labels)
ytick_labels : 'list'
List of custome yticks. Note len(yticks) == len(ytick_labels)
axis_colors : 'string', 'tuple'
string indicating y-axis colors, tuple of strings indicates color of
each y-axis
colors : 'ndarray'
Iterable list of colors to plot for each line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
linestyles : 'ndarray'
Iterable list of Matplotlib designations for the linestyle for each
line in 'data'. Will be cycled if fewer entries are specified than the
number of lines in 'data'.
linewidth : 'Int'
Line width for each line in 'data'.
markersize : 'Float'
Marker size for each marker in 'data'.
markeredge : 'list'
[marker edge color, marker edge width]
markers : 'ndarray'
Iterable list of Matplotlib designations for the marker for each line
in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
font : 'String'
Font to be used.
fontsize_axes : 'Int'
Font size to be used for axes labels.
fontsize_other : 'Int'
Font size to be used for all other text (legend, axis numbers, etc.).
boarderwidth : 'Int'
Linewidth of plot frame
add_legend : 'Bool', default = 'False'
If 'True' a legend will be added at 'legendlocation'.
legend_location : 'String' or 'Int', default = '0'
Matplotlib designator for legend location, default is 'best'.
figsize : 'Tuple', default = '(8,6)'
Width and height of figure
resolution : 'Int', default = '300'
DPI resolution of figure.
showfig : 'Bool', default = 'True'
Whether to show figure.
filename : 'String', default = None.
Name of file/path to save the figure to.
Returns
-------
Plots the lines in 'data1' and lines in 'data2' on a dual y-axis plot.
"""
if not isinstance(data1, (list, tuple)):
lines1 = (data1,)
else:
lines1 = data1
if not isinstance(data2, (list, tuple)):
lines2 = (data2,)
else:
lines2 = data2
if colors is not None:
if isinstance(colors[0], list):
colors1 = itertools.cycle(colors[0])
colors2 = itertools.cycle(colors[1])
else:
colors1 = itertools.cycle(colors[::2])
colors2 = itertools.cycle(colors[1::2])
else:
colors1 = itertools.cycle((COLORS["blue"],
COLORS["red"],
COLORS["purple"],
COLORS["cyan"],
COLORS["lime"]))
colors2 = itertools.cycle((COLORS["green"],
COLORS["orange"],
COLORS["grey"],
COLORS["teal"],
COLORS["brown"]))
if linestyles is None:
linestyles1 = itertools.cycle(('',))
linestyles2 = itertools.cycle(('',))
elif linestyles == 'Automatic':
linestyles1 = itertools.cycle(def_linestyles[::2])
linestyles2 = itertools.cycle(def_linestyles[1::2])
else:
if isinstance(linestyles[0], (list, tuple)):
linestyles1 = itertools.cycle(linestyles[0])
linestyles2 = itertools.cycle(linestyles[1])
else:
linestyles1 = itertools.cycle(linestyles[::2])
linestyles2 = itertools.cycle(linestyles[1::2])
if markers is None:
markers1 = itertools.cycle(('',))
markers2 = itertools.cycle(('',))
elif markers == 'Automatic':
markers1 = itertools.cycle(def_markers[::2])
markers2 = itertools.cycle(def_markers[1::2])
else:
if isinstance(markers[0], (list, tuple)):
markers1 = itertools.cycle(markers[0])
markers2 = itertools.cycle(markers[1])
else:
markers1 = itertools.cycle(markers[::2])
markers2 = itertools.cycle(markers[1::2])
if len(axis_colors) == 1:
axis_color1 = axis_colors
axis_color2 = axis_colors
else:
axis_color1 = axis_colors[0]
axis_color2 = axis_colors[1]
if markeredge is not None:
mec, mew = markeredge
else:
mec = None
mew = None
fig = mplt.figure(figsize=figsize, dpi=resolution)
axis1 = fig.add_subplot(111)
for line in lines1:
axis1.plot(line[:, 0], line[:, 1], linewidth=linewidth,
markersize=markersize, marker=next(markers1),
color=next(colors1), linestyle=next(linestyles1),
mec=mec, mew=mew)
axis2 = axis1.twinx()
for line in lines2:
axis2.plot(line[:, 0], line[:, 1], linewidth=linewidth,
markersize=markersize, marker=next(markers2),
color=next(colors2), linestyle=next(linestyles2),
mec=mec, mew=mew)
mpl.rcParams['font.sans-serif'] = font
mpl.rcParams['pdf.fonttype'] = 42
# update plot labels and format based on user input
for ax in ['top', 'bottom', 'left', 'right']:
axis1.spines[ax].set_linewidth(borderwidth)
axis2.spines[ax].set_linewidth(borderwidth)
if xlabel is not None:
axis1.set_xlabel(xlabel, fontsize=fontsize_axes)
if ylabel is not None:
if len(ylabel) == 1:
axis1.set_ylabel(ylabel, fontsize=fontsize_axes, color=axis_color1)
axis2.set_ylabel(ylabel, fontsize=fontsize_axes, color=axis_color2)
else:
axis1.set_ylabel(ylabel[0], fontsize=fontsize_axes,
color=axis_color1)
axis2.set_ylabel(ylabel[1], fontsize=fontsize_axes,
color=axis_color2)
if xlim is not None:
axis1.set_xlim(xlim)
if ylim is not None:
if len(np.asarray(ylim).shape) == 1:
axis1.set_ylim(ylim)
axis2.set_ylim(ylim)
else:
axis1.set_ylim(ylim[0])
axis2.set_ylim(ylim[1])
if xticks is not None:
axis1.set_xticks(xticks)
if xtick_labels is not None:
axis1.set_xticklabels(xtick_labels)
if yticks is not None:
if len(np.asarray(yticks).shape) == 1:
axis1.set_set_yticks(yticks)
axis2.set_set_yticks(yticks)
else:
axis1.set_set_yticks(yticks[0])
axis2.set_set_yticks(yticks[1])
if ytick_labels is not None:
if len(np.asarray(ytick_labels).shape) == 1:
axis1.set_set_yticklabels(ytick_labels)
axis2.set_set_yticklabels(ytick_labels)
else:
axis1.set_set_yticklabels(ytick_labels[0])
axis2.set_set_yticklabels(ytick_labels[1])
axis1.tick_params(axis='x', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0], color='k')
axis1.tick_params(axis='y', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0], color=axis_color1)
axis2.tick_params(axis='y', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0], color=axis_color2)
if len(axis_colors) == 2:
for tl in axis1.get_yticklabels():
tl.set_color(axis_colors[0])
for t2 in axis2.get_yticklabels():
t2.set_color(axis_colors[1])
if add_legend is not None:
mplt.legend(add_legend, prop={'size': 12}, loc=legend_location)
fig.tight_layout()
if filename is not None:
mplt.savefig(filename, dpi=resolution, transparent=True,
bbox_inches='tight')
if showfig:
mplt.show()
mplt.close()
def error_plot(data_error, xlabel=None, ylabel=None, xlim=None, ylim=None,
xticks=None, yticks=None, ticksize=(8, 2),
xtick_labels=None, ytick_labels=None, capsize=6,
colors=None, linestyles=None, linewidth=2, markers='Automatic',
markersize=5, markeredge=['k', 0.5], font='Arial',
fontsize_axes=18, fontsize_other=16, borderwidth=2,
add_legend=None, legend_location=0, figsize=(6.4, 4.8),
resolution=100, showfig=True, filename=None):
"""
Parameters
----------
data_error : 'list'
list of [(data, error)] arrays.
data is an nx2 array (x, y)
error is an nx2 array (x_error, y_error)
xlabel : 'String'
Label for x-axis.
ylabel : 'String'
Label for y-axis.
xlim : 'tuple', len(xlim) == 2
Upper and lower limits for the x-axis.
ylim : 'tuple', len(ylim) == 2
Upper and lower limits for the y-axis.
xticks : 'ndarray'
List of ticks to use on the x-axis. Should be within the bounds set by
xlim.
yticks : 'ndarray'
List of ticks to use on the y-axis. Should be within the bound set by
ylim.
ticksize : 'ndarray', default '[8,2]'
Length and width of ticks.
xtick_labels : 'list'
List of custome xticks. Note len(xticks) == len(xtick_labels)
ytick_labels : 'list'
List of custome yticks. Note len(yticks) == len(ytick_labels)
capsize : 'int'
size of error bar cap
colors : 'ndarray'
Iterable list of colors to plot for each line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
linestyles : 'ndarray'
Iterable list of Matplotlib designations for the linestyle for each
line in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
linewidth : 'Int'
Line width for each line in 'data'.
markersize : 'Float'
Marker size for each marker in 'data'.
markeredge : 'list'
[marker edge color, marker edge width]
markers : 'ndarray'
Iterable list of Matplotlib designations for the marker for each line
in 'data'.
Will be cycled if fewer entries are specified than the number of lines
in 'data'.
font : 'String'
Font to be used.
fontsize_axes : 'Int'
Font size to be used for axes labels.
fontsize_other : 'Int'
Font size to be used for all other text (legend, axis numbers, etc.).
boarderwidth : 'Int'
Linewidth of plot frame
add_legend : 'Bool', default = 'False'
If 'True' a legend will be added at 'legendlocation'.
legend_location : 'String' or 'Int', default = '0'
Matplotlib designator for legend location, default is 'best'.
figsize : 'Tuple', default = '(8,6)'
Width and height of figure
resolution : 'Int', default = '300'
DPI resolution of figure.
showfig : 'Bool', default = 'True'
Whether to show figure.
filename : 'String', default = None.
Name of file/path to save the figure to.
Returns
-------
Plots the lines in 'data' with given error bars.
"""
assert isinstance(data_error, (list, tuple)), 'Input data needs to be in \
(data, error) pairs'
if colors is not None:
colors = itertools.cycle(colors)
else:
colors = itertools.cycle((COLORS["blue"],
COLORS["green"],
COLORS["red"],
COLORS["orange"],
COLORS["purple"],
COLORS["grey"],
COLORS["cyan"],
COLORS["teal"],
COLORS["lime"],
COLORS["brown"]))
if linestyles is None:
linestyles = itertools.cycle(('',))
elif linestyles == 'Automatic':
linestyles = itertools.cycle(def_linestyles)
else:
linestyles = itertools.cycle(linestyles)
if markers is None:
markers = itertools.cycle(('',))
elif markers == 'Automatic':
markers = itertools.cycle(def_markers)
else:
markers = itertools.cycle(markers)
if markeredge is not None:
mec, mew = markeredge
else:
mec = None
mew = None
fig = mplt.figure(figsize=figsize, dpi=resolution)
axis = fig.add_subplot(111)
for data, error in data_error:
x = data[:, 0]
x_error = error[:, 0]
if np.isnan(x_error).all():
x_error = None
y = data[:, 1]
y_error = error[:, 1]
if np.isnan(y_error).all():
y_error = None
axis.errorbar(x, y, xerr=x_error, yerr=y_error,
linewidth=linewidth, markersize=markersize,
marker=next(markers), color=next(colors),
linestyle=next(linestyles), mec=mec, mew=mew,
capsize=capsize, capthick=linewidth)
mpl.rcParams['font.sans-serif'] = font
mpl.rcParams['pdf.fonttype'] = 42
# update plot labels and format based on user input
for ax in ['top', 'bottom', 'left', 'right']:
axis.spines[ax].set_linewidth(borderwidth)
if xlabel is not None:
axis.set_xlabel(xlabel, fontsize=fontsize_axes)
if ylabel is not None:
axis.set_ylabel(ylabel, fontsize=fontsize_axes)
if xlim is not None:
axis.set_xlim(xlim)
if ylim is not None:
axis.set_ylim(ylim)
axis.tick_params(axis='both', labelsize=fontsize_other, width=ticksize[1],
length=ticksize[0])
if xticks is not None:
axis.set_xticks(xticks)
if xtick_labels is not None:
axis.set_xticklabels(xtick_labels)
if yticks is not None:
axis.set_yticks(yticks)
if ytick_labels is not None:
axis.set_yticklabels(ytick_labels)
if add_legend is not None:
mplt.legend(add_legend, prop={'size': 12}, loc=legend_location)
fig.tight_layout()
if filename is not None:
mplt.savefig(filename, dpi=resolution, transparent=True,
bbox_inches='tight')
if showfig:
mplt.show()
mplt.close()
def contour_plot(data, xlim=None, ylim=None, zlim=None, major_spacing=None,
minor_spacing=None, contour_width=1, contour_color='k',
opacity=1., colorbar_on=True, colorbar_location='right',
colorbar_label=None, colorbar_lines=True,
colorbar_ticks=None, colormap='jet', font='Arial',
fontsize_axes=18, fontsize_other=16, fontsize_colorbar=18,
axis_on=False, xlabel=None, ylabel=None, xticks=None,
yticks=None, ticksize=(8, 2), xtick_labels=None,
ytick_labels=None, borderwidth=2, figsize=6,
resolution=100, showfig=True, filename=None):
"""
Parameters
----------
data : 'ndarray', len(data) = 3, shape(data[i]) = (n,m)
Either a tuple or list of nx2 arrays or a single nx2 array.
xlim : 'tuple', len(xlim) == 2
Upper and lower limits for the x-axis.
ylim : 'tuple', len(ylim) == 2
Upper and lower limits for the y-axis.
zlim : 'tuple', len(ylim) == 2
Upper and lower limits for the z-data.
major_spacing : 'float'
Spacing between major contours.
minor_spacing : 'float'
Spacing between minor contours.
contour_width : 'int'
Width of contour lines
contour_color : 'string'
Color of contour lines
opacity : 'float'
Opacity of contour plot (0 = transparent)
colorbar_on : 'boole', default=True
Show colorbar.
colorbar_location : 'string'
Location of colorbar with respect to contour_plot
colorbar_label : 'string'
Label for colorbar.
colorbar_lines : 'boole'
Show contour lines on colorbar
colormap : 'string'
Colormap name
font : 'String'
Font to be used.
fontsize_axes : 'Int'
Font size to be used for axes labels.
fontsize_other : 'Int'
Font size to be used for all other text (legend, axis numbers, etc.).
fontsize_colorbar : 'Int'
Font size to be used for colorbar label.
axis_on : 'boole', default=false
Show axis.
xlabel : 'String'
Label for x-axis.
ylabel : 'String'
Label for y-axis.
xticks : 'ndarray'
List of ticks to use on the x-axis. Should be within the bounds set by
xlim.
yticks : 'ndarray'
List of ticks to use on the y-axis. Should be within the bound set by
ylim.
ticksize : 'ndarray', default '[8,2]'
Length and width of ticks.
xtick_labels : 'list'
List of custome xticks. Note len(xticks) == len(xtick_labels)
ytick_labels : 'list'
List of custome yticks. Note len(yticks) == len(ytick_labels)
boarderwidth : 'Int'
Linewidth of plot frame
figsize : 'Tuple', default = '(8,6)'
Width and height of figure
resolution : 'Int', default = '300'
DPI resolution of figure.
showfig : 'Bool', default = 'True'
Whether to show figure.
filename : 'String', default = None.
Name of file/path to save the figure to.
Returns
-------
Plot (x, y, z) arrays in 'data' as filled contours.
"""
assert len(data) == 3, 'Data must equal (x, y, data)'
x, y, z = data
z_m = ma.masked_invalid(z)
a_ratio = z.shape
a_ratio = a_ratio[1] / a_ratio[0]
if isinstance(figsize, (int, float)):
figsize = [figsize * a_ratio, figsize]
else:
figsize = max(figsize)
figsize = [figsize * a_ratio, figsize]
if colorbar_on:
if colorbar_location in ['top', 'bottom']:
figsize[1] += figsize[1] / 10
cbar_size = figsize[0] / 20
else:
figsize[0] += figsize[0] / 10
cbar_size = figsize[1] / 20
else:
cbar_size = max(figsize) / 20
if zlim is None:
zmin, zmax = np.nanmin(z), np.nanmax(z)
else:
zmin, zmax = zlim
if major_spacing is None:
major_spacing = (zmax - zmin) / 10
if minor_spacing is None:
minor_spacing = major_spacing / 10
cl_levels = np.arange(zmin, zmax + major_spacing, major_spacing)
cf_levels = np.arange(zmin, zmax + minor_spacing, minor_spacing)
if colorbar_ticks is None:
l_levels = cl_levels[::2]
else:
l_levels = (zmax - zmin) / colorbar_ticks
l_levels = np.arange(zmin, zmax + l_levels, l_levels)
orientation = 'vertical'
if colorbar_location in ['top', 'bottom']:
orientation = 'horizontal'
fig = mplt.figure(figsize=figsize, dpi=resolution)
axis = fig.add_subplot(111)
cf = mplt.contourf(x, y, z_m, alpha=opacity, levels=cf_levels,
extend='both', antialiased=True)
if contour_color is not None:
cl = mplt.contour(cf, levels=cl_levels, colors=(contour_color,),
linewidths=(contour_width,))
if colormap is not None:
cf.set_cmap(colormap)
mpl.rcParams['font.sans-serif'] = font
mpl.rcParams['pdf.fonttype'] = 42
mplt.axes().set_aspect('equal')
if xlim is not None:
axis.set_xlim(xlim)
if ylim is not None:
axis.set_ylim(ylim)
cbar_padding = 0.1
if axis_on:
for ax in ['top', 'bottom', 'left', 'right']:
axis.spines[ax].set_linewidth(borderwidth)
if xlabel is not None:
axis.set_xlabel(xlabel, fontsize=fontsize_axes)
if ylabel is not None:
axis.set_ylabel(ylabel, fontsize=fontsize_axes)