#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''contour_plot.py: Contains a basic contour plotting routine using matplotlib'''
#-----------------------------------------------------------------------------
# Boilerplate
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
import matplotlib.pyplot as plt
import numpy as np
from . set_style import set_plot_style
from .. pygeostat_parameters import Parameters
[docs]
@set_plot_style
def contour_plot(data, griddef=None, var=None, orient='xy', slice_number=0, ax=None, output_file=None, c='k',
figsize=None, xlabel=None, ylabel=None, title=None, unit=None, leg_label=None,
aspect=None, clabel=False, lw=1.0, plot_style=None, custom_style=None, axis_xy=None, grid=None, return_ax=True, return_csi=False):
"""
Contains a basic contour plotting routine using matplotlib
Parameters:
data: A numpy ndarray, pandas DataFrame or pygeostat DataFile, where each column is a
variable and each row is an observation
griddef (GridDef): A pygeostat GridDef class, which must be provided if a DataFile is
not passed as data with a valid internal
GridDef :class:`gs.GridDef <pygeostat.data.grid_definition.GridDef>`
var (str,int): The name of the column within data to plot. If an int is provided, then it
corresponds with the column number in data. If None, the first column of data
is used.
orient (str): Orientation to slice data. ``'xy'``, ``'xz'``, ``'yz'`` are the only accepted
values
slice_number (int): Grid cell location along the axis not plotted to take the slice of data to
plot
ax (mpl.axis): Matplotlib axis to plot the figure
output_file (str): Output figure file name and location
show (bool): ``True`` will use plt.show() at end. Typically don't need this.
c (str): Matplotlib color
figsize (tuple): Figure size (width, height)
xlabel (str): X-axis label
ylabel (str): Y-axis label
title (str): title for the plot
unit (str): Distance unit, taken from Parameters if ``None``
leg_label (str): Adds a single label to the legend for the contour lines
aspect (str): Set a permissible aspect ratio of the image to pass to matplotlib.
clabel (bool): Whether or not to label the contours wth their values
lw (float): the weight of the contour lines
plot_style (str): Optional pygeostat plotting style
custom_style (dict): Custom dictionary for plotting styles
grid (bool): Plots the major grid lines if True. Based on Parameters['plotting.grid']
if None.
axis_xy (bool): converts the axis to GSLIB-style axis visibility (only left and bottom
visible) if axis_xy is True. Based on Parameters['plotting.axis_xy'] if None.
return_ax (bool): specify if the plotting axis should be returned
return_csi (bool): specify if the contour instance should be returned
Returns:
csi (ax): Matplotlib ax.contour instance
**Examples:**
A basic contour plotting example:
.. plot::
import pygeostat as gs
grid_str = '''120 5.00 10.00 -nx, xmn, xsiz
110 1205.00 10.00 -ny, ymn, ysiz
1 0.5 1.0 -nz, zmn, zsiz'''
griddef = gs.GridDef(grid_str=grid_str)
data_fl = gs.ExampleData("grid2d_surf", griddef=griddef)
gs.contour_plot(data_fl, var="Thickness", clabel=True)
Contour plot on top of slice plot:
.. plot::
import pygeostat as gs
grid_str = '''120 5.00 10.00 -nx, xmn, xsiz
110 1205.00 10.00 -ny, ymn, ysiz
1 0.5 1.0 -nz, zmn, zsiz'''
griddef = gs.GridDef(grid_str=grid_str)
data_fl = gs.ExampleData("grid2d_surf", griddef=griddef)
ax = gs.slice_plot(data_fl, var="Thickness")
_ = gs.contour_plot(data_fl, var="Thickness", ax = ax, clabel=True)
"""
from . utils import format_plot, _spatial_griddata, _spatial_labels, _spatial_aspect
from .export_image import export_image
from ..datautils.utils import slice_grid
# Parse the data, var and griddef input to determine the data and griddef
data, griddef = _spatial_griddata(data, var, griddef)
# Slice the data
if orient in ['xy', 'xz', 'yz']:
view = slice_grid(data, griddef, orient, slice_number)
else:
raise Exception("Error: no orientation set! {}".format(orient))
a = orient[0]
b = orient[1]
xmin = getattr(griddef, a + 'limits')[0]
xmax = getattr(griddef, a + 'limits')[1]
ymin = getattr(griddef, b + 'limits')[0]
ymax = getattr(griddef, b + 'limits')[1]
if aspect is None:
aspect = _spatial_aspect([xmin, xmax], [ymin, ymax])
# Discretize for contour map
X = np.linspace(xmin, xmax, len(view[0, :]))
Y = np.linspace(ymin, ymax, len(view[:, 0]))
if ax is None:
_, ax = plt.subplots(1, 1, figsize=figsize)
# Create the 'artists' that draw the contours
csi = ax.contour(X, Y, np.reshape(view, (len(view[:, 0]), len(view[0, :]))), linewidths=lw,
colors=c)
if leg_label is not None:
ax.plot(np.nan, lw=lw, color=c, label=leg_label)
if clabel:
ax.clabel(csi, inline=1, fontsize=9, fmt='%.0f')
if aspect:
ax.set_aspect(aspect)
_spatial_labels(ax, orient, griddef, slice_number, title, xlabel, ylabel, unit)
if axis_xy is None:
axis_xy = Parameters['plotting.axis_xy_spatial']
format_plot(ax, axis_xy=axis_xy, grid=grid)
# Done Plotting, save figure if required and show it
if output_file is not None:
export_image(output_file)
# return some things
if return_ax and return_csi:
return ax, csi
elif return_ax:
return ax
elif return_csi:
return csi
