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Commit cfe2ed98 authored by Chris Smith's avatar Chris Smith
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plot_map_stack updates 

Corrected passing of kwargs to calls to figure, ImageGrid, and plot_map
parent 693e3bf7
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pycroscopy/viz/plot_utils.py
View file @ cfe2ed98
......@@ -4,13 +4,14 @@ Created on Thu May 05 13:29:12 2016
@author: Suhas Somnath
"""
# TODO: All general plotting functions should support data with 1 or 2 spatial dimensions.
# TODO: All general plotting functions should support data with 1, 2, or 3 spatial dimensions.
from __future__ import division # int/int = float
from warnings import warn
import os
import h5py
import scipy
import inspect
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from mpl_toolkits.axes_grid1 import ImageGrid
......@@ -336,7 +337,7 @@ def plot_line_family(axis, x_axis, line_family, line_names=None, label_prefix='L
color=cmap(int(255 * line_ind / (num_lines - 1))), **kwargs)
def plot_map(axis, data, stdevs=2, **kwargs):
def plot_map(axis, data, stdevs=2, origin='lower', **kwargs):
"""
Plots a 2d map with a tight z axis, with or without color bars.
Note that the direction of the y axis is flipped if the color bar is required
......@@ -349,13 +350,16 @@ def plot_map(axis, data, stdevs=2, **kwargs):
Data to be plotted
stdevs : unsigned int (Optional. Default = 2)
Number of standard deviations to consider for plotting
origin : str
Where should the origin of the image data be located. 'lower' sets the origin to the
bottom left, 'upper' sets it to the upper left.
Default 'lower'
Returns
-------
"""
data_mean = np.mean(data)
data_std = np.std(data)
origin = kwargs.pop('origin', 'lower')
im = axis.imshow(data, interpolation='none',
vmin=data_mean - stdevs * data_std,
vmax=data_mean + stdevs * data_std,
......@@ -616,7 +620,7 @@ def plotScree(scree, title='Scree'):
def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly_spaced=False,
title='Component', heading='Map Stack', fig_mult=(4, 4), **kwargs):
title='Component', heading='Map Stack', fig_mult=(4, 4), pad_mult=(0.1, 0.07), **kwargs):
"""
Plots the provided stack of maps
......@@ -639,6 +643,13 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
fig_mult : length 2 array_like of uints
Size multipliers for the figure. Figure size is calculated as (num_rows*`fig_mult[0]`, num_cols*`fig_mult[1]`).
Default (4, 4)
pad_mult : length 2 array_like of floats
Multipliers for the axis padding between plots in the stack. Padding is calculated as
(pad_mult[0]*fig_mult[1], pad_mult[1]*fig_mult[0]) for the width and height padding respectively.
Default (0.1, 0.07)
kwargs : dictionary
Keyword arguments to be passed to either matplotlib.pyplot.figure, mpl_toolkits.axes_grid1.ImageGrid, or
pycroscopy.vis.plot_utils.plot_map. See specific function documentation for the relavent options.
Returns:
---------
......@@ -647,7 +658,6 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
num_comps = abs(num_comps)
num_comps = min(num_comps, map_stack.shape[-1])
if evenly_spaced:
chosen_pos = np.linspace(0, map_stack.shape[-1] - 1, num_comps, dtype=int)
else:
......@@ -670,12 +680,38 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
p_cols = int(np.ceil(num_comps / p_rows))
if p_rows*p_cols < num_comps:
p_cols += 1
fig202 = plt.figure(figsize=(p_cols * fig_w, p_rows * fig_h))
pad_w, pad_h = pad_mult
'''
Set defaults for kwargs to the figure creation and extract any non-default values from current kwargs
'''
figkwargs = dict()
for key in inspect.getargspec(plt.figure).args:
if key in kwargs:
figkwargs.update({key: kwargs.pop(key)})
fig202 = plt.figure(figsize=(p_cols * fig_w, p_rows * fig_h), **figkwargs)
'''
Set defaults for kwargs to the ImageGrid and extract any non-default values from current kwargs
'''
igkwargs = {'cbar_pad': '1%',
'cbar_size': '5%',
'cbar_location': 'right',
'direction': 'row',
'add_all': True,
'share_all': False,
'aspect': True,
'label_mode': 'L'}
for key in igkwargs.iterkeys():
if key in kwargs:
igkwargs.update({key: kwargs.pop(key)})
axes202 = ImageGrid(fig202, 111, nrows_ncols=(p_rows, p_cols),
cbar_mode=color_bar_mode,
cbar_pad='1%',
cbar_size='5%',
axes_pad=(0.1*fig_w, 0.07*fig_h))
axes_pad=(pad_w*fig_w, pad_h*fig_h),
**igkwargs)
fig202.canvas.set_window_title(heading)
fig202.suptitle(heading, fontsize=16)
......@@ -695,24 +731,24 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
def plot_cluster_h5_group(h5_group, y_spec_label, centroids_together=True):
"""
Plots the cluster labels and mean response for each cluster
Plots the cluster labels and mean response for each cluster
Parameters
----------
h5_group : h5py.Datagroup object
H5 group containing the labels and mean response
y_spec_label : str
Label to use for Y axis on cluster centroid plot
centroids_together : Boolean, optional - default = True
Whether or nor to plot all centroids together on the same plot
Returns
-------
fig : Figure
Figure containing the plots
axes : 1D array_like of axes objects
Axes of the individual plots within `fig`
"""
Parameters
----------
h5_group : h5py.Datagroup object
H5 group containing the labels and mean response
y_spec_label : str
Label to use for Y axis on cluster centroid plot
centroids_together : Boolean, optional - default = True
Whether or nor to plot all centroids together on the same plot
Returns
-------
fig : Figure
Figure containing the plots
axes : 1D array_like of axes objects
Axes of the individual plots within `fig`
"""
# TODO: The quantity and units for the main dataset itself are missing in most cases!
h5_labels = h5_group['Labels']
try:
......
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