Commit c3eb76e0 authored by Chris Smith's avatar Chris Smith
Browse files

Small fix to map stack

Commented out imshow call
parent 2713a973
......@@ -12,7 +12,6 @@ import scipy
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
from mpl_toolkits.axes_grid1 import make_axes_locatable
from ..analysis.utils.be_loop import loopFitFunction
from ..io.hdf_utils import reshape_to_Ndims, get_formatted_labels
......@@ -79,6 +78,24 @@ def cmap_jet_white_center():
}
return LinearSegmentedColormap('white_jet', cdict)
def cmap_hot_desaturated():
hot_desaturated = [(1, (255, 76, 76, 255)),
(0.857, (107, 0, 0, 255)),
(0.714, (255, 96, 0, 255)),
(0.571, (255, 255, 0, 255)),
(0.429, (0, 127, 0, 255)),
(0.285, (0, 255, 255, 255)),
(0.143, (0, 0, 91, 255)),
(0, (71, 71, 219, 255))]
cdict = {'red': tuple([(dist, colors[0]/255.0, colors[0]/255.0) for (dist, colors) in hot_desaturated][::-1]),
'green': tuple([(dist, colors[1]/255.0, colors[1]/255.0) for (dist, colors) in hot_desaturated][::-1]),
'blue': tuple([(dist, colors[2]/255.0, colors[2]/255.0) for (dist, colors) in hot_desaturated][::-1])}
return LinearSegmentedColormap('hot_desaturated', cdict)
def discrete_cmap(num_bins, base_cmap=plt.cm.jet):
"""
Create an N-bin discrete colormap from the specified input map
......@@ -755,6 +772,10 @@ def plotClusterResults(label_mat, mean_response, spec_val=None, cmap=plt.cm.jet,
resp_label : str, optional
Label to use for Y axis on cluster centroid plot
Default = 'Response'
pos_labels : array_like of str, optional
Labels to use for the X and Y axes on the Label map
Default = ('X', 'Y')
pos_ticks : array_like of int
Returns
-------
......@@ -788,7 +809,6 @@ def plotClusterResults(label_mat, mean_response, spec_val=None, cmap=plt.cm.jet,
resp_label + ' - Phase', cmap)
plot_handles, plot_labels = ax_amp.get_legend_handles_labels()
else:
fig = plt.figure(figsize=(12, 8))
ax_map = plt.subplot2grid((1, 12), (0, 0), colspan=6)
......@@ -811,7 +831,7 @@ def plotClusterResults(label_mat, mean_response, spec_val=None, cmap=plt.cm.jet,
ny = len(np.unique(pos[:, 1]))
label_mat = label_mat[()].reshape(nx, ny)
im = ax_map.imshow(label_mat, interpolation='none')
# im = ax_map.imshow(label_mat, interpolation='none')
ax_map.set_xlabel(pos_labels[0])
ax_map.set_ylabel(pos_labels[1])
......
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