Commit e0ccd48e authored by Chris Smith's avatar Chris Smith
Browse files

Fixed circular import and removed useless GetGoodLims function

parent a21c7421
......@@ -70,24 +70,24 @@ def plotLoops(dc_vec, resp_mat, x_label='', y_label='', title=None, save_path=No
fig.savefig(save_path, format='png', dpi=300)
def getGoodLims(resp_mat):
'''
Returns the mean and standard deviation of the provided numpy array
Parameters
------------
resp_mat : numpy ndarray
N dimensional array containing homogenous data
Returns
---------
mean: float
Mean of the complete dataset
std: float
Standard deviation of the dataset
'''
return np.mean(resp_mat), np.std(resp_mat)
# def getGoodLims(resp_mat):
# '''
# Returns the mean and standard deviation of the provided numpy array
#
# Parameters
# ------------
# resp_mat : numpy ndarray
# N dimensional array containing homogenous data
#
# Returns
# ---------
# mean: float
# Mean of the complete dataset
# std: float
# Standard deviation of the dataset
# '''
# return np.mean(resp_mat), np.std(resp_mat)
#
#%%
......
......@@ -12,7 +12,6 @@ from scipy.cluster.hierarchy import linkage, dendrogram
from scipy.spatial.distance import pdist
from warnings import warn
from mpl_toolkits.axes_grid1 import make_axes_locatable
from ..analysis.be_sho_utils import getGoodLims
###############################################################################
......@@ -153,7 +152,8 @@ def plotSHOMaps(sho_maps, map_names, stdevs=2, title='', save_path=None):
fig,axes=plt.subplots(ncols=3, nrows=2, sharex=True, figsize=(15, 10))
for index, ax_hand, data_mat, qty_name in zip(range(len(map_names)), axes.flat, sho_maps, map_names):
(amp_mean, amp_std) = getGoodLims(data_mat)
amp_mean = np.mean(data_mat)
amp_std = np.std(data_mat)
pcol0 = ax_hand.pcolor(data_mat, vmin=amp_mean-stdevs*amp_std,
vmax=amp_mean+stdevs*amp_std)
......@@ -208,7 +208,8 @@ def plotVSsnapshots(resp_mat, title='', stdevs=2, save_path=None):
for count, posn in enumerate(xrange(0,num_udvs, delta_pos)):
snapshot = np.squeeze(resp_mat[:,:,posn])
(amp_mean, amp_std) = getGoodLims(snapshot)
amp_mean = np.mean(snapshot)
amp_std = np.std(snapshot)
ndims = len(snapshot.shape)
if ndims == 2:
axes_lin[count].imshow(snapshot, vmin=amp_mean-stdevs*amp_std, vmax=amp_mean+stdevs*amp_std)
......@@ -262,7 +263,8 @@ def plotSpectrograms(eigenvectors, num_comps=4, title='Eigenvectors', xlabel='St
for index in xrange(num_comps):
cur_map = np.transpose(eigenvectors[index, :, :])
ax = axes201.flat[index]
(mean, std) = getGoodLims(cur_map)
mean = np.mean(cur_map)
std = np.std(cur_map)
ax.imshow(cur_map, cmap='jet',
vmin=mean - stdevs * std,
vmax=mean + stdevs * std)
......@@ -311,7 +313,8 @@ def plotBEspectrograms(eigenvectors, num_comps=4, title='Eigenvectors', xlabel='
funcs = [np.abs, np.angle]
labels = ['Amplitude', 'Phase']
for func, lab, ax in zip(funcs, labels, axes):
(amp_mean, amp_std) = getGoodLims(func(cur_map))
amp_mean = np.mean(func(cur_map))
amp_std = np.std(func(cur_map))
ax.imshow(func(cur_map), cmap='inferno',
vmin=amp_mean - stdevs * amp_std,
vmax=amp_mean + stdevs * amp_std)
......@@ -473,7 +476,8 @@ def plotLoadingMaps(loadings, num_comps=4, stdevs=2, colormap='jet', show_colorb
for index in xrange(num_comps):
cur_map = loadings[:, :, index]
(amp_mean, amp_std) = getGoodLims(cur_map)
amp_mean = np.mean(cur_map)
amp_std = np.std(cur_map)
if show_colorbar:
pcol0 = axes202.flat[index].pcolor(cur_map, vmin=amp_mean - stdevs * amp_std,
vmax=amp_mean + stdevs * amp_std)
......
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