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Commit 97acf0ba authored by Somnath, Suhas's avatar Somnath, Suhas
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cleaned up visualizeSHOResults substantially and this method only uses... 

cleaned up visualizeSHOResults substantially and this method only uses plot_map_stack and plot_loops.
parent c97a3a8a
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pycroscopy/viz/plot_utils.py
View file @ 97acf0ba
......@@ -350,31 +350,6 @@ def plot_loops(excit_wfm, h5_loops, h5_pos=None, central_resp_size=None,
return fig, axes
def plotVSsnapshots(resp_mat, title='', stdevs=2, save_path=None):
"""
Plots the spatial distribution of the response at evenly spaced UDVS steps
Parameters
-------------
resp_mat : 3D numpy array
SHO responses arranged as [rows, cols, udvs_step]
title : (Optional) String
Super title for the plots - Preferably the group name
stdevs : (Optional) string
Number of standard deviations from the mean to be used to clip the color axis
save_path : (Optional) String
Absolute path to write the figure to
Returns
----------
None
"""
fig, axes = plot_map_stack(resp_mat, stdevs=stdevs, color_bar_mode="each", evenly_spaced=True,
title='UDVS Step #', heading=title, cmap=cmap_jet_white_center())
if save_path:
fig.savefig(save_path, format='png', dpi=300)
def plotSpectrograms(eigenvectors, num_comps=4, title='Eigenvectors', xlabel='Step', stdevs=2,
show_colorbar=True):
# TODO: use plot_map_stack instead of plotSpectrograms
......@@ -511,7 +486,6 @@ def plotBEeigenvectors(eigenvectors, num_comps=4, xlabel=''):
for index in range(num_comps):
cur_map = eigenvectors[index, :]
# axes = [axes201.flat[index], axes201.flat[index+num_comps], axes201.flat[index+2*num_comps], axes201.flat[index+3*num_comps]]
axes = [axes201.flat[index], axes201.flat[index + num_comps]]
for func, lab, ax in zip(funcs, labels, axes):
ax.plot(func(cur_map))
......@@ -568,14 +542,14 @@ def plotBELoops(xaxis, xlabel, amp_mat, phase_mat, num_comps, title=None):
###############################################################################
def plotScree(S, title='Scree'):
def plotScree(scree, title='Scree'):
"""
Plots the S or scree
Plots the scree or scree
Parameters:
-------------
S : 1D real numpy array
The S vector from SVD
scree : 1D real numpy array
The scree vector from SVD
Returns:
---------
......@@ -583,12 +557,12 @@ def plotScree(S, title='Scree'):
"""
fig203 = plt.figure(figsize=(6.5, 6))
axes203 = fig203.add_axes([0.1, 0.1, .8, .8]) # left, bottom, width, height (range 0 to 1)
axes203.loglog(np.arange(len(S)) + 1, S, 'b', marker='*')
axes203.loglog(np.arange(len(scree)) + 1, scree, 'b', marker='*')
axes203.set_xlabel('Principal Component')
axes203.set_ylabel('Variance')
axes203.set_title(title)
axes203.set_xlim(left=1, right=len(S))
axes203.set_ylim(bottom=np.min(S), top=np.max(S))
axes203.set_xlim(left=1, right=len(scree))
axes203.set_ylim(bottom=np.min(scree), top=np.max(scree))
fig203.canvas.set_window_title("Scree")
return fig203, axes203
......@@ -1173,37 +1147,6 @@ def plotHistgrams(p_hist, p_hbins, title, figure_path=None):
return fig
def plotSHOLoops(dc_vec, resp_mat, x_label='', y_label='', title=None, save_path=None):
"""
Plots BE loops from up to 9 positions (evenly separated)
Parameters
-----------
dc_vec : 1D numpy array
X axis - DC offset / AC amplitude
resp_mat : real 2D numpy array
containing quantity such as amplitude or phase organized as
[position, spectroscopic index]
x_label : (optional) String
X Label for all plots
y_label : (optional) String
Y label for all plots
title : (optional) String
Main plot title
save_path : (Optional) String
Absolute path to write the figure to
Returns
-----------
None
"""
fig, ax = plot_loops(dc_vec, resp_mat, evenly_spaced=True, plots_on_side=5, rainbow_plot=False,
x_label=x_label, y_label=y_label, subtitles='Loop', title=title)
if save_path:
fig.savefig(save_path, format='png', dpi=300)
def visualizeSHOResults(h5_main, save_plots=True, show_plots=True):
"""
Plots some loops, amplitude, phase maps for BE-Line and BEPS datasets.\n
......@@ -1222,6 +1165,22 @@ def visualizeSHOResults(h5_main, save_plots=True, show_plots=True):
-------
None
"""
def __plot_loops_maps(ac_vec, resp_mat, grp_name, win_title, spec_var_title, meas_var_title, save_plots,
folder_path, basename, num_rows, num_cols):
plt_title = grp_name + '_' + win_title + '_Loops'
fig, ax = plot_loops(ac_vec, resp_mat, evenly_spaced=True, plots_on_side=5, rainbow_plot=False,
x_label=spec_var_title, y_label=meas_var_title, subtitles='Loop', title=plt_title)
if save_plots:
fig.savefig(os.path.join(folder_path, basename + '_' + plt_title + '.png'), format='png', dpi=300)
plt_title = grp_name + '_' + win_title + '_Snaps'
fig, axes = plot_map_stack(resp_mat.reshape(num_rows, num_cols, resp_mat.shape[1]),
color_bar_mode="each", evenly_spaced=True, title='UDVS Step #',
heading=plt_title, cmap=cmap_jet_white_center())
if save_plots:
fig.savefig(os.path.join(folder_path, basename + '_' + plt_title + '.png'), format='png', dpi=300)
plt_path = None
print('Creating plots of SHO Results from {}.'.format(h5_main.name))
......@@ -1255,7 +1214,6 @@ def visualizeSHOResults(h5_main, save_plots=True, show_plots=True):
num_cols = len(np.unique(h5_pos[:, 1]))
try:
h5_spec_inds = h5_file[h5_main.attrs['Spectroscopic_Indices']]
h5_spec_vals = h5_file[h5_main.attrs['Spectroscopic_Values']]
# except KeyError:
# warn('No Spectrosocpic Datasets found as attribute of {}'.format(h5_main.name))
......@@ -1283,68 +1241,31 @@ def visualizeSHOResults(h5_main, save_plots=True, show_plots=True):
if meas_type == 'AC modulation mode with time reversal':
center = int(h5_spec_vals.shape[1] * 0.5)
ac_vec = np.squeeze(h5_spec_vals[h5_spec_vals.attrs['AC_Amplitude']][0:center])
forw_resp = np.squeeze(amp_mat[:, slice(0, center)])
plt_title = grp_name + '_Forward_Loops'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotSHOLoops(ac_vec, forw_resp, 'AC Amplitude', 'Amplitude', title=plt_title, save_path=plt_path)
rev_resp = np.squeeze(amp_mat[:, slice(center, None)])
plt_title = grp_name + '_Reverse_Loops'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotSHOLoops(ac_vec, rev_resp, 'AC Amplitude', 'Amplitude', title=plt_title, save_path=plt_path)
plt_title = grp_name + '_Forward_Snaps'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotVSsnapshots(forw_resp.reshape(num_rows, num_cols, forw_resp.shape[1]), title=plt_title,
save_path=plt_path)
plt_title = grp_name + '_Reverse_Snaps'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotVSsnapshots(rev_resp.reshape(num_rows, num_cols, rev_resp.shape[1]), title=plt_title,
save_path=plt_path)
for win_title, resp_mat in zip(['Forward', 'Reverse'], [forw_resp, rev_resp]):
__plot_loops_maps(ac_vec, resp_mat, grp_name, win_title, 'AC Amplitude', 'Amplitude', save_plots,
folder_path, basename, num_rows, num_cols)
else:
# plot loops at a few locations
dc_vec = np.squeeze(h5_spec_vals[h5_spec_vals.attrs['DC_Offset']])
if chan_grp.parent.attrs['VS_measure_in_field_loops'] == 'in and out-of-field':
dc_vec = np.squeeze(dc_vec[slice(0, None, 2)])
in_phase = np.squeeze(phase_mat[:, slice(0, None, 2)])
in_amp = np.squeeze(amp_mat[:, slice(0, None, 2)])
dc_vec = np.squeeze(dc_vec[slice(0, None, 2)])
plt_title = grp_name + '_In_Field_Loops'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotSHOLoops(dc_vec, in_phase * in_amp, 'DC Bias', 'Piezoresponse (a.u.)', title=plt_title,
save_path=plt_path)
out_phase = np.squeeze(phase_mat[:, slice(1, None, 2)])
out_amp = np.squeeze(amp_mat[:, slice(1, None, 2)])
plt_title = grp_name + '_Out_of_Field_Loops'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotSHOLoops(dc_vec, out_phase * out_amp, 'DC Bias', 'Piezoresponse (a.u.)', title=plt_title,
save_path=plt_path)
# print 'trying to reshape', in_phase.shape, 'into', in_phase.shape[0],',',num_rows,',',num_cols
plt_title = grp_name + '_In_Field_Snaps'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotVSsnapshots(in_phase.reshape(num_rows, num_cols, in_phase.shape[1]), title=plt_title,
save_path=plt_path)
plt_title = grp_name + '_Out_of_Field_Snaps'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotVSsnapshots(out_phase.reshape(num_rows, num_cols, out_phase.shape[1]), title=plt_title,
save_path=plt_path)
for win_title, resp_mat in zip(['In_Field', 'Out_of_Field'], [in_phase * in_amp, out_phase * out_amp]):
__plot_loops_maps(dc_vec, resp_mat, grp_name, win_title, 'DC Bias', 'Piezoresponse (a.u.)',
save_plots, folder_path, basename, num_rows, num_cols)
else:
plt_title = grp_name + '_Loops'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotSHOLoops(dc_vec, phase_mat * amp_mat, 'DC Bias', 'Piezoresponse (a.u.)', title=plt_title,
save_path=plt_path)
plt_title = grp_name + '_Snaps'
if save_plots:
plt_path = os.path.join(folder_path, basename + '_' + plt_title + '.png')
plotVSsnapshots(phase_mat.reshape(num_rows, num_cols, phase_mat.shape[1]), title=plt_title,
save_path=plt_path)
__plot_loops_maps(dc_vec, phase_mat * amp_mat, grp_name, '', 'DC Bias', 'Piezoresponse (a.u.)',
save_plots, folder_path, basename, num_rows, num_cols)
else: # BE-Line can only visualize the amplitude and phase maps:
amp_mat = amp_mat.reshape(num_rows, num_cols)
......
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