def histograms(modelLogger):
if not cc.cfg['plots']['histograms']:
return
if not os.path.exists(cc.cfg['plots']['histograms_dir']):
os.makedirs(cc.cfg['plots']['histograms_dir'])
cntEpochs = len(modelLogger.epochLogs)
cntLayers = len(modelLogger.epochLogs[-1]['weights'])
logVals = [
{'name':'weights','color':'blue'},
{'name':'updates','color':'red'},
{'name':'ratios','color':'green'}
]
subplotRows = len(logVals)
subplotCols = cntLayers
for x in range(cntEpochs):
subplotIdx = 1
plt.figure(figsize=(5*subplotCols,5*subplotRows))
plt.suptitle('Histograms per layer, epoch {}/{}'.format(x,cntEpochs-1), fontsize=14)
for logVal in logVals:
for i,layer in enumerate(modelLogger.epochLogs[x][logVal['name']]):
histmin = layer.min()
histmax = layer.max()
plt.subplot(subplotRows, subplotCols, subplotIdx)
plt.title('{}, {}'.format(modelLogger.model.layers[modelLogger.loggedLayers[i]].name,logVal['name']))
plt.hist(layer, range = (histmin, histmax), bins = 30, color = logVal['color'])
subplotIdx+=1
plt.tight_layout()
plt.subplots_adjust(top=0.9)
plt.savefig('{}/hist_{e:03d}.png'.format(cc.cfg['plots']['histograms_dir'], e = x))
plt.close()
def plot_multiple_streams(self, fig, ax, datasets, colors, axis_font={}, title_font={},
tick_font={}, width_in=8.3 , plot_qaqc=0, scatter=False, **kwargs):
# Plot a timeseries with multiple y-axes using multiple streams from uFrame
#
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
#
# http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html
if not axis_font:
axis_font = axis_font_default
if not title_font:
title_font = title_font_default
n_vars = len(datasets)
if n_vars > 6:
raise Exception('This code currently handles a maximum of 6 independent variables.')
elif n_vars < 2:
raise Exception('This code currently handles a minimum of 2 independent variables.')
if scatter:
kwargs['marker'] = 'o'
# Generate the plot.
# Use twinx() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
y_axis = n_vars * [0]
y_axis[0] = ax
for i in range(1, n_vars):
y_axis[i] = ax.twinx()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(y_axis[1])
self.set_spine_direction(y_axis[1], "top")
# Define the axes position offsets for each 'extra' axis
spine_directions = ["left", "right", "left", "right", "left", "right"]
# Adjust the axes left/right accordingly
if n_vars >= 4:
if width_in < 8.3:
# set axis location
offset = [1.2, -0.2, 1.40, -0.40]
# overwrite width
l_mod = 0.3
r_mod = 0.8
else:
offset = [1.10, -0.10, 1.20, -0.20]
l_mod = 0.5
r_mod = 1.2
plt.subplots_adjust(left=l_mod, right=r_mod)
elif n_vars == 3:
offset = [1.20, -0.20, 1.40, -0.40]
plt.subplots_adjust(left=0.0, right=0.7)
count = 0
for i in range(2, n_vars):
y_axis[i].spines[spine_directions[count+1]].set_position(("axes", offset[count]))
self.make_patch_spines_invisible(y_axis[i])
self.set_spine_direction(y_axis[i], spine_directions[count+1])
count += 1
# Plot the data
legend_handles = []
legend_labels = []
for ind, data in enumerate(datasets):
xlabel = data['x_field'][0]
ylabel = data['y_field'][0]
xdata = data['x'][xlabel]
ydata = data['y'][ylabel]
# Handle the QAQC data
qaqc = data['qaqc'][ylabel]
if plot_qaqc >= 10:
# Plot all of the qaqc flags results
# qaqc_data = data['qaqc'][ylabel]
pass
elif plot_qaqc >= 1:
# This is a case where the user wants to plot just one of the 9 QAQC tests
ind = np.where(qaqc != plot_qaqc)
qaqc[ind] = 0
else:
qaqc = []
h, = y_axis[ind].plot(xdata, ydata, colors[ind], label=data['title'], **kwargs)
if len(qaqc) > 0:
bad_data = np.where(qaqc > 0)
y_axis[ind].plot(xdata[bad_data], ydata[bad_data],
marker='o',
mfc='none',
linestyle='None',
markersize=6,
markeredgewidth=2,
mec='r')
# Label the y-axis and set text color:
# Been experimenting with other ways to handle tick labels with spines
y_axis[ind].yaxis.get_major_formatter().set_useOffset(False)
y_axis[ind].set_ylabel(ylabel.replace("_", " "), labelpad=10, **axis_font)
y_axis[ind].yaxis.label.set_color(colors[ind])
y_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
if tick_font:
labelsize = tick_font['labelsize']
y_axis[ind].tick_params(axis='y', labelsize=labelsize, colors=colors[ind])
legend_handles.append(h)
legend_labels.append(data['title'][0:20])
self.get_time_label(ax, xdata)
fig.autofmt_xdate()
ax.legend(legend_handles, legend_labels)
# ax.tick_params(axis='x', labelsize=10)
# ax.set_title(title.replace("_", " "), y=1.05, **title_font)
ax.grid(True)
plt.tight_layout()
def plot_multiple_yaxes(self, fig, ax, xdata, ydata, colors, title, units=[], scatter=False,
axis_font={}, title_font={}, tick_font={}, width_in=8.3, qaqc={}, **kwargs):
# Plot a timeseries with multiple y-axes
#
# ydata is a python dictionary of all the data to plot. Key values are used as plot labels
#
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
#
# http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html
if not axis_font:
axis_font = axis_font_default
if not title_font:
title_font = title_font_default
n_vars = len(ydata)
if n_vars > 6:
raise Exception('This code currently handles a maximum of 6 independent variables.')
elif n_vars < 2:
raise Exception('This code currently handles a minimum of 2 independent variables.')
if scatter:
kwargs['marker'] = 'o'
# Generate the plot.
# Use twinx() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
y_axis = n_vars * [0]
y_axis[0] = ax
for i in range(1, n_vars):
y_axis[i] = ax.twinx()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(y_axis[1])
self.set_spine_direction(y_axis[1], "top")
# Define the axes position offsets for each 'extra' axis
spine_directions = ["left", "right", "left", "right", "left", "right"]
# Adjust the axes left/right accordingly
if n_vars >= 4:
if width_in < 8.3:
# set axis location
offset = [1.2, -0.2, 1.40, -0.40]
# overwrite width
l_mod = 0.3
r_mod = 0.8
else:
offset = [1.10, -0.10, 1.20, -0.20]
l_mod = 0.5
r_mod = 1.2
plt.subplots_adjust(left=l_mod, right=r_mod)
elif n_vars == 3:
offset = [1.20, -0.20, 1.40, -0.40]
plt.subplots_adjust(left=0.0, right=0.7)
count = 0
for i in range(2, n_vars):
y_axis[i].spines[spine_directions[count+1]].set_position(("axes", offset[count]))
self.make_patch_spines_invisible(y_axis[i])
self.set_spine_direction(y_axis[i], spine_directions[count+1])
count += 1
# Plot the data
for ind, key in enumerate(ydata):
y_axis[ind].plot(xdata[key], ydata[key], colors[ind], **kwargs)
if len(qaqc[key]) > 0:
bad_data = np.where(qaqc[key] > 0)
y_axis[ind].plot(xdata[key][bad_data], ydata[key][bad_data],
marker='o',
mfc='none',
linestyle='None',
markersize=6,
markeredgewidth=2,
mec='r')
# Label the y-axis and set text color:
# Been experimenting with other ways to handle tick labels with spines
y_axis[ind].yaxis.get_major_formatter().set_useOffset(False)
y_axis[ind].set_ylabel(key.replace("_", " ") + ' (' + units[ind] + ')', labelpad=10, **axis_font)
y_axis[ind].yaxis.label.set_color(colors[ind])
y_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
if tick_font:
labelsize = tick_font['labelsize']
y_axis[ind].tick_params(axis='y', labelsize=labelsize, colors=colors[ind])
self.get_time_label(ax, xdata['time'])
fig.autofmt_xdate()
# ax.tick_params(axis='x', labelsize=10)
ax.set_title(title.replace("_", " "), y=1.05, **title_font)
ax.grid(True)
plt.tight_layout()
def plot_multiple_xaxes(self, ax, xdata, ydata, colors, ylabel='Depth (m)', title='', title_font={},
axis_font={}, tick_font={}, width_in=8.3, **kwargs):
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
n_vars = len(xdata)
if n_vars > 6:
raise Exception('This code currently handles a maximum of 6 independent variables.')
elif n_vars < 2:
raise Exception('This code currently handles a minimum of 2 independent variables.')
# Generate the plot.
# Use twiny() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
x_axis = n_vars * [0]
x_axis[0] = ax
for i in range(1, n_vars):
x_axis[i] = ax.twiny()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(x_axis[1])
self.set_spine_direction(x_axis[1], "top")
offset = [1.10, -0.1, -0.20, 1.20]
spine_directions = ["top", "bottom", "bottom", "top", "top", "bottom"]
count = 0
for i in range(2, n_vars):
x_axis[i].spines[spine_directions[count]].set_position(("axes", offset[count]))
self.make_patch_spines_invisible(x_axis[i])
self.set_spine_direction(x_axis[i], spine_directions[count])
count += 1
# Adjust the axes left/right accordingly
if n_vars >= 4:
plt.subplots_adjust(bottom=0.2, top=0.8)
elif n_vars == 3:
plt.subplots_adjust(bottom=0.0, top=0.8)
# Label the y-axis:
ax.set_ylabel(ylabel, **axis_font)
for ind, key in enumerate(xdata):
x_axis[ind].plot(xdata[key], ydata, colors[ind], **kwargs)
# Label the x-axis and set text color:
x_axis[ind].set_xlabel(key.replace("_", " "), **axis_font)
x_axis[ind].xaxis.label.set_color(colors[ind])
x_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
for obj in x_axis[ind].xaxis.get_ticklines():
# `obj` is a matplotlib.lines.Line2D instance
obj.set_color(colors[ind])
obj.set_markeredgewidth(2)
for obj in x_axis[ind].xaxis.get_ticklabels():
obj.set_color(colors[ind])
ax.invert_yaxis()
ax.grid(True)
if tick_font:
ax.tick_params(**tick_font)
ax.set_title(title.replace("_", " "), y=1.23, **title_font)
plt.tight_layout()
def plot_multiple_streams(self,
fig,
ax,
datasets,
colors,
axis_font={},
title_font={},
tick_font={},
width_in=8.3,
plot_qaqc=0,
scatter=False,
**kwargs):
# Plot a timeseries with multiple y-axes using multiple streams from uFrame
#
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
#
# http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html
if not axis_font:
axis_font = axis_font_default
if not title_font:
title_font = title_font_default
n_vars = len(datasets)
if n_vars > 6:
raise Exception(
'This code currently handles a maximum of 6 independent variables.'
)
elif n_vars < 2:
raise Exception(
'This code currently handles a minimum of 2 independent variables.'
)
if scatter:
kwargs['marker'] = 'o'
# Generate the plot.
# Use twinx() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
y_axis = n_vars * [0]
y_axis[0] = ax
for i in range(1, n_vars):
y_axis[i] = ax.twinx()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(y_axis[1])
self.set_spine_direction(y_axis[1], "top")
# Define the axes position offsets for each 'extra' axis
spine_directions = ["left", "right", "left", "right", "left", "right"]
# Adjust the axes left/right accordingly
if n_vars >= 4:
if width_in < 8.3:
# set axis location
offset = [1.2, -0.2, 1.40, -0.40]
# overwrite width
l_mod = 0.3
r_mod = 0.8
else:
offset = [1.10, -0.10, 1.20, -0.20]
l_mod = 0.5
r_mod = 1.2
plt.subplots_adjust(left=l_mod, right=r_mod)
elif n_vars == 3:
offset = [1.20, -0.20, 1.40, -0.40]
plt.subplots_adjust(left=0.0, right=0.7)
count = 0
for i in range(2, n_vars):
y_axis[i].spines[spine_directions[count + 1]].set_position(
("axes", offset[count]))
self.make_patch_spines_invisible(y_axis[i])
self.set_spine_direction(y_axis[i], spine_directions[count + 1])
count += 1
# Plot the data
legend_handles = []
legend_labels = []
for ind, data in enumerate(datasets):
xlabel = data['x_field'][0]
ylabel = data['y_field'][0]
xdata = data['x'][xlabel]
ydata = data['y'][ylabel]
# Handle the QAQC data
qaqc = data['qaqc'][ylabel]
if plot_qaqc >= 10:
# Plot all of the qaqc flags results
# qaqc_data = data['qaqc'][ylabel]
pass
elif plot_qaqc >= 1:
# This is a case where the user wants to plot just one of the 9 QAQC tests
ind = np.where(qaqc != plot_qaqc)
qaqc[ind] = 0
else:
qaqc = []
h, = y_axis[ind].plot(xdata,
ydata,
colors[ind],
label=data['title'],
**kwargs)
if len(qaqc) > 0:
bad_data = np.where(qaqc > 0)
y_axis[ind].plot(xdata[bad_data],
ydata[bad_data],
marker='o',
mfc='none',
linestyle='None',
markersize=6,
markeredgewidth=2,
mec='r')
# Label the y-axis and set text color:
# Been experimenting with other ways to handle tick labels with spines
y_axis[ind].yaxis.get_major_formatter().set_useOffset(False)
y_axis[ind].set_ylabel(ylabel.replace("_", " "),
labelpad=10,
**axis_font)
y_axis[ind].yaxis.label.set_color(colors[ind])
y_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
if tick_font:
labelsize = tick_font['labelsize']
y_axis[ind].tick_params(axis='y',
labelsize=labelsize,
colors=colors[ind])
legend_handles.append(h)
legend_labels.append(data['title'][0:20])
self.get_time_label(ax, xdata)
fig.autofmt_xdate()
ax.legend(legend_handles, legend_labels)
# ax.tick_params(axis='x', labelsize=10)
# ax.set_title(title.replace("_", " "), y=1.05, **title_font)
ax.grid(True)
plt.tight_layout()
def plot_multiple_yaxes(self,
fig,
ax,
xdata,
ydata,
colors,
title,
units=[],
scatter=False,
axis_font={},
title_font={},
tick_font={},
width_in=8.3,
qaqc={},
**kwargs):
# Plot a timeseries with multiple y-axes
#
# ydata is a python dictionary of all the data to plot. Key values are used as plot labels
#
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
#
# http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html
if not axis_font:
axis_font = axis_font_default
if not title_font:
title_font = title_font_default
n_vars = len(ydata)
if n_vars > 6:
raise Exception(
'This code currently handles a maximum of 6 independent variables.'
)
elif n_vars < 2:
raise Exception(
'This code currently handles a minimum of 2 independent variables.'
)
if scatter:
kwargs['marker'] = 'o'
# Generate the plot.
# Use twinx() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
y_axis = n_vars * [0]
y_axis[0] = ax
for i in range(1, n_vars):
y_axis[i] = ax.twinx()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(y_axis[1])
self.set_spine_direction(y_axis[1], "top")
# Define the axes position offsets for each 'extra' axis
spine_directions = ["left", "right", "left", "right", "left", "right"]
# Adjust the axes left/right accordingly
if n_vars >= 4:
if width_in < 8.3:
# set axis location
offset = [1.2, -0.2, 1.40, -0.40]
# overwrite width
l_mod = 0.3
r_mod = 0.8
else:
offset = [1.10, -0.10, 1.20, -0.20]
l_mod = 0.5
r_mod = 1.2
plt.subplots_adjust(left=l_mod, right=r_mod)
elif n_vars == 3:
offset = [1.20, -0.20, 1.40, -0.40]
plt.subplots_adjust(left=0.0, right=0.7)
count = 0
for i in range(2, n_vars):
y_axis[i].spines[spine_directions[count + 1]].set_position(
("axes", offset[count]))
self.make_patch_spines_invisible(y_axis[i])
self.set_spine_direction(y_axis[i], spine_directions[count + 1])
count += 1
# Plot the data
for ind, key in enumerate(ydata):
y_axis[ind].plot(xdata[key], ydata[key], colors[ind], **kwargs)
if len(qaqc[key]) > 0:
bad_data = np.where(qaqc[key] > 0)
y_axis[ind].plot(xdata[key][bad_data],
ydata[key][bad_data],
marker='o',
mfc='none',
linestyle='None',
markersize=6,
markeredgewidth=2,
mec='r')
# Label the y-axis and set text color:
# Been experimenting with other ways to handle tick labels with spines
y_axis[ind].yaxis.get_major_formatter().set_useOffset(False)
y_axis[ind].set_ylabel(key.replace("_", " ") + ' (' + units[ind] +
')',
labelpad=10,
**axis_font)
y_axis[ind].yaxis.label.set_color(colors[ind])
y_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
if tick_font:
labelsize = tick_font['labelsize']
y_axis[ind].tick_params(axis='y',
labelsize=labelsize,
colors=colors[ind])
self.get_time_label(ax, xdata['time'])
fig.autofmt_xdate()
# ax.tick_params(axis='x', labelsize=10)
ax.set_title(title.replace("_", " "), y=1.05, **title_font)
ax.grid(True)
plt.tight_layout()
def plot_multiple_xaxes(self,
ax,
xdata,
ydata,
colors,
ylabel='Depth (m)',
title='',
title_font={},
axis_font={},
tick_font={},
width_in=8.3,
**kwargs):
# Acknowledgment: This function is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
n_vars = len(xdata)
if n_vars > 6:
raise Exception(
'This code currently handles a maximum of 6 independent variables.'
)
elif n_vars < 2:
raise Exception(
'This code currently handles a minimum of 2 independent variables.'
)
# Generate the plot.
# Use twiny() to create extra axes for all dependent variables except the first
# (we get the first as part of the ax axes).
x_axis = n_vars * [0]
x_axis[0] = ax
for i in range(1, n_vars):
x_axis[i] = ax.twiny()
ax.spines["top"].set_visible(False)
self.make_patch_spines_invisible(x_axis[1])
self.set_spine_direction(x_axis[1], "top")
offset = [1.10, -0.1, -0.20, 1.20]
spine_directions = ["top", "bottom", "bottom", "top", "top", "bottom"]
count = 0
for i in range(2, n_vars):
x_axis[i].spines[spine_directions[count]].set_position(
("axes", offset[count]))
self.make_patch_spines_invisible(x_axis[i])
self.set_spine_direction(x_axis[i], spine_directions[count])
count += 1
# Adjust the axes left/right accordingly
if n_vars >= 4:
plt.subplots_adjust(bottom=0.2, top=0.8)
elif n_vars == 3:
plt.subplots_adjust(bottom=0.0, top=0.8)
# Label the y-axis:
ax.set_ylabel(ylabel, **axis_font)
for ind, key in enumerate(xdata):
x_axis[ind].plot(xdata[key], ydata, colors[ind], **kwargs)
# Label the x-axis and set text color:
x_axis[ind].set_xlabel(key.replace("_", " "), **axis_font)
x_axis[ind].xaxis.label.set_color(colors[ind])
x_axis[ind].spines[spine_directions[ind]].set_color(colors[ind])
for obj in x_axis[ind].xaxis.get_ticklines():
# `obj` is a matplotlib.lines.Line2D instance
obj.set_color(colors[ind])
obj.set_markeredgewidth(2)
for obj in x_axis[ind].xaxis.get_ticklabels():
obj.set_color(colors[ind])
ax.invert_yaxis()
ax.grid(True)
if tick_font:
ax.tick_params(**tick_font)
ax.set_title(title.replace("_", " "), y=1.23, **title_font)
plt.tight_layout()