def plot_regressors_as_RGB(self, fig1, gs, regressors, rsq, b, colors, brightness_scale=3):
b_pos = b * (b > 0) # Get positive beta values
# Set up colorize function
c = Colorize(cmap="indexed", scale=brightness_scale, flag_scale=1)
for ii in xrange(0, len(regressors)):
ax1 = fig1.add_subplot(gs[0, ii])
c.colors = [colors[ii]]
img = c.transform([b_pos[ii, :, :]], mask=rsq, background=self.reference, mixing=0.5)
self.image(img)
# Plot the unique stimuli in subplots
subplot_count = 0
for ii in self.unique_stimuli:
b_pos_list = []
color_mat = []
for keys in regressors.iterkeys():
if ii in keys:
index = regressors.keys().index(keys)
b_pos_list.append(b_pos[index, :, :])
color_mat.append(colors[index])
ax1 = fig1.add_subplot(gs[1, subplot_count])
c.colors = color_mat
img = c.transform(b_pos_list, mask=rsq, background=self.reference, mixing=0.5)
self.image(img)
subplot_count += 1
# Plot the different stimuli parameters in subplots
for ii in self.parameters:
b_pos_list = []
color_mat = []
for keys in regressors.iterkeys():
if ii in keys:
index = regressors.keys().index(keys)
b_pos_list.append(b_pos[index, :, :])
color_mat.append(colors[index])
ax1 = fig1.add_subplot(gs[1, subplot_count])
c.colors = color_mat
img = c.transform(b_pos_list, mask=rsq, background=self.reference, mixing=0.5)
self.image(img)
subplot_count += 1
# Plot all together
b_pos_list = []
color_mat = []
for ii in xrange(0, len(regressors)):
b_pos_list.append(b_pos[ii, :, :])
color_mat.append(colors[ii])
ax1 = fig1.add_subplot(gs[2:4, 1:3])
c.colors = color_mat
img = c.transform(b_pos_list, mask=rsq, background=self.reference, mixing=0.5)
self.image(img)
subplot_count += 1
ax1 = fig1.add_subplot(gs[2, 0])
self.create_colorbar(ax1, regressors, colors)
def plot_all_together_inseperateplot(self,
fig1,
gs,
regressors,
rsq,
b,
colors,
brightness_scale=3,
gridspecs='[0, 0]'):
b_pos = b * (b > 0) # Get positive beta values
# Set up colorize function
c = Colorize(cmap='indexed', scale=brightness_scale, flag_scale=1)
b_pos_list = []
color_mat = []
for ii in xrange(0, len(regressors)):
b_pos_list.append(b_pos[ii, :, :])
color_mat.append(colors[ii])
ax1 = eval('fig1.add_subplot(gs' + gridspecs + ')')
c.colors = color_mat
img = c.transform(b_pos_list,
mask=rsq,
background=self.reference,
mixing=0.5)
self.image(img)
def plot_all_together_inseperateplot(
self, fig1, gs, regressors, rsq, b, colors, brightness_scale=3, gridspecs="[0, 0]"
):
b_pos = b * (b > 0) # Get positive beta values
# Set up colorize function
c = Colorize(cmap="indexed", scale=brightness_scale, flag_scale=1)
b_pos_list = []
color_mat = []
for ii in xrange(0, len(regressors)):
b_pos_list.append(b_pos[ii, :, :])
color_mat.append(colors[ii])
ax1 = eval("fig1.add_subplot(gs" + gridspecs + ")")
c.colors = color_mat
img = c.transform(b_pos_list, mask=rsq, background=self.reference, mixing=0.5)
self.image(img)
def plot_regressors_as_RGB(self,
fig1,
gs,
regressors,
rsq,
b,
colors,
brightness_scale=3):
b_pos = b * (b > 0) # Get positive beta values
# Set up colorize function
c = Colorize(cmap='indexed', scale=brightness_scale, flag_scale=1)
for ii in xrange(0, len(regressors)):
ax1 = fig1.add_subplot(gs[0, ii])
c.colors = [colors[ii]]
img = c.transform([b_pos[ii, :, :]],
mask=rsq,
background=self.reference,
mixing=0.5)
self.image(img)
# Plot the unique stimuli in subplots
subplot_count = 0
for ii in self.unique_stimuli:
b_pos_list = []
color_mat = []
for keys in regressors.iterkeys():
if ii in keys:
index = regressors.keys().index(keys)
b_pos_list.append(b_pos[index, :, :])
color_mat.append(colors[index])
ax1 = fig1.add_subplot(gs[1, subplot_count])
c.colors = color_mat
img = c.transform(b_pos_list,
mask=rsq,
background=self.reference,
mixing=0.5)
self.image(img)
subplot_count += 1
# Plot the different stimuli parameters in subplots
for ii in self.parameters:
b_pos_list = []
color_mat = []
for keys in regressors.iterkeys():
if ii in keys:
index = regressors.keys().index(keys)
b_pos_list.append(b_pos[index, :, :])
color_mat.append(colors[index])
ax1 = fig1.add_subplot(gs[1, subplot_count])
c.colors = color_mat
img = c.transform(b_pos_list,
mask=rsq,
background=self.reference,
mixing=0.5)
self.image(img)
subplot_count += 1
# Plot all together
b_pos_list = []
color_mat = []
for ii in xrange(0, len(regressors)):
b_pos_list.append(b_pos[ii, :, :])
color_mat.append(colors[ii])
ax1 = fig1.add_subplot(gs[2:4, 1:3])
c.colors = color_mat
img = c.transform(b_pos_list,
mask=rsq,
background=self.reference,
mixing=0.5)
self.image(img)
subplot_count += 1
ax1 = fig1.add_subplot(gs[2, 0])
self.create_colorbar(ax1, regressors, colors)
