def __init__(self, fig, labelstr):
artist.Artist.__init__(self)
self.set_figure(fig)
x, self.depth = self.parser.to_rgba(labelstr,
color='black',
fontsize=14,
dpi=100)
xHover, depth = self.parser.to_rgba(labelstr,
color='white',
fontsize=14,
dpi=100)
self.labelwidth = x.shape[1]
self.labelheight = x.shape[0]
print 'h', self.labelheight
self.label = image.FigureImage(fig)
self.label.set_array(x.astype(float) / 255.)
self.labelHover = image.FigureImage(fig)
self.labelHover.set_array(xHover.astype(float) / 255.)
# we'll update these later
self.rect = patches.Rectangle((0, 0),
1,
1,
facecolor='yellow',
alpha=0.2)
self.rectHover = patches.Rectangle((0, 0),
1,
1,
facecolor='blue',
alpha=0.2)
def __init__(self,
fig,
labelstr,
props=None,
hoverprops=None,
on_select=None):
artist.Artist.__init__(self)
self.set_figure(fig)
self.labelstr = labelstr
if props is None:
props = ItemProperties()
if hoverprops is None:
hoverprops = ItemProperties()
self.props = props
self.hoverprops = hoverprops
self.on_select = on_select
x, self.depth = self.parser.to_mask(labelstr,
fontsize=props.fontsize,
dpi=fig.dpi)
if props.fontsize != hoverprops.fontsize:
raise NotImplementedError(
'support for different font sizes not implemented')
self.labelwidth = x.shape[1]
self.labelheight = x.shape[0]
self.labelArray = np.zeros((x.shape[0], x.shape[1], 4))
self.labelArray[:, :, -1] = x / 255.
self.label = image.FigureImage(fig, origin='upper')
self.label.set_array(self.labelArray)
# we'll update these later
self.rect = patches.Rectangle((0, 0), 1, 1)
self.set_hover_props(False)
fig.canvas.mpl_connect('button_release_event', self.check_select)
def _plot(fig, hists, labels, n, show_ticks=None):
"""
Plot pair-wise correlation histograms
"""
if n <= 1:
fig.text(0.5,
0.5,
"No correlation plots when only one variable",
ha="center",
va="center")
return
vmin, vmax = inf, -inf
for data, _, _ in hists.values():
positive = data[data > 0]
if len(positive) > 0:
vmin = min(vmin, np.amin(positive))
vmax = max(vmax, np.amax(positive))
norm = colors.LogNorm(vmin=vmin, vmax=vmax, clip=False)
#norm = colors.Normalize(vmin=vmin, vmax=vmax)
mapper = image.FigureImage(fig)
mapper.set_array(np.zeros(0))
mapper.set_cmap(cmap=COLORMAP)
mapper.set_norm(norm)
if show_ticks is None:
show_ticks = n < 3
ax = {}
Nr = Nc = n - 1
for i in range(0, n - 1):
for j in range(i + 1, n):
sharex = ax.get((0, j), None)
sharey = ax.get((i, i + 1), None)
a = fig.add_subplot(Nr,
Nc, (Nr - i - 1) * Nc + j,
sharex=sharex,
sharey=sharey)
ax[(i, j)] = a
a.xaxis.set_major_locator(MaxNLocator(4, steps=[1, 2, 4, 5, 10]))
a.yaxis.set_major_locator(MaxNLocator(4, steps=[1, 2, 4, 5, 10]))
data, x, y = hists[(i, j)]
data = np.clip(data, vmin, vmax)
a.pcolorfast(y, x, data, cmap=COLORMAP, norm=norm)
# Show labels or hide ticks
if i != 0:
artist.setp(a.get_xticklabels(), visible=False)
if i == n - 2 and j == n - 1:
a.set_xlabel(labels[j])
#a.xaxis.set_label_position("top")
#a.xaxis.set_offset_position("top")
if not show_ticks:
a.xaxis.set_ticks([])
if j == i + 1:
a.set_ylabel(labels[i])
else:
artist.setp(a.get_yticklabels(), visible=False)
if not show_ticks:
a.yaxis.set_ticks([])
a.zoomable = True
# Adjust subplots and add the colorbar
fig.subplots_adjust(left=0.07,
bottom=0.07,
top=0.9,
right=0.85,
wspace=0.0,
hspace=0.0)
cax = fig.add_axes([0.88, 0.2, 0.04, 0.6])
fig.colorbar(mapper, cax=cax, orientation='vertical')
return ax
return None
plot_post_psd(overwrite = True)
#%% Tests to join psd
plot_post = raws_filt[0].plot_psd(area_mode=None, show=True, average=False, ax=plt.axes(ylim=(0,60)),fmin =1.0, fmax=80.0, dB=False, n_fft=160)
plot_pre = raws_filt[1].plot_psd(area_mode=None, show=True, average=False, ax=plt.axes(ylim=(0,60)),fmin =1.0, fmax=80.0, dB=False, n_fft=160)
path = "C:\\Users\\admin\\Desktop\\eeGNN\\preprocessing\\psd_real\\pre_psd\\S23_real_pre.png"
path2 = "C:\\Users\\admin\\Desktop\\eeGNN\\preprocessing\\psd_real\\pre_psd\\S66_real_pre.png"
b = image.FigureImage(plot_post)
c = image.FigureImage(plot_pre)
a = [b,c]
list_im = [path, path2]
new_im = Image.new('RGB', (444,95)) #creates a new empty image, RGB mode, and size 444 by 95
for elem in list_im:
im=Image.open(elem)
print(elem)
#im.show()
new_im.paste(im, (i,0))
new_im.save('test2.jpg')
#%% Other tests
