def _plot(self, a, key, title, gx, gy, num_x, num_y):
logger.debug('Plotting: %s', key)
pp.rcParams['figure.figsize'] = (self._image_width / 300,
self._image_height / 300)
pp.title(title)
# Interpolate the data
rbf = Rbf(a['x'], a['y'], a[key], function='linear')
z = rbf(gx, gy)
z = z.reshape((num_y, num_x))
# Render the interpolated data to the plot
pp.axis('off')
# begin color mapping
if 'min' in self.thresholds.get(key, {}):
vmin = self.thresholds[key]['min']
logger.debug('Using min threshold from thresholds: %s', vmin)
else:
vmin = min(a[key])
logger.debug('Using calculated min threshold: %s', vmin)
if 'max' in self.thresholds.get(key, {}):
vmax = self.thresholds[key]['max']
logger.debug('Using max threshold from thresholds: %s', vmax)
else:
vmax = max(a[key])
logger.debug('Using calculated max threshold: %s', vmax)
norm = matplotlib.colors.Normalize(vmin=vmin, vmax=vmax, clip=True)
mapper = cm.ScalarMappable(norm=norm, cmap='RdYlBu_r')
# end color mapping
image = pp.imshow(z,
extent=(0, self._image_width, self._image_height, 0),
cmap='RdYlBu_r',
alpha=0.5,
zorder=100,
vmin=vmin,
vmax=vmax)
pp.colorbar(image)
pp.imshow(self._layout, interpolation='bicubic', zorder=1, alpha=1)
labelsize = FontManager.get_default_size() * 0.4
# begin plotting points
for idx in range(0, len(a['x'])):
if (a['x'][idx], a['y'][idx]) in self._corners:
continue
pp.plot(a['x'][idx],
a['y'][idx],
marker='o',
markeredgecolor='black',
markeredgewidth=1,
markerfacecolor=mapper.to_rgba(a[key][idx]),
markersize=6)
pp.text(a['x'][idx],
a['y'][idx] - 30,
a['ap'][idx],
fontsize=labelsize,
horizontalalignment='center')
# end plotting points
fname = '%s_%s.png' % (key, self._title)
logger.info('Writing plot to: %s', fname)
pp.savefig(fname, dpi=300)
pp.close('all')
def _plot(self, a, key, title, gx, gy, num_x, num_y):
if key not in a:
logger.info("Skipping {} due to insufficient data".format(key))
return
if not len(a['x']) == len(a['y']) == len(a[key]):
logger.info("Skipping {} because data has holes".format(key))
return
logger.debug('Plotting: %s', key)
pp.rcParams['figure.figsize'] = (
self._image_width / 300, self._image_height / 300
)
fig, ax = pp.subplots()
ax.set_title(title)
if 'min' in self.thresholds.get(key, {}):
vmin = self.thresholds[key]['min']
logger.debug('Using min threshold from thresholds: %s', vmin)
else:
vmin = min(a[key])
logger.debug('Using calculated min threshold: %s', vmin)
if 'max' in self.thresholds.get(key, {}):
vmax = self.thresholds[key]['max']
logger.debug('Using max threshold from thresholds: %s', vmax)
else:
vmax = max(a[key])
logger.debug('Using calculated max threshold: %s', vmax)
logger.info("{} has range [{},{}]".format(key, vmin, vmax))
# Interpolate the data only if there is something to interpolate
if vmin != vmax:
rbf = Rbf(
a['x'], a['y'], a[key], function='linear'
)
z = rbf(gx, gy)
z = z.reshape((num_y, num_x))
else:
# Uniform array with the same color everywhere
# (avoids interpolation artifacts)
z = numpy.ones((num_y, num_x))*vmin
# Render the interpolated data to the plot
ax.axis('off')
# begin color mapping
norm = matplotlib.colors.Normalize(vmin=vmin, vmax=vmax, clip=True)
mapper = cm.ScalarMappable(norm=norm, cmap=self._cmap)
# end color mapping
image = ax.imshow(
z,
extent=(0, self._image_width, self._image_height, 0),
alpha=0.5, zorder=100,
cmap=self._cmap, vmin=vmin, vmax=vmax
)
# Draw contours if requested and meaningful in this plot
if self._contours is not None and vmin != vmax:
CS = ax.contour(z, colors='k', linewidths=1, levels=self._contours,
extent=(0, self._image_width, self._image_height, 0),
alpha=0.3, zorder=150, origin='upper')
ax.clabel(CS, inline=1, fontsize=6)
cbar = fig.colorbar(image)
# Print only one ytick label when there is only one value to be shown
if vmin == vmax:
cbar.set_ticks([vmin])
# Draw floorplan itself to the lowest layer with full opacity
ax.imshow(self._layout, interpolation='bicubic', zorder=1, alpha=1)
labelsize = FontManager.get_default_size() * 0.4
if(self._showpoints):
# begin plotting points
for idx in range(0, len(a['x'])):
if (a['x'][idx], a['y'][idx]) in self._corners:
continue
ax.plot(
a['x'][idx], a['y'][idx], zorder=200,
marker='o', markeredgecolor='black', markeredgewidth=1,
markerfacecolor=mapper.to_rgba(a[key][idx]), markersize=6
)
ax.text(
a['x'][idx], a['y'][idx] - 30,
a['ap'][idx], fontsize=labelsize,
horizontalalignment='center'
)
# end plotting points
fname = '%s_%s.png' % (key, self._title)
logger.info('Writing plot to: %s', fname)
pp.savefig(fname, dpi=300)
pp.close('all')
def fontsize(idx, default=FontManager.get_default_size()):
coeff = p.nodes[idx]["freq"] / p.molecules
size = default * coeff * ax_coeff
return size
