def plot_weighted(self,
mapp,
ax=None,
weighting='linear',
second_map=None,
indices=None,
**plot_args):
"""
Generate weighted plot
:param mapp:
:type mapp:
:param ax: axes object
:param weighting: weighting function, 'linear' or 'dual'.
:type weighting: str
:param second_map:
:param indices:
.. todo:: __doc__
"""
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
else:
fig = ax.get_figure()
if self.color_list is None:
color_list = get_colors(len(mapp[0][-1]) + 1)
color_list.pop(0) #remove black
else:
color_list = self.color_list
pts, datas = zip(*list(mapp))
if indices is None:
indices = range(0, len(datas[0]))
rgbs = []
datas = zip(*datas)
datas = [d for id, d in enumerate(datas) if id in indices]
datas = zip(*datas)
if second_map:
pts2, datas2 = zip(*second_map)
datas2 = zip(*datas2)
datas2 = [d for id, d in enumerate(datas2) if id in indices]
datas2 = zip(*datas2)
else:
datas2 = datas
for data, data2 in zip(datas, datas2):
if weighting == 'linear':
rs, gs, bs = zip(*color_list)
r = 1 - sum(float((1 - ri) * di) for ri, di in zip(rs, data))
g = 1 - sum(float((1 - gi) * di) for gi, di in zip(gs, data))
b = 1 - sum(float((1 - bi) * di) for bi, di in zip(bs, data))
eff_res = self.resolution * self.resolution_enhancement
rgbs.append([r, g, b])
elif weighting == 'dual':
rs, gs, bs = zip(*color_list)
r = 1 - sum(
float((1 - ri) * di * d2i)
for ri, di, d2i in zip(rs, data, data2))
g = 1 - sum(
float((1 - gi) * di * d2i)
for gi, di, d2i in zip(gs, data, data2))
b = 1 - sum(
float((1 - bi) * di * d2i)
for bi, di, d2i in zip(bs, data, data2))
eff_res = 300
rgbs.append([r, g, b])
r, g, b = zip(*rgbs)
x, y = zip(*pts)
xi = np.linspace(min(x), max(x), eff_res)
yi = np.linspace(min(y), max(y), eff_res)
ri = griddata(x, y, r, xi, yi)
gi = griddata(x, y, g, xi, yi)
bi = griddata(x, y, b, xi, yi)
rgb_array = np.zeros((eff_res, eff_res, 3))
for i in range(0, eff_res):
for j in range(0, eff_res):
rgb_array[i, j, 0] = ri[i, j]
rgb_array[i, j, 1] = gi[i, j]
rgb_array[i, j, 2] = bi[i, j]
xminmax, yminmax = self.descriptor_ranges
xmin, xmax = xminmax
ymin, ymax = yminmax
ax.imshow(rgb_array, extent=[xmin, xmax, ymin, ymax], origin='lower')
self.plot_descriptor_pts(mapp, i, ax)
if getattr(self, 'n_xticks', None):
ax.xaxis.set_major_locator(MaxNLocator(self.n_xticks))
if getattr(self, 'n_yticks', None):
ax.yaxis.set_major_locator(MaxNLocator(self.n_yticks))
ax.set_xlabel(self.descriptor_labels[0])
ax.set_ylabel(self.descriptor_labels[1])
if self.aspect:
ax.set_aspect(self.aspect)
ax.apply_aspect()
return fig
def plot_weighted(self, mapp, ax=None, weighting='linear',
second_map=None, indices=None, **plot_args):
"""
Generate weighted plot
:param mapp:
:type mapp:
:param ax: axes object
:param weighting: weighting function, 'linear' or 'dual'.
:type weighting: str
:param second_map:
:param indices:
.. todo:: __doc__
"""
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
else:
fig = ax.get_figure()
if self.color_list is None:
color_list = get_colors(len(mapp[0][-1]) + 1)
color_list.pop(0) # remove black
else:
color_list = self.color_list
pts, datas = zip(*mapp)
if indices is None:
indices = range(0, len(datas[0]))
rgbs = []
datas = zip(*datas)
datas = [d for id, d in enumerate(datas) if id in indices]
datas = zip(*datas)
if second_map:
pts2, datas2 = zip(*second_map)
datas2 = zip(*datas2)
datas2 = [d for id, d in enumerate(datas2) if id in indices]
datas2 = zip(*datas2)
else:
datas2 = datas
for data, data2 in zip(datas, datas2):
if weighting == 'linear':
rs, gs, bs = zip(*color_list)
r = 1 - sum(float((1 - ri) * di) for ri, di in zip(rs, data))
g = 1 - sum(float((1 - gi) * di) for gi, di in zip(gs, data))
b = 1 - sum(float((1 - bi) * di) for bi, di in zip(bs, data))
eff_res = self.resolution * self.resolution_enhancement
rgbs.append([r, g, b])
elif weighting == 'dual':
rs, gs, bs = zip(*color_list)
r = 1 - sum(float((1 - ri) * di * d2i)
for ri, di, d2i in zip(rs, data, data2))
g = 1 - sum(float((1 - gi) * di * d2i)
for gi, di, d2i in zip(gs, data, data2))
b = 1 - sum(float((1 - bi) * di * d2i)
for bi, di, d2i in zip(bs, data, data2))
eff_res = 300
rgbs.append([r, g, b])
r, g, b = zip(*rgbs)
x, y = zip(*pts)
xi = np.linspace(min(x), max(x), eff_res)
yi = np.linspace(min(y), max(y), eff_res)
ri = griddata(x, y, r, xi, yi)
gi = griddata(x, y, g, xi, yi)
bi = griddata(x, y, b, xi, yi)
rgb_array = np.zeros((eff_res, eff_res, 3))
for i in range(0, eff_res):
for j in range(0, eff_res):
rgb_array[i, j, 0] = ri[i, j]
rgb_array[i, j, 1] = gi[i, j]
rgb_array[i, j, 2] = bi[i, j]
xminmax, yminmax = self.descriptor_ranges
xmin, xmax = xminmax
ymin, ymax = yminmax
ax.imshow(rgb_array, extent=[xmin, xmax, ymin, ymax], origin='lower')
self.plot_descriptor_pts(mapp, i, ax)
if getattr(self, 'n_xticks', None):
ax.xaxis.set_major_locator(MaxNLocator(self.n_xticks))
if getattr(self, 'n_yticks', None):
ax.yaxis.set_major_locator(MaxNLocator(self.n_yticks))
ax.set_xlabel(self.descriptor_labels[0])
ax.set_ylabel(self.descriptor_labels[1])
if self.aspect:
ax.set_aspect(self.aspect)
ax.apply_aspect()
return fig