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Aug 9, 2016
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Trisurf and color optimizations #499

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120 changes: 71 additions & 49 deletions plotly/tools.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3022,47 +3022,60 @@ def _unconvert_from_RGB_255(colors):
return un_rgb_color

@staticmethod
def _map_face2color(face, colormap, vmin, vmax):
def _map_faces2color(faces, colormap):
"""
Normalize facecolor values by vmin/vmax and return rgb-color strings

This function takes a tuple color along with a colormap and a minimum
(vmin) and maximum (vmax) range of possible mean distances for the
given parametrized surface. It returns an rgb color based on the mean
distance between vmin and vmax
Normalize facecolors by their min/max and return rgb-color strings.

This function takes a tuple color along with a colormap.
It returns an rgb color based on the mean distance between the
minimum and maximum value of faces.
"""
if vmin >= vmax:
raise exceptions.PlotlyError("Incorrect relation between vmin "
"and vmax. The vmin value cannot be "
"bigger than or equal to the value "
"of vmax.")

if len(colormap) == 1:
colormap = np.atleast_2d(colormap)
if colormap.shape[0] == 1:
# color each triangle face with the same color in colormap
face_color = colormap[0]
face_color = FigureFactory._convert_to_RGB_255(face_color)
face_color = FigureFactory._label_rgb(face_color)
face_colors = colormap
else:
if face == vmax:
# pick last color in colormap
face_color = colormap[-1]
face_color = FigureFactory._convert_to_RGB_255(face_color)
face_color = FigureFactory._label_rgb(face_color)
else:
# find the normalized distance t of a triangle face between
# vmin and vmax where the distance is between 0 and 1
t = (face - vmin) / float((vmax - vmin))
low_color_index = int(t / (1./(len(colormap) - 1)))

face_color = FigureFactory._find_intermediate_color(
colormap[low_color_index],
colormap[low_color_index + 1],
t * (len(colormap) - 1) - low_color_index)
face_color = FigureFactory._convert_to_RGB_255(face_color)
face_color = FigureFactory._label_rgb(face_color)
# Convert face values to between 0 and 1
vmin = faces.min()
vmax = faces.max()
if vmin >= vmax:
raise exceptions.PlotlyError("Incorrect relation between vmin"
" and vmax. The vmin value cannot"
" be bigger than or equal to the"
" value of vmax.")
# Scale t to between 0 and 1
t = (faces - vmin) / float((vmax - vmin))
t_ixs = np.round(t * 255).astype(int)

# If a list of colors is given, interpolate between them.
color_range = FigureFactory._blend_colors(colormap)
face_colors = color_range[t_ixs]

# Convert to 255 scale, and round to nearest integer
face_colors = np.round(face_colors * 255., 0)
face_colors = FigureFactory._label_rgb(face_colors)
return face_colors

return face_color
@staticmethod
def _blend_colors(colormap, n_colors=255.):
if len(colormap) == 1:
raise ValueError('Cannot blend a colormap with only one color')
# Figure out how many splits we need
n_split = np.floor(n_colors / (len(colormap) - 1)).astype(int)
n_remain = np.mod(n_colors, len(colormap))

# Iterate through pairs of colors
color_range = []
for ii in range(len(colormap) - 1):
# For each channel (r, g, b)
this_interp = []
for cstt, cstp in zip(colormap[ii], colormap[ii + 1]):
# If it's not an even split, add req'd amount on first iter
n_interp = n_split + n_remain if ii == 0 else n_split
this_interp.append(np.linspace(cstt, cstp, n_interp))
color_range.append(np.vstack(this_interp).T)
color_range = np.vstack(color_range)
return color_range

@staticmethod
def _trisurf(x, y, z, simplices, colormap=None, color_func=None,
Expand Down Expand Up @@ -3117,17 +3130,12 @@ def _trisurf(x, y, z, simplices, colormap=None, color_func=None,
if isinstance(mean_dists[0], str):
facecolor = mean_dists
else:
min_mean_dists = np.min(mean_dists)
max_mean_dists = np.max(mean_dists)

if facecolor is None:
facecolor = []
for index in range(len(mean_dists)):
color = FigureFactory._map_face2color(mean_dists[index],
colormap,
min_mean_dists,
max_mean_dists)
facecolor.append(color)
# Map distances to color using the given cmap
dist_colors = FigureFactory._map_faces2color(mean_dists, colormap)
if facecolor is not None:
facecolor = np.vstack([facecolor, dist_colors])
else:
facecolor = dist_colors

# Make sure we have arrays to speed up plotting
facecolor = np.asarray(facecolor)
Expand Down Expand Up @@ -4338,8 +4346,17 @@ def _convert_to_RGB_255(colors):
"""
Multiplies each element of a triplet by 255
"""

return (colors[0]*255.0, colors[1]*255.0, colors[2]*255.0)
if isinstance(colors, tuple):
return (colors[0]*255.0, colors[1]*255.0, colors[2]*255.0)
elif isinstance(colors, np.ndarray):
# Vectorize the multiplication and return a list of tuples
return [tuple(ii) for ii in colors * 255.0]
else:
colors_255 = []
for color in colors:
rgb_color = (color[0]*255.0, color[1]*255.0, color[2]*255.0)
colors_255.append(rgb_color)
return colors_255

@staticmethod
def _n_colors(lowcolor, highcolor, n_colors):
Expand Down Expand Up @@ -4372,7 +4389,12 @@ def _label_rgb(colors):
"""
Takes tuple (a, b, c) and returns an rgb color 'rgb(a, b, c)'
"""
return ('rgb(%s, %s, %s)' % (colors[0], colors[1], colors[2]))
if isinstance(colors, tuple):
return ('rgb(%s, %s, %s)' % (colors[0], colors[1], colors[2]))
else:
colors_label = ['rgb(%s, %s, %s)' % (r, g, b)
for r, g, b in colors]
return colors_label

@staticmethod
def _unlabel_rgb(colors):
Expand Down