def to_rgb_color_list(color_str, default):
if "rgb" in color_str:
return [int(v) for v in color_str.strip("rgb()").split(",")]
elif "#" in color_str:
return clrs.hex_to_rgb(color_str)
else:
return default
def to_rgb_color_list(color_str, default):
if 'rgb' in color_str:
return [int(v) for v in color_str.strip('rgb()').split(',')]
elif '#' in color_str:
return clrs.hex_to_rgb(color_str)
else:
return default
def _colors(ncontours, colormap=None):
"""
Return a list of ``ncontours`` colors from the ``colormap`` colorscale.
"""
if colormap in clrs.PLOTLY_SCALES.keys():
cmap = clrs.PLOTLY_SCALES[colormap]
else:
raise exceptions.PlotlyError(
"Colorscale must be a valid Plotly Colorscale."
"The available colorscale names are {}".format(
clrs.PLOTLY_SCALES.keys()))
values = np.linspace(0, 1, ncontours)
vals_cmap = np.array([pair[0] for pair in cmap])
cols = np.array([pair[1] for pair in cmap])
inds = np.searchsorted(vals_cmap, values)
if "#" in cols[0]: # for Viridis
cols = [clrs.label_rgb(clrs.hex_to_rgb(col)) for col in cols]
colors = [cols[0]]
for ind, val in zip(inds[1:], values[1:]):
val1, val2 = vals_cmap[ind - 1], vals_cmap[ind]
interm = (val - val1) / (val2 - val1)
col = clrs.find_intermediate_color(cols[ind - 1],
cols[ind],
interm,
colortype="rgb")
colors.append(col)
return colors
def to_rgb_color_list(color_str, default):
if 'rgb' in color_str:
return [int(v) for v in color_str.strip('rgb()').split(',')]
elif '#' in color_str:
return clrs.hex_to_rgb(color_str)
else:
return default
def _any_to_rgb(color: Union[tuple, str]) -> str:
c: str = label_rgb(color) if isinstance(color, tuple) else color
if c.startswith("#"):
c = label_rgb(hex_to_rgb(c))
if not c.startswith("rgb("):
raise RuntimeError("Something went wrong with the logic above!")
return c
def _colors(ncontours, colormap=None):
"""
Return a list of ``ncontours`` colors from the ``colormap`` colorscale.
"""
if colormap in clrs.PLOTLY_SCALES.keys():
cmap = clrs.PLOTLY_SCALES[colormap]
else:
raise exceptions.PlotlyError(
"Colorscale must be a valid Plotly Colorscale."
"The available colorscale names are {}".format(
clrs.PLOTLY_SCALES.keys()))
values = np.linspace(0, 1, ncontours)
vals_cmap = np.array([pair[0] for pair in cmap])
cols = np.array([pair[1] for pair in cmap])
inds = np.searchsorted(vals_cmap, values)
if '#' in cols[0]: # for Viridis
cols = [clrs.label_rgb(clrs.hex_to_rgb(col)) for col in cols]
colors = [cols[0]]
for ind, val in zip(inds[1:], values[1:]):
val1, val2 = vals_cmap[ind - 1], vals_cmap[ind]
interm = (val - val1) / (val2 - val1)
col = clrs.find_intermediate_color(cols[ind - 1],
cols[ind], interm,
colortype='rgb')
colors.append(col)
return colors
def to_rgb_color_list(color_str, default):
color_str = color_str.strip()
if color_str.startswith("rgb"):
return [int(v) for v in color_str.strip("rgba()").split(",")]
elif color_str.startswith("#"):
return clrs.hex_to_rgb(color_str)
else:
return default
def graph_options(self, element, ranges, style):
opts = super(TriSurfacePlot, self).graph_options(element, ranges, style)
copts = self.get_color_opts(element.dimensions()[2], element, ranges, style)
opts['colormap'] = [tuple(v/255. for v in colors.hex_to_rgb(c))
for _, c in copts['colorscale']]
opts['scale'] = [l for l, _ in copts['colorscale']]
opts['show_colorbar'] = self.colorbar
return {k: v for k, v in opts.items() if 'legend' not in k and k != 'name'}
def graph_options(self, element, ranges, style):
opts = super(TriSurfacePlot, self).graph_options(element, ranges, style)
copts = self.get_color_opts(element.dimensions()[2], element, ranges, style)
opts['colormap'] = [tuple(v/255. for v in colors.hex_to_rgb(c))
for _, c in copts['colorscale']]
opts['scale'] = [l for l, _ in copts['colorscale']]
opts['show_colorbar'] = self.colorbar
opts['edges_color'] = style.get('edges_color', 'black')
opts['plot_edges'] = 'edges_color' in style
opts['colorbar'] = copts.get('colorbar', None)
return {k: v for k, v in opts.items() if 'legend' not in k and k != 'name'}
)
from plotly.express.colors import sequential
# noinspection PyProtectedMember
from ridgeplot._colors import _path_to_colors_dict
# start off by getting all named color-scales defined in PLOTLY_SCALES
all_colorscales_raw = PLOTLY_SCALES.copy()
# turn plotly's default colors into the default color-scale
all_colorscales_raw["default"] = make_colorscale(DEFAULT_PLOTLY_COLORS)
# add all sequential color-scales
for name, color_list in vars(sequential).items():
if name.startswith("_") or name.startswith("swatches"):
continue
all_colorscales_raw[name] = make_colorscale(color_list)
all_colorscales_clean = {}
for name, colorscale in all_colorscales_raw.items():
# convert all color-scales to 'rgb(r, g, b)' format
if colorscale[0][1].startswith("#"):
colorscale = [[s, label_rgb(hex_to_rgb(c))] for s, c in colorscale]
# validate the color-scale as a sanity check and
# use lower-case convention for all color-scales
validate_colorscale(colorscale)
all_colorscales_clean[name.lower()] = colorscale
with _path_to_colors_dict.open(mode="w") as _colors_json:
json.dump(all_colorscales_clean, _colors_json, indent=2)
def alpha(hex_colour: str, a: float) -> str:
"""Add an alpha component to a colour represented as a hex string without an alpha component."""
rgb: tuple[int, int, int] = hex_to_rgb(hex_colour)
return f"rgba({rgb[0]},{rgb[1]},{rgb[2]},{a})"
def trisurf(x, y, z, simplices, show_colorbar, edges_color, scale,
colormap=None, color_func=None, plot_edges=False, x_edge=None,
y_edge=None, z_edge=None, facecolor=None):
"""
Refer to FigureFactory.create_trisurf() for docstring
"""
# numpy import check
if not np:
raise ImportError("FigureFactory._trisurf() requires "
"numpy imported.")
points3D = np.vstack((x, y, z)).T
simplices = np.atleast_2d(simplices)
# vertices of the surface triangles
tri_vertices = points3D[simplices]
# Define colors for the triangle faces
if color_func is None:
# mean values of z-coordinates of triangle vertices
mean_dists = tri_vertices[:, :, 2].mean(-1)
elif isinstance(color_func, (list, np.ndarray)):
# Pre-computed list / array of values to map onto color
if len(color_func) != len(simplices):
raise ValueError("If color_func is a list/array, it must "
"be the same length as simplices.")
# convert all colors in color_func to rgb
for index in range(len(color_func)):
if isinstance(color_func[index], str):
if '#' in color_func[index]:
foo = colors.hex_to_rgb(color_func[index])
color_func[index] = colors.label_rgb(foo)
if isinstance(color_func[index], tuple):
foo = colors.convert_to_RGB_255(color_func[index])
color_func[index] = colors.label_rgb(foo)
mean_dists = np.asarray(color_func)
else:
# apply user inputted function to calculate
# custom coloring for triangle vertices
mean_dists = []
for triangle in tri_vertices:
dists = []
for vertex in triangle:
dist = color_func(vertex[0], vertex[1], vertex[2])
dists.append(dist)
mean_dists.append(np.mean(dists))
mean_dists = np.asarray(mean_dists)
# Check if facecolors are already strings and can be skipped
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 = map_face2color(mean_dists[index], colormap, scale,
min_mean_dists, max_mean_dists)
facecolor.append(color)
# Make sure facecolor is a list so output is consistent across Pythons
facecolor = np.asarray(facecolor)
ii, jj, kk = simplices.T
triangles = graph_objs.Mesh3d(x=x, y=y, z=z, facecolor=facecolor,
i=ii, j=jj, k=kk, name='')
mean_dists_are_numbers = not isinstance(mean_dists[0], str)
if mean_dists_are_numbers and show_colorbar is True:
# make a colorscale from the colors
colorscale = colors.make_colorscale(colormap, scale)
colorscale = colors.convert_colorscale_to_rgb(colorscale)
colorbar = graph_objs.Scatter3d(
x=x[:1],
y=y[:1],
z=z[:1],
mode='markers',
marker=dict(
size=0.1,
color=[min_mean_dists, max_mean_dists],
colorscale=colorscale,
showscale=True),
hoverinfo='none',
showlegend=False
)
# the triangle sides are not plotted
if plot_edges is False:
if mean_dists_are_numbers and show_colorbar is True:
return [triangles, colorbar]
else:
return [triangles]
# define the lists x_edge, y_edge and z_edge, of x, y, resp z
# coordinates of edge end points for each triangle
# None separates data corresponding to two consecutive triangles
is_none = [ii is None for ii in [x_edge, y_edge, z_edge]]
if any(is_none):
if not all(is_none):
raise ValueError("If any (x_edge, y_edge, z_edge) is None, "
"all must be None")
else:
x_edge = []
y_edge = []
z_edge = []
# Pull indices we care about, then add a None column to separate tris
ixs_triangles = [0, 1, 2, 0]
pull_edges = tri_vertices[:, ixs_triangles, :]
x_edge_pull = np.hstack([pull_edges[:, :, 0],
np.tile(None, [pull_edges.shape[0], 1])])
y_edge_pull = np.hstack([pull_edges[:, :, 1],
np.tile(None, [pull_edges.shape[0], 1])])
z_edge_pull = np.hstack([pull_edges[:, :, 2],
np.tile(None, [pull_edges.shape[0], 1])])
# Now unravel the edges into a 1-d vector for plotting
x_edge = np.hstack([x_edge, x_edge_pull.reshape([1, -1])[0]])
y_edge = np.hstack([y_edge, y_edge_pull.reshape([1, -1])[0]])
z_edge = np.hstack([z_edge, z_edge_pull.reshape([1, -1])[0]])
if not (len(x_edge) == len(y_edge) == len(z_edge)):
raise exceptions.PlotlyError("The lengths of x_edge, y_edge and "
"z_edge are not the same.")
# define the lines for plotting
lines = graph_objs.Scatter3d(
x=x_edge, y=y_edge, z=z_edge, mode='lines',
line=graph_objs.scatter3d.Line(
color=edges_color,
width=1.5
),
showlegend=False
)
if mean_dists_are_numbers and show_colorbar is True:
return [triangles, lines, colorbar]
else:
return [triangles, lines]
def trisurf(x,
y,
z,
simplices,
show_colorbar,
edges_color,
scale,
colormap=None,
color_func=None,
plot_edges=False,
x_edge=None,
y_edge=None,
z_edge=None,
facecolor=None):
"""
Refer to FigureFactory.create_trisurf() for docstring
"""
# numpy import check
if not np:
raise ImportError("FigureFactory._trisurf() requires "
"numpy imported.")
points3D = np.vstack((x, y, z)).T
simplices = np.atleast_2d(simplices)
# vertices of the surface triangles
tri_vertices = points3D[simplices]
# Define colors for the triangle faces
if color_func is None:
# mean values of z-coordinates of triangle vertices
mean_dists = tri_vertices[:, :, 2].mean(-1)
elif isinstance(color_func, (list, np.ndarray)):
# Pre-computed list / array of values to map onto color
if len(color_func) != len(simplices):
raise ValueError("If color_func is a list/array, it must "
"be the same length as simplices.")
# convert all colors in color_func to rgb
for index in range(len(color_func)):
if isinstance(color_func[index], str):
if '#' in color_func[index]:
foo = colors.hex_to_rgb(color_func[index])
color_func[index] = colors.label_rgb(foo)
if isinstance(color_func[index], tuple):
foo = colors.convert_to_RGB_255(color_func[index])
color_func[index] = colors.label_rgb(foo)
mean_dists = np.asarray(color_func)
else:
# apply user inputted function to calculate
# custom coloring for triangle vertices
mean_dists = []
for triangle in tri_vertices:
dists = []
for vertex in triangle:
dist = color_func(vertex[0], vertex[1], vertex[2])
dists.append(dist)
mean_dists.append(np.mean(dists))
mean_dists = np.asarray(mean_dists)
# Check if facecolors are already strings and can be skipped
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 = map_face2color(mean_dists[index], colormap, scale,
min_mean_dists, max_mean_dists)
facecolor.append(color)
# Make sure facecolor is a list so output is consistent across Pythons
facecolor = np.asarray(facecolor)
ii, jj, kk = simplices.T
triangles = graph_objs.Mesh3d(x=x,
y=y,
z=z,
facecolor=facecolor,
i=ii,
j=jj,
k=kk,
name='')
mean_dists_are_numbers = not isinstance(mean_dists[0], str)
if mean_dists_are_numbers and show_colorbar is True:
# make a colorscale from the colors
colorscale = colors.make_colorscale(colormap, scale)
colorscale = colors.convert_colorscale_to_rgb(colorscale)
colorbar = graph_objs.Scatter3d(
x=x[:1],
y=y[:1],
z=z[:1],
mode='markers',
marker=dict(size=0.1,
color=[min_mean_dists, max_mean_dists],
colorscale=colorscale,
showscale=True),
hoverinfo='None',
showlegend=False)
# the triangle sides are not plotted
if plot_edges is False:
if mean_dists_are_numbers and show_colorbar is True:
return graph_objs.Data([triangles, colorbar])
else:
return graph_objs.Data([triangles])
# define the lists x_edge, y_edge and z_edge, of x, y, resp z
# coordinates of edge end points for each triangle
# None separates data corresponding to two consecutive triangles
is_none = [ii is None for ii in [x_edge, y_edge, z_edge]]
if any(is_none):
if not all(is_none):
raise ValueError("If any (x_edge, y_edge, z_edge) is None, "
"all must be None")
else:
x_edge = []
y_edge = []
z_edge = []
# Pull indices we care about, then add a None column to separate tris
ixs_triangles = [0, 1, 2, 0]
pull_edges = tri_vertices[:, ixs_triangles, :]
x_edge_pull = np.hstack(
[pull_edges[:, :, 0],
np.tile(None, [pull_edges.shape[0], 1])])
y_edge_pull = np.hstack(
[pull_edges[:, :, 1],
np.tile(None, [pull_edges.shape[0], 1])])
z_edge_pull = np.hstack(
[pull_edges[:, :, 2],
np.tile(None, [pull_edges.shape[0], 1])])
# Now unravel the edges into a 1-d vector for plotting
x_edge = np.hstack([x_edge, x_edge_pull.reshape([1, -1])[0]])
y_edge = np.hstack([y_edge, y_edge_pull.reshape([1, -1])[0]])
z_edge = np.hstack([z_edge, z_edge_pull.reshape([1, -1])[0]])
if not (len(x_edge) == len(y_edge) == len(z_edge)):
raise exceptions.PlotlyError("The lengths of x_edge, y_edge and "
"z_edge are not the same.")
# define the lines for plotting
lines = graph_objs.Scatter3d(x=x_edge,
y=y_edge,
z=z_edge,
mode='lines',
line=graph_objs.Line(color=edges_color,
width=1.5),
showlegend=False)
if mean_dists_are_numbers and show_colorbar is True:
return graph_objs.Data([triangles, lines, colorbar])
else:
return graph_objs.Data([triangles, lines])
