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"""
colors
=====
Functions that manipulate colors and arrays of colors.
-----
There are three basic types of color types: rgb, hex and tuple:
rgb - An rgb color is a string of the form 'rgb(a,b,c)' where a, b and c are
integers between 0 and 255 inclusive.
hex - A hex color is a string of the form '#xxxxxx' where each x is a
character that belongs to the set [0,1,2,3,4,5,6,7,8,9,a,b,c,d,e,f]. This is
just the set of characters used in the hexadecimal numeric system.
tuple - A tuple color is a 3-tuple of the form (a,b,c) where a, b and c are
floats between 0 and 1 inclusive.
-----
Colormaps and Colorscales:
A colormap or a colorscale is a correspondence between values - Pythonic
objects such as strings and floats - to colors.
There are typically two main types of colormaps that exist: numerical and
categorical colormaps.
Numerical:
----------
Numerical colormaps are used when the coloring column being used takes a
spectrum of values or numbers.
A classic example from the Plotly library:
```
rainbow_colorscale = [
[0, 'rgb(150,0,90)'], [0.125, 'rgb(0,0,200)'],
[0.25, 'rgb(0,25,255)'], [0.375, 'rgb(0,152,255)'],
[0.5, 'rgb(44,255,150)'], [0.625, 'rgb(151,255,0)'],
[0.75, 'rgb(255,234,0)'], [0.875, 'rgb(255,111,0)'],
[1, 'rgb(255,0,0)']
]
```
Notice that this colorscale is a list of lists with each inner list containing
a number and a color. These left hand numbers in the nested lists go from 0 to
1, and they are like pointers tell you when a number is mapped to a specific
color.
If you have a column of numbers `col_num` that you want to plot, and you know
```
min(col_num) = 0
max(col_num) = 100
```
then if you pull out the number `12.5` in the list and want to figure out what
color the corresponding chart element (bar, scatter plot, etc) is going to be,
you'll figure out that proportionally 12.5 to 100 is the same as 0.125 to 1.
So, the point will be mapped to 'rgb(0,0,200)'.
All other colors between the pinned values in a colorscale are linearly
interpolated.
Categorical:
------------
Alternatively, a categorical colormap is used to assign a specific value in a
color column to a specific color everytime it appears in the dataset.
A column of strings in a panadas.dataframe that is chosen to serve as the
color index would naturally use a categorical colormap. However, you can
choose to use a categorical colormap with a column of numbers.
Be careful! If you have a lot of unique numbers in your color column you will
end up with a colormap that is massive and may slow down graphing performance.
"""
import decimal
from numbers import Number
from _plotly_utils import exceptions
# Built-in qualitative color sequences and sequential,
# diverging and cyclical color scales.
#
# Initially ported over from plotly_express
from . import ( # noqa: F401
qualitative,
sequential,
diverging,
cyclical,
cmocean,
colorbrewer,
carto,
plotlyjs,
)
DEFAULT_PLOTLY_COLORS = [
"rgb(31, 119, 180)",
"rgb(255, 127, 14)",
"rgb(44, 160, 44)",
"rgb(214, 39, 40)",
"rgb(148, 103, 189)",
"rgb(140, 86, 75)",
"rgb(227, 119, 194)",
"rgb(127, 127, 127)",
"rgb(188, 189, 34)",
"rgb(23, 190, 207)",
]
PLOTLY_SCALES = {
"Greys": [[0, "rgb(0,0,0)"], [1, "rgb(255,255,255)"]],
"YlGnBu": [
[0, "rgb(8,29,88)"],
[0.125, "rgb(37,52,148)"],
[0.25, "rgb(34,94,168)"],
[0.375, "rgb(29,145,192)"],
[0.5, "rgb(65,182,196)"],
[0.625, "rgb(127,205,187)"],
[0.75, "rgb(199,233,180)"],
[0.875, "rgb(237,248,217)"],
[1, "rgb(255,255,217)"],
],
"Greens": [
[0, "rgb(0,68,27)"],
[0.125, "rgb(0,109,44)"],
[0.25, "rgb(35,139,69)"],
[0.375, "rgb(65,171,93)"],
[0.5, "rgb(116,196,118)"],
[0.625, "rgb(161,217,155)"],
[0.75, "rgb(199,233,192)"],
[0.875, "rgb(229,245,224)"],
[1, "rgb(247,252,245)"],
],
"YlOrRd": [
[0, "rgb(128,0,38)"],
[0.125, "rgb(189,0,38)"],
[0.25, "rgb(227,26,28)"],
[0.375, "rgb(252,78,42)"],
[0.5, "rgb(253,141,60)"],
[0.625, "rgb(254,178,76)"],
[0.75, "rgb(254,217,118)"],
[0.875, "rgb(255,237,160)"],
[1, "rgb(255,255,204)"],
],
"Bluered": [[0, "rgb(0,0,255)"], [1, "rgb(255,0,0)"]],
# modified RdBu based on
# www.sandia.gov/~kmorel/documents/ColorMaps/ColorMapsExpanded.pdf
"RdBu": [
[0, "rgb(5,10,172)"],
[0.35, "rgb(106,137,247)"],
[0.5, "rgb(190,190,190)"],
[0.6, "rgb(220,170,132)"],
[0.7, "rgb(230,145,90)"],
[1, "rgb(178,10,28)"],
],
# Scale for non-negative numeric values
"Reds": [
[0, "rgb(220,220,220)"],
[0.2, "rgb(245,195,157)"],
[0.4, "rgb(245,160,105)"],
[1, "rgb(178,10,28)"],
],
# Scale for non-positive numeric values
"Blues": [
[0, "rgb(5,10,172)"],
[0.35, "rgb(40,60,190)"],
[0.5, "rgb(70,100,245)"],
[0.6, "rgb(90,120,245)"],
[0.7, "rgb(106,137,247)"],
[1, "rgb(220,220,220)"],
],
"Picnic": [
[0, "rgb(0,0,255)"],
[0.1, "rgb(51,153,255)"],
[0.2, "rgb(102,204,255)"],
[0.3, "rgb(153,204,255)"],
[0.4, "rgb(204,204,255)"],
[0.5, "rgb(255,255,255)"],
[0.6, "rgb(255,204,255)"],
[0.7, "rgb(255,153,255)"],
[0.8, "rgb(255,102,204)"],
[0.9, "rgb(255,102,102)"],
[1, "rgb(255,0,0)"],
],
"Rainbow": [
[0, "rgb(150,0,90)"],
[0.125, "rgb(0,0,200)"],
[0.25, "rgb(0,25,255)"],
[0.375, "rgb(0,152,255)"],
[0.5, "rgb(44,255,150)"],
[0.625, "rgb(151,255,0)"],
[0.75, "rgb(255,234,0)"],
[0.875, "rgb(255,111,0)"],
[1, "rgb(255,0,0)"],
],
"Portland": [
[0, "rgb(12,51,131)"],
[0.25, "rgb(10,136,186)"],
[0.5, "rgb(242,211,56)"],
[0.75, "rgb(242,143,56)"],
[1, "rgb(217,30,30)"],
],
"Jet": [
[0, "rgb(0,0,131)"],
[0.125, "rgb(0,60,170)"],
[0.375, "rgb(5,255,255)"],
[0.625, "rgb(255,255,0)"],
[0.875, "rgb(250,0,0)"],
[1, "rgb(128,0,0)"],
],
"Hot": [
[0, "rgb(0,0,0)"],
[0.3, "rgb(230,0,0)"],
[0.6, "rgb(255,210,0)"],
[1, "rgb(255,255,255)"],
],
"Blackbody": [
[0, "rgb(0,0,0)"],
[0.2, "rgb(230,0,0)"],
[0.4, "rgb(230,210,0)"],
[0.7, "rgb(255,255,255)"],
[1, "rgb(160,200,255)"],
],
"Earth": [
[0, "rgb(0,0,130)"],
[0.1, "rgb(0,180,180)"],
[0.2, "rgb(40,210,40)"],
[0.4, "rgb(230,230,50)"],
[0.6, "rgb(120,70,20)"],
[1, "rgb(255,255,255)"],
],
"Electric": [
[0, "rgb(0,0,0)"],
[0.15, "rgb(30,0,100)"],
[0.4, "rgb(120,0,100)"],
[0.6, "rgb(160,90,0)"],
[0.8, "rgb(230,200,0)"],
[1, "rgb(255,250,220)"],
],
"Viridis": [
[0, "#440154"],
[0.06274509803921569, "#48186a"],
[0.12549019607843137, "#472d7b"],
[0.18823529411764706, "#424086"],
[0.25098039215686274, "#3b528b"],
[0.3137254901960784, "#33638d"],
[0.3764705882352941, "#2c728e"],
[0.4392156862745098, "#26828e"],
[0.5019607843137255, "#21918c"],
[0.5647058823529412, "#1fa088"],
[0.6274509803921569, "#28ae80"],
[0.6901960784313725, "#3fbc73"],
[0.7529411764705882, "#5ec962"],
[0.8156862745098039, "#84d44b"],
[0.8784313725490196, "#addc30"],
[0.9411764705882353, "#d8e219"],
[1, "#fde725"],
],
"Cividis": [
[0.000000, "rgb(0,32,76)"],
[0.058824, "rgb(0,42,102)"],
[0.117647, "rgb(0,52,110)"],
[0.176471, "rgb(39,63,108)"],
[0.235294, "rgb(60,74,107)"],
[0.294118, "rgb(76,85,107)"],
[0.352941, "rgb(91,95,109)"],
[0.411765, "rgb(104,106,112)"],
[0.470588, "rgb(117,117,117)"],
[0.529412, "rgb(131,129,120)"],
[0.588235, "rgb(146,140,120)"],
[0.647059, "rgb(161,152,118)"],
[0.705882, "rgb(176,165,114)"],
[0.764706, "rgb(192,177,109)"],
[0.823529, "rgb(209,191,102)"],
[0.882353, "rgb(225,204,92)"],
[0.941176, "rgb(243,219,79)"],
[1.000000, "rgb(255,233,69)"],
],
}
def color_parser(colors, function):
"""
Takes color(s) and a function and applies the function on the color(s)
In particular, this function identifies whether the given color object
is an iterable or not and applies the given color-parsing function to
the color or iterable of colors. If given an iterable, it will only be
able to work with it if all items in the iterable are of the same type
- rgb string, hex string or tuple
"""
if isinstance(colors, str):
return function(colors)
if isinstance(colors, tuple) and isinstance(colors[0], Number):
return function(colors)
if hasattr(colors, "__iter__"):
if isinstance(colors, tuple):
new_color_tuple = tuple(function(item) for item in colors)
return new_color_tuple
else:
new_color_list = [function(item) for item in colors]
return new_color_list
def validate_colors(colors, colortype="tuple"):
"""
Validates color(s) and returns a list of color(s) of a specified type
"""
from numbers import Number
if colors is None:
colors = DEFAULT_PLOTLY_COLORS
if isinstance(colors, str):
if colors in PLOTLY_SCALES:
colors_list = colorscale_to_colors(PLOTLY_SCALES[colors])
# TODO: fix _gantt.py/_scatter.py so that they can accept the
# actual colorscale and not just a list of the first and last
# color in the plotly colorscale. In resolving this issue we
# will be removing the immediate line below
colors = [colors_list[0]] + [colors_list[-1]]
elif "rgb" in colors or "#" in colors:
colors = [colors]
else:
raise exceptions.PlotlyError(
"If your colors variable is a string, it must be a "
"Plotly scale, an rgb color or a hex color."
)
elif isinstance(colors, tuple):
if isinstance(colors[0], Number):
colors = [colors]
else:
colors = list(colors)
# convert color elements in list to tuple color
for j, each_color in enumerate(colors):
if "rgb" in each_color:
each_color = color_parser(each_color, unlabel_rgb)
for value in each_color:
if value > 255.0:
raise exceptions.PlotlyError(
"Whoops! The elements in your rgb colors "
"tuples cannot exceed 255.0."
)
each_color = color_parser(each_color, unconvert_from_RGB_255)
colors[j] = each_color
if "#" in each_color:
each_color = color_parser(each_color, hex_to_rgb)
each_color = color_parser(each_color, unconvert_from_RGB_255)
colors[j] = each_color
if isinstance(each_color, tuple):
for value in each_color:
if value > 1.0:
raise exceptions.PlotlyError(
"Whoops! The elements in your colors tuples cannot exceed 1.0."
)
colors[j] = each_color
if colortype == "rgb" and not isinstance(colors, str):
for j, each_color in enumerate(colors):
rgb_color = color_parser(each_color, convert_to_RGB_255)
colors[j] = color_parser(rgb_color, label_rgb)
return colors
def validate_colors_dict(colors, colortype="tuple"):
"""
Validates dictionary of color(s)
"""
# validate each color element in the dictionary
for key in colors:
if "rgb" in colors[key]:
colors[key] = color_parser(colors[key], unlabel_rgb)
for value in colors[key]:
if value > 255.0:
raise exceptions.PlotlyError(
"Whoops! The elements in your rgb colors "
"tuples cannot exceed 255.0."
)
colors[key] = color_parser(colors[key], unconvert_from_RGB_255)
if "#" in colors[key]:
colors[key] = color_parser(colors[key], hex_to_rgb)
colors[key] = color_parser(colors[key], unconvert_from_RGB_255)
if isinstance(colors[key], tuple):
for value in colors[key]:
if value > 1.0:
raise exceptions.PlotlyError(
"Whoops! The elements in your colors tuples cannot exceed 1.0."
)
if colortype == "rgb":
for key in colors:
colors[key] = color_parser(colors[key], convert_to_RGB_255)
colors[key] = color_parser(colors[key], label_rgb)
return colors
def convert_colors_to_same_type(
colors,
colortype="rgb",
scale=None,
return_default_colors=False,
num_of_defualt_colors=2,
):
"""
Converts color(s) to the specified color type
Takes a single color or an iterable of colors, as well as a list of scale
values, and outputs a 2-pair of the list of color(s) converted all to an
rgb or tuple color type, aswell as the scale as the second element. If
colors is a Plotly Scale name, then 'scale' will be forced to the scale
from the respective colorscale and the colors in that colorscale will also
be coverted to the selected colortype. If colors is None, then there is an
option to return portion of the DEFAULT_PLOTLY_COLORS
:param (str|tuple|list) colors: either a plotly scale name, an rgb or hex
color, a color tuple or a list/tuple of colors
:param (list) scale: see docs for validate_scale_values()
:rtype (tuple) (colors_list, scale) if scale is None in the function call,
then scale will remain None in the returned tuple
"""
colors_list = []
if colors is None and return_default_colors is True:
colors_list = DEFAULT_PLOTLY_COLORS[0:num_of_defualt_colors]
if isinstance(colors, str):
if colors in PLOTLY_SCALES:
colors_list = colorscale_to_colors(PLOTLY_SCALES[colors])
if scale is None:
scale = colorscale_to_scale(PLOTLY_SCALES[colors])
elif "rgb" in colors or "#" in colors:
colors_list = [colors]
elif isinstance(colors, tuple):
if isinstance(colors[0], Number):
colors_list = [colors]
else:
colors_list = list(colors)
elif isinstance(colors, list):
colors_list = colors
# validate scale
if scale is not None:
validate_scale_values(scale)
if len(colors_list) != len(scale):
raise exceptions.PlotlyError(
"Make sure that the length of your scale matches the length "
"of your list of colors which is {}.".format(len(colors_list))
)
# convert all colors to rgb
for j, each_color in enumerate(colors_list):
if "#" in each_color:
each_color = color_parser(each_color, hex_to_rgb)
each_color = color_parser(each_color, label_rgb)
colors_list[j] = each_color
elif isinstance(each_color, tuple):
each_color = color_parser(each_color, convert_to_RGB_255)
each_color = color_parser(each_color, label_rgb)
colors_list[j] = each_color
if colortype == "rgb":
return (colors_list, scale)
elif colortype == "tuple":
for j, each_color in enumerate(colors_list):
each_color = color_parser(each_color, unlabel_rgb)
each_color = color_parser(each_color, unconvert_from_RGB_255)
colors_list[j] = each_color
return (colors_list, scale)
else:
raise exceptions.PlotlyError(
"You must select either rgb or tuple for your colortype variable."
)
def convert_dict_colors_to_same_type(colors_dict, colortype="rgb"):
"""
Converts a colors in a dictionary of colors to the specified color type
:param (dict) colors_dict: a dictionary whose values are single colors
"""
for key in colors_dict:
if "#" in colors_dict[key]:
colors_dict[key] = color_parser(colors_dict[key], hex_to_rgb)
colors_dict[key] = color_parser(colors_dict[key], label_rgb)
elif isinstance(colors_dict[key], tuple):
colors_dict[key] = color_parser(colors_dict[key], convert_to_RGB_255)
colors_dict[key] = color_parser(colors_dict[key], label_rgb)
if colortype == "rgb":
return colors_dict
elif colortype == "tuple":
for key in colors_dict:
colors_dict[key] = color_parser(colors_dict[key], unlabel_rgb)
colors_dict[key] = color_parser(colors_dict[key], unconvert_from_RGB_255)
return colors_dict
else:
raise exceptions.PlotlyError(
"You must select either rgb or tuple for your colortype variable."
)
def validate_scale_values(scale):
"""
Validates scale values from a colorscale
:param (list) scale: a strictly increasing list of floats that begins
with 0 and ends with 1. Its usage derives from a colorscale which is
a list of two-lists (a list with two elements) of the form
[value, color] which are used to determine how interpolation weighting
works between the colors in the colorscale. Therefore scale is just
the extraction of these values from the two-lists in order
"""
if len(scale) < 2:
raise exceptions.PlotlyError(
"You must input a list of scale values that has at least two values."
)
if (scale[0] != 0) or (scale[-1] != 1):
raise exceptions.PlotlyError(
"The first and last number in your scale must be 0.0 and 1.0 respectively."
)
if not all(x < y for x, y in zip(scale, scale[1:])):
raise exceptions.PlotlyError(
"'scale' must be a list that contains a strictly increasing "
"sequence of numbers."
)
def validate_colorscale(colorscale):
"""Validate the structure, scale values and colors of colorscale."""
if not isinstance(colorscale, list):
# TODO Write tests for these exceptions
raise exceptions.PlotlyError("A valid colorscale must be a list.")
if not all(isinstance(innerlist, list) for innerlist in colorscale):
raise exceptions.PlotlyError("A valid colorscale must be a list of lists.")
colorscale_colors = colorscale_to_colors(colorscale)
scale_values = colorscale_to_scale(colorscale)
validate_scale_values(scale_values)
validate_colors(colorscale_colors)
def make_colorscale(colors, scale=None):
"""
Makes a colorscale from a list of colors and a scale
Takes a list of colors and scales and constructs a colorscale based
on the colors in sequential order. If 'scale' is left empty, a linear-
interpolated colorscale will be generated. If 'scale' is a specificed
list, it must be the same legnth as colors and must contain all floats
For documentation regarding to the form of the output, see
https://plot.ly/python/reference/#mesh3d-colorscale
:param (list) colors: a list of single colors
"""
colorscale = []
# validate minimum colors length of 2
if len(colors) < 2:
raise exceptions.PlotlyError(
"You must input a list of colors that has at least two colors."
)
if scale is None:
scale_incr = 1.0 / (len(colors) - 1)
return [[i * scale_incr, color] for i, color in enumerate(colors)]
else:
if len(colors) != len(scale):
raise exceptions.PlotlyError(
"The length of colors and scale must be the same."
)
validate_scale_values(scale)
colorscale = [list(tup) for tup in zip(scale, colors)]
return colorscale
def find_intermediate_color(lowcolor, highcolor, intermed, colortype="tuple"):
"""
Returns the color at a given distance between two colors
This function takes two color tuples, where each element is between 0
and 1, along with a value 0 < intermed < 1 and returns a color that is
intermed-percent from lowcolor to highcolor. If colortype is set to 'rgb',
the function will automatically convert the rgb type to a tuple, find the
intermediate color and return it as an rgb color.
"""
if colortype == "rgb":
# convert to tuple color, eg. (1, 0.45, 0.7)
lowcolor = unlabel_rgb(lowcolor)
highcolor = unlabel_rgb(highcolor)
diff_0 = float(highcolor[0] - lowcolor[0])
diff_1 = float(highcolor[1] - lowcolor[1])
diff_2 = float(highcolor[2] - lowcolor[2])
inter_med_tuple = (
lowcolor[0] + intermed * diff_0,
lowcolor[1] + intermed * diff_1,
lowcolor[2] + intermed * diff_2,
)
if colortype == "rgb":
# back to an rgb string, e.g. rgb(30, 20, 10)
inter_med_rgb = label_rgb(inter_med_tuple)
return inter_med_rgb
return inter_med_tuple
def unconvert_from_RGB_255(colors):
"""
Return a tuple where each element gets divided by 255
Takes a (list of) color tuple(s) where each element is between 0 and
255. Returns the same tuples where each tuple element is normalized to
a value between 0 and 1
"""
return (colors[0] / (255.0), colors[1] / (255.0), colors[2] / (255.0))
def convert_to_RGB_255(colors):
"""
Multiplies each element of a triplet by 255
Each coordinate of the color tuple is rounded to the nearest float and
then is turned into an integer. If a number is of the form x.5, then
if x is odd, the number rounds up to (x+1). Otherwise, it rounds down
to just x. This is the way rounding works in Python 3 and in current
statistical analysis to avoid rounding bias
:param (list) rgb_components: grabs the three R, G and B values to be
returned as computed in the function
"""
rgb_components = []
for component in colors:
rounded_num = decimal.Decimal(str(component * 255.0)).quantize(
decimal.Decimal("1"), rounding=decimal.ROUND_HALF_EVEN
)
# convert rounded number to an integer from 'Decimal' form
rounded_num = int(rounded_num)
rgb_components.append(rounded_num)
return (rgb_components[0], rgb_components[1], rgb_components[2])
def n_colors(lowcolor, highcolor, n_colors, colortype="tuple"):
"""
Splits a low and high color into a list of n_colors colors in it
Accepts two color tuples and returns a list of n_colors colors
which form the intermediate colors between lowcolor and highcolor
from linearly interpolating through RGB space. If colortype is 'rgb'
the function will return a list of colors in the same form.
"""
if colortype == "rgb":
# convert to tuple
lowcolor = unlabel_rgb(lowcolor)
highcolor = unlabel_rgb(highcolor)
diff_0 = float(highcolor[0] - lowcolor[0])
incr_0 = diff_0 / (n_colors - 1)
diff_1 = float(highcolor[1] - lowcolor[1])
incr_1 = diff_1 / (n_colors - 1)
diff_2 = float(highcolor[2] - lowcolor[2])
incr_2 = diff_2 / (n_colors - 1)
list_of_colors = []
def _constrain_color(c):
if c > 255.0:
return 255.0
elif c < 0.0:
return 0.0
else:
return c
for index in range(n_colors):
new_tuple = (
_constrain_color(lowcolor[0] + (index * incr_0)),
_constrain_color(lowcolor[1] + (index * incr_1)),
_constrain_color(lowcolor[2] + (index * incr_2)),
)
list_of_colors.append(new_tuple)
if colortype == "rgb":
# back to an rgb string
list_of_colors = color_parser(list_of_colors, label_rgb)
return list_of_colors
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])
def unlabel_rgb(colors):
"""
Takes rgb color(s) 'rgb(a, b, c)' and returns tuple(s) (a, b, c)
This function takes either an 'rgb(a, b, c)' color or a list of
such colors and returns the color tuples in tuple(s) (a, b, c)
"""
str_vals = ""
for index in range(len(colors)):
try:
float(colors[index])
str_vals = str_vals + colors[index]
except ValueError:
if colors[index] == "," or colors[index] == ".":
str_vals = str_vals + colors[index]
str_vals = str_vals + ","
numbers = []
str_num = ""
for char in str_vals:
if char != ",":
str_num = str_num + char
else:
numbers.append(float(str_num))
str_num = ""
return (numbers[0], numbers[1], numbers[2])
def hex_to_rgb(value):
"""
Calculates rgb values from a hex color code.
:param (string) value: Hex color string
:rtype (tuple) (r_value, g_value, b_value): tuple of rgb values
"""
value = value.lstrip("#")
hex_total_length = len(value)
rgb_section_length = hex_total_length // 3
return tuple(
int(value[i : i + rgb_section_length], 16)
for i in range(0, hex_total_length, rgb_section_length)
)
def colorscale_to_colors(colorscale):
"""
Extracts the colors from colorscale as a list
"""
color_list = []
for item in colorscale:
color_list.append(item[1])
return color_list
def colorscale_to_scale(colorscale):
"""
Extracts the interpolation scale values from colorscale as a list
"""
scale_list = []
for item in colorscale:
scale_list.append(item[0])
return scale_list
def convert_colorscale_to_rgb(colorscale):
"""
Converts the colors in a colorscale to rgb colors
A colorscale is an array of arrays, each with a numeric value as the
first item and a color as the second. This function specifically is
converting a colorscale with tuple colors (each coordinate between 0
and 1) into a colorscale with the colors transformed into rgb colors
"""
for color in colorscale:
color[1] = convert_to_RGB_255(color[1])
for color in colorscale:
color[1] = label_rgb(color[1])
return colorscale
def named_colorscales():
"""
Returns lowercased names of built-in continuous colorscales.
"""
from _plotly_utils.basevalidators import ColorscaleValidator
return [c for c in ColorscaleValidator("", "").named_colorscales]
def get_colorscale(name):
"""
Returns the colorscale for a given name. See `named_colorscales` for the
built-in colorscales.
"""
from _plotly_utils.basevalidators import ColorscaleValidator
if not isinstance(name, str):
raise exceptions.PlotlyError("Name argument have to be a string.")
name = name.lower()
if name[-2:] == "_r":
should_reverse = True
name = name[:-2]
else:
should_reverse = False
if name in ColorscaleValidator("", "").named_colorscales:
colorscale = ColorscaleValidator("", "").named_colorscales[name]
else:
raise exceptions.PlotlyError(f"Colorscale {name} is not a built-in scale.")
if should_reverse:
colorscale = colorscale[::-1]
return make_colorscale(colorscale)
def sample_colorscale(colorscale, samplepoints, low=0.0, high=1.0, colortype="rgb"):
"""
Samples a colorscale at specific points.
Interpolates between colors in a colorscale to find the specific colors
corresponding to the specified sample values. The colorscale can be specified
as a list of `[scale, color]` pairs, as a list of colors, or as a named
plotly colorscale. The samplepoints can be specefied as an iterable of specific
points in the range [0.0, 1.0], or as an integer number of points which will
be spaced equally between the low value (default 0.0) and the high value
(default 1.0). The output is a list of colors, formatted according to the
specified colortype.
"""
from bisect import bisect_left
try:
validate_colorscale(colorscale)
except exceptions.PlotlyError:
if isinstance(colorscale, str):
colorscale = get_colorscale(colorscale)
else:
colorscale = make_colorscale(colorscale)
scale = colorscale_to_scale(colorscale)
validate_scale_values(scale)
colors = colorscale_to_colors(colorscale)
colors = validate_colors(colors, colortype="tuple")
if isinstance(samplepoints, int):
samplepoints = [
low + idx / (samplepoints - 1) * (high - low) for idx in range(samplepoints)
]
elif isinstance(samplepoints, float):
samplepoints = [samplepoints]
sampled_colors = []
for point in samplepoints:
high = bisect_left(scale, point)
low = high - 1
interpolant = (point - scale[low]) / (scale[high] - scale[low])
sampled_color = find_intermediate_color(colors[low], colors[high], interpolant)
sampled_colors.append(sampled_color)
return validate_colors(sampled_colors, colortype=colortype)

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def _swatches(module_names, module_contents, template=None):
"""
Parameters
----------
template : str or dict or plotly.graph_objects.layout.Template instance
The figure template name or definition.
Returns
-------
fig : graph_objects.Figure containing the displayed image
A `Figure` object. This figure demonstrates the color scales and
sequences in this module, as stacked bar charts.
"""
import plotly.graph_objs as go
from plotly.express._core import apply_default_cascade
args = dict(template=template)
apply_default_cascade(args)
sequences = [
(k, v)
for k, v in module_contents.items()
if not (k.startswith("_") or k.startswith("swatches") or k.endswith("_r"))
]
return go.Figure(
data=[
go.Bar(
orientation="h",
y=[name] * len(colors),
x=[1] * len(colors),
customdata=list(range(len(colors))),
marker=dict(color=colors),
hovertemplate="%{y}[%{customdata}] = %{marker.color}<extra></extra>",
)
for name, colors in reversed(sequences)
],
layout=dict(
title="plotly.colors." + module_names.split(".")[-1],
barmode="stack",
barnorm="fraction",
bargap=0.5,
showlegend=False,
xaxis=dict(range=[-0.02, 1.02], showticklabels=False, showgrid=False),
height=max(600, 40 * len(sequences)),
template=args["template"],
margin=dict(b=10),
),
)
def _swatches_continuous(module_names, module_contents, template=None):
"""
Parameters
----------
template : str or dict or plotly.graph_objects.layout.Template instance
The figure template name or definition.
Returns
-------
fig : graph_objects.Figure containing the displayed image
A `Figure` object. This figure demonstrates the color scales and
sequences in this module, as stacked bar charts.
"""
import plotly.graph_objs as go
from plotly.express._core import apply_default_cascade
args = dict(template=template)
apply_default_cascade(args)
sequences = [
(k, v)
for k, v in module_contents.items()
if not (k.startswith("_") or k.startswith("swatches") or k.endswith("_r"))
]
n = 100
return go.Figure(
data=[
go.Bar(
orientation="h",
y=[name] * n,
x=[1] * n,
customdata=[(x + 1) / n for x in range(n)],
marker=dict(color=list(range(n)), colorscale=name, line_width=0),
hovertemplate="%{customdata}",
name=name,
)
for name, colors in reversed(sequences)
],
layout=dict(
title="plotly.colors." + module_names.split(".")[-1],
barmode="stack",
barnorm="fraction",
bargap=0.3,
showlegend=False,
xaxis=dict(range=[-0.02, 1.02], showticklabels=False, showgrid=False),
height=max(600, 40 * len(sequences)),
width=500,
template=args["template"],
margin=dict(b=10),
),
)
def _swatches_cyclical(module_names, module_contents, template=None):
"""
Parameters
----------
template : str or dict or plotly.graph_objects.layout.Template instance
The figure template name or definition.
Returns
-------
fig : graph_objects.Figure containing the displayed image
A `Figure` object. This figure demonstrates the color scales and
sequences in this module, as polar bar charts.
"""
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from plotly.express._core import apply_default_cascade
args = dict(template=template)
apply_default_cascade(args)
rows = 2
cols = 4
scales = [
(k, v)
for k, v in module_contents.items()
if not (k.startswith("_") or k.startswith("swatches") or k.endswith("_r"))
]
names = [name for name, colors in scales]
fig = make_subplots(
rows=rows,
cols=cols,
subplot_titles=names,
specs=[[{"type": "polar"}] * cols] * rows,
)
for i, (name, scale) in enumerate(scales):
fig.add_trace(
go.Barpolar(
r=[1] * int(360 / 5),
theta=list(range(0, 360, 5)),
marker_color=list(range(0, 360, 5)),
marker_cmin=0,
marker_cmax=360,
marker_colorscale=name,
name=name,
),
row=int(i / cols) + 1,
col=i % cols + 1,
)
fig.update_traces(width=5.2, marker_line_width=0, base=0.5, showlegend=False)
fig.update_polars(angularaxis_visible=False, radialaxis_visible=False)
fig.update_layout(
title="plotly.colors." + module_names.split(".")[-1], template=args["template"]
)
return fig

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"""
Color sequences and scales from CARTO's CartoColors
Learn more at https://github.com/CartoDB/CartoColor
CARTOColors are made available under a Creative Commons Attribution license: https://creativecommons.org/licenses/by/3.0/us/
"""
from ._swatches import _swatches
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
Burg = [
"rgb(255, 198, 196)",
"rgb(244, 163, 168)",
"rgb(227, 129, 145)",
"rgb(204, 96, 125)",
"rgb(173, 70, 108)",
"rgb(139, 48, 88)",
"rgb(103, 32, 68)",
]
Burgyl = [
"rgb(251, 230, 197)",
"rgb(245, 186, 152)",
"rgb(238, 138, 130)",
"rgb(220, 113, 118)",
"rgb(200, 88, 108)",
"rgb(156, 63, 93)",
"rgb(112, 40, 74)",
]
Redor = [
"rgb(246, 210, 169)",
"rgb(245, 183, 142)",
"rgb(241, 156, 124)",
"rgb(234, 129, 113)",
"rgb(221, 104, 108)",
"rgb(202, 82, 104)",
"rgb(177, 63, 100)",
]
Oryel = [
"rgb(236, 218, 154)",
"rgb(239, 196, 126)",
"rgb(243, 173, 106)",
"rgb(247, 148, 93)",
"rgb(249, 123, 87)",
"rgb(246, 99, 86)",
"rgb(238, 77, 90)",
]
Peach = [
"rgb(253, 224, 197)",
"rgb(250, 203, 166)",
"rgb(248, 181, 139)",
"rgb(245, 158, 114)",
"rgb(242, 133, 93)",
"rgb(239, 106, 76)",
"rgb(235, 74, 64)",
]
Pinkyl = [
"rgb(254, 246, 181)",
"rgb(255, 221, 154)",
"rgb(255, 194, 133)",
"rgb(255, 166, 121)",
"rgb(250, 138, 118)",
"rgb(241, 109, 122)",
"rgb(225, 83, 131)",
]
Mint = [
"rgb(228, 241, 225)",
"rgb(180, 217, 204)",
"rgb(137, 192, 182)",
"rgb(99, 166, 160)",
"rgb(68, 140, 138)",
"rgb(40, 114, 116)",
"rgb(13, 88, 95)",
]
Blugrn = [
"rgb(196, 230, 195)",
"rgb(150, 210, 164)",
"rgb(109, 188, 144)",
"rgb(77, 162, 132)",
"rgb(54, 135, 122)",
"rgb(38, 107, 110)",
"rgb(29, 79, 96)",
]
Darkmint = [
"rgb(210, 251, 212)",
"rgb(165, 219, 194)",
"rgb(123, 188, 176)",
"rgb(85, 156, 158)",
"rgb(58, 124, 137)",
"rgb(35, 93, 114)",
"rgb(18, 63, 90)",
]
Emrld = [
"rgb(211, 242, 163)",
"rgb(151, 225, 150)",
"rgb(108, 192, 139)",
"rgb(76, 155, 130)",
"rgb(33, 122, 121)",
"rgb(16, 89, 101)",
"rgb(7, 64, 80)",
]
Aggrnyl = [
"rgb(36, 86, 104)",
"rgb(15, 114, 121)",
"rgb(13, 143, 129)",
"rgb(57, 171, 126)",
"rgb(110, 197, 116)",
"rgb(169, 220, 103)",
"rgb(237, 239, 93)",
]
Bluyl = [
"rgb(247, 254, 174)",
"rgb(183, 230, 165)",
"rgb(124, 203, 162)",
"rgb(70, 174, 160)",
"rgb(8, 144, 153)",
"rgb(0, 113, 139)",
"rgb(4, 82, 117)",
]
Teal = [
"rgb(209, 238, 234)",
"rgb(168, 219, 217)",
"rgb(133, 196, 201)",
"rgb(104, 171, 184)",
"rgb(79, 144, 166)",
"rgb(59, 115, 143)",
"rgb(42, 86, 116)",
]
Tealgrn = [
"rgb(176, 242, 188)",
"rgb(137, 232, 172)",
"rgb(103, 219, 165)",
"rgb(76, 200, 163)",
"rgb(56, 178, 163)",
"rgb(44, 152, 160)",
"rgb(37, 125, 152)",
]
Purp = [
"rgb(243, 224, 247)",
"rgb(228, 199, 241)",
"rgb(209, 175, 232)",
"rgb(185, 152, 221)",
"rgb(159, 130, 206)",
"rgb(130, 109, 186)",
"rgb(99, 88, 159)",
]
Purpor = [
"rgb(249, 221, 218)",
"rgb(242, 185, 196)",
"rgb(229, 151, 185)",
"rgb(206, 120, 179)",
"rgb(173, 95, 173)",
"rgb(131, 75, 160)",
"rgb(87, 59, 136)",
]
Sunset = [
"rgb(243, 231, 155)",
"rgb(250, 196, 132)",
"rgb(248, 160, 126)",
"rgb(235, 127, 134)",
"rgb(206, 102, 147)",
"rgb(160, 89, 160)",
"rgb(92, 83, 165)",
]
Magenta = [
"rgb(243, 203, 211)",
"rgb(234, 169, 189)",
"rgb(221, 136, 172)",
"rgb(202, 105, 157)",
"rgb(177, 77, 142)",
"rgb(145, 53, 125)",
"rgb(108, 33, 103)",
]
Sunsetdark = [
"rgb(252, 222, 156)",
"rgb(250, 164, 118)",
"rgb(240, 116, 110)",
"rgb(227, 79, 111)",
"rgb(220, 57, 119)",
"rgb(185, 37, 122)",
"rgb(124, 29, 111)",
]
Agsunset = [
"rgb(75, 41, 145)",
"rgb(135, 44, 162)",
"rgb(192, 54, 157)",
"rgb(234, 79, 136)",
"rgb(250, 120, 118)",
"rgb(246, 169, 122)",
"rgb(237, 217, 163)",
]
Brwnyl = [
"rgb(237, 229, 207)",
"rgb(224, 194, 162)",
"rgb(211, 156, 131)",
"rgb(193, 118, 111)",
"rgb(166, 84, 97)",
"rgb(129, 55, 83)",
"rgb(84, 31, 63)",
]
# Diverging schemes
Armyrose = [
"rgb(121, 130, 52)",
"rgb(163, 173, 98)",
"rgb(208, 211, 162)",
"rgb(253, 251, 228)",
"rgb(240, 198, 195)",
"rgb(223, 145, 163)",
"rgb(212, 103, 128)",
]
Fall = [
"rgb(61, 89, 65)",
"rgb(119, 136, 104)",
"rgb(181, 185, 145)",
"rgb(246, 237, 189)",
"rgb(237, 187, 138)",
"rgb(222, 138, 90)",
"rgb(202, 86, 44)",
]
Geyser = [
"rgb(0, 128, 128)",
"rgb(112, 164, 148)",
"rgb(180, 200, 168)",
"rgb(246, 237, 189)",
"rgb(237, 187, 138)",
"rgb(222, 138, 90)",
"rgb(202, 86, 44)",
]
Temps = [
"rgb(0, 147, 146)",
"rgb(57, 177, 133)",
"rgb(156, 203, 134)",
"rgb(233, 226, 156)",
"rgb(238, 180, 121)",
"rgb(232, 132, 113)",
"rgb(207, 89, 126)",
]
Tealrose = [
"rgb(0, 147, 146)",
"rgb(114, 170, 161)",
"rgb(177, 199, 179)",
"rgb(241, 234, 200)",
"rgb(229, 185, 173)",
"rgb(217, 137, 148)",
"rgb(208, 88, 126)",
]
Tropic = [
"rgb(0, 155, 158)",
"rgb(66, 183, 185)",
"rgb(167, 211, 212)",
"rgb(241, 241, 241)",
"rgb(228, 193, 217)",
"rgb(214, 145, 193)",
"rgb(199, 93, 171)",
]
Earth = [
"rgb(161, 105, 40)",
"rgb(189, 146, 90)",
"rgb(214, 189, 141)",
"rgb(237, 234, 194)",
"rgb(181, 200, 184)",
"rgb(121, 167, 172)",
"rgb(40, 135, 161)",
]
# Qualitative palettes
Antique = [
"rgb(133, 92, 117)",
"rgb(217, 175, 107)",
"rgb(175, 100, 88)",
"rgb(115, 111, 76)",
"rgb(82, 106, 131)",
"rgb(98, 83, 119)",
"rgb(104, 133, 92)",
"rgb(156, 156, 94)",
"rgb(160, 97, 119)",
"rgb(140, 120, 93)",
"rgb(124, 124, 124)",
]
Bold = [
"rgb(127, 60, 141)",
"rgb(17, 165, 121)",
"rgb(57, 105, 172)",
"rgb(242, 183, 1)",
"rgb(231, 63, 116)",
"rgb(128, 186, 90)",
"rgb(230, 131, 16)",
"rgb(0, 134, 149)",
"rgb(207, 28, 144)",
"rgb(249, 123, 114)",
"rgb(165, 170, 153)",
]
Pastel = [
"rgb(102, 197, 204)",
"rgb(246, 207, 113)",
"rgb(248, 156, 116)",
"rgb(220, 176, 242)",
"rgb(135, 197, 95)",
"rgb(158, 185, 243)",
"rgb(254, 136, 177)",
"rgb(201, 219, 116)",
"rgb(139, 224, 164)",
"rgb(180, 151, 231)",
"rgb(179, 179, 179)",
]
Prism = [
"rgb(95, 70, 144)",
"rgb(29, 105, 150)",
"rgb(56, 166, 165)",
"rgb(15, 133, 84)",
"rgb(115, 175, 72)",
"rgb(237, 173, 8)",
"rgb(225, 124, 5)",
"rgb(204, 80, 62)",
"rgb(148, 52, 110)",
"rgb(111, 64, 112)",
"rgb(102, 102, 102)",
]
Safe = [
"rgb(136, 204, 238)",
"rgb(204, 102, 119)",
"rgb(221, 204, 119)",
"rgb(17, 119, 51)",
"rgb(51, 34, 136)",
"rgb(170, 68, 153)",
"rgb(68, 170, 153)",
"rgb(153, 153, 51)",
"rgb(136, 34, 85)",
"rgb(102, 17, 0)",
"rgb(136, 136, 136)",
]
Vivid = [
"rgb(229, 134, 6)",
"rgb(93, 105, 177)",
"rgb(82, 188, 163)",
"rgb(153, 201, 69)",
"rgb(204, 97, 176)",
"rgb(36, 121, 108)",
"rgb(218, 165, 27)",
"rgb(47, 138, 196)",
"rgb(118, 78, 159)",
"rgb(237, 100, 90)",
"rgb(165, 170, 153)",
]
Aggrnyl_r = Aggrnyl[::-1]
Agsunset_r = Agsunset[::-1]
Antique_r = Antique[::-1]
Armyrose_r = Armyrose[::-1]
Blugrn_r = Blugrn[::-1]
Bluyl_r = Bluyl[::-1]
Bold_r = Bold[::-1]
Brwnyl_r = Brwnyl[::-1]
Burg_r = Burg[::-1]
Burgyl_r = Burgyl[::-1]
Darkmint_r = Darkmint[::-1]
Earth_r = Earth[::-1]
Emrld_r = Emrld[::-1]
Fall_r = Fall[::-1]
Geyser_r = Geyser[::-1]
Magenta_r = Magenta[::-1]
Mint_r = Mint[::-1]
Oryel_r = Oryel[::-1]
Pastel_r = Pastel[::-1]
Peach_r = Peach[::-1]
Pinkyl_r = Pinkyl[::-1]
Prism_r = Prism[::-1]
Purp_r = Purp[::-1]
Purpor_r = Purpor[::-1]
Redor_r = Redor[::-1]
Safe_r = Safe[::-1]
Sunset_r = Sunset[::-1]
Sunsetdark_r = Sunsetdark[::-1]
Teal_r = Teal[::-1]
Tealgrn_r = Tealgrn[::-1]
Tealrose_r = Tealrose[::-1]
Temps_r = Temps[::-1]
Tropic_r = Tropic[::-1]
Vivid_r = Vivid[::-1]

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"""
Color scales from the cmocean project
Learn more at https://matplotlib.org/cmocean/
cmocean is made available under an MIT license: https://github.com/matplotlib/cmocean/blob/master/LICENSE.txt
"""
from ._swatches import _swatches, _swatches_continuous
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
def swatches_continuous(template=None):
return _swatches_continuous(__name__, globals(), template)
swatches_continuous.__doc__ = _swatches_continuous.__doc__
turbid = [
"rgb(232, 245, 171)",
"rgb(220, 219, 137)",
"rgb(209, 193, 107)",
"rgb(199, 168, 83)",
"rgb(186, 143, 66)",
"rgb(170, 121, 60)",
"rgb(151, 103, 58)",
"rgb(129, 87, 56)",
"rgb(104, 72, 53)",
"rgb(80, 59, 46)",
"rgb(57, 45, 37)",
"rgb(34, 30, 27)",
]
thermal = [
"rgb(3, 35, 51)",
"rgb(13, 48, 100)",
"rgb(53, 50, 155)",
"rgb(93, 62, 153)",
"rgb(126, 77, 143)",
"rgb(158, 89, 135)",
"rgb(193, 100, 121)",
"rgb(225, 113, 97)",
"rgb(246, 139, 69)",
"rgb(251, 173, 60)",
"rgb(246, 211, 70)",
"rgb(231, 250, 90)",
]
haline = [
"rgb(41, 24, 107)",
"rgb(42, 35, 160)",
"rgb(15, 71, 153)",
"rgb(18, 95, 142)",
"rgb(38, 116, 137)",
"rgb(53, 136, 136)",
"rgb(65, 157, 133)",
"rgb(81, 178, 124)",
"rgb(111, 198, 107)",
"rgb(160, 214, 91)",
"rgb(212, 225, 112)",
"rgb(253, 238, 153)",
]
solar = [
"rgb(51, 19, 23)",
"rgb(79, 28, 33)",
"rgb(108, 36, 36)",
"rgb(135, 47, 32)",
"rgb(157, 66, 25)",
"rgb(174, 88, 20)",
"rgb(188, 111, 19)",
"rgb(199, 137, 22)",
"rgb(209, 164, 32)",
"rgb(217, 192, 44)",
"rgb(222, 222, 59)",
"rgb(224, 253, 74)",
]
ice = [
"rgb(3, 5, 18)",
"rgb(25, 25, 51)",
"rgb(44, 42, 87)",
"rgb(58, 60, 125)",
"rgb(62, 83, 160)",
"rgb(62, 109, 178)",
"rgb(72, 134, 187)",
"rgb(89, 159, 196)",
"rgb(114, 184, 205)",
"rgb(149, 207, 216)",
"rgb(192, 229, 232)",
"rgb(234, 252, 253)",
]
gray = [
"rgb(0, 0, 0)",
"rgb(16, 16, 16)",
"rgb(38, 38, 38)",
"rgb(59, 59, 59)",
"rgb(81, 80, 80)",
"rgb(102, 101, 101)",
"rgb(124, 123, 122)",
"rgb(146, 146, 145)",
"rgb(171, 171, 170)",
"rgb(197, 197, 195)",
"rgb(224, 224, 223)",
"rgb(254, 254, 253)",
]
oxy = [
"rgb(63, 5, 5)",
"rgb(101, 6, 13)",
"rgb(138, 17, 9)",
"rgb(96, 95, 95)",
"rgb(119, 118, 118)",
"rgb(142, 141, 141)",
"rgb(166, 166, 165)",
"rgb(193, 192, 191)",
"rgb(222, 222, 220)",
"rgb(239, 248, 90)",
"rgb(230, 210, 41)",
"rgb(220, 174, 25)",
]
deep = [
"rgb(253, 253, 204)",
"rgb(206, 236, 179)",
"rgb(156, 219, 165)",
"rgb(111, 201, 163)",
"rgb(86, 177, 163)",
"rgb(76, 153, 160)",
"rgb(68, 130, 155)",
"rgb(62, 108, 150)",
"rgb(62, 82, 143)",
"rgb(64, 60, 115)",
"rgb(54, 43, 77)",
"rgb(39, 26, 44)",
]
dense = [
"rgb(230, 240, 240)",
"rgb(191, 221, 229)",
"rgb(156, 201, 226)",
"rgb(129, 180, 227)",
"rgb(115, 154, 228)",
"rgb(117, 127, 221)",
"rgb(120, 100, 202)",
"rgb(119, 74, 175)",
"rgb(113, 50, 141)",
"rgb(100, 31, 104)",
"rgb(80, 20, 66)",
"rgb(54, 14, 36)",
]
algae = [
"rgb(214, 249, 207)",
"rgb(186, 228, 174)",
"rgb(156, 209, 143)",
"rgb(124, 191, 115)",
"rgb(85, 174, 91)",
"rgb(37, 157, 81)",
"rgb(7, 138, 78)",
"rgb(13, 117, 71)",
"rgb(23, 95, 61)",
"rgb(25, 75, 49)",
"rgb(23, 55, 35)",
"rgb(17, 36, 20)",
]
matter = [
"rgb(253, 237, 176)",
"rgb(250, 205, 145)",
"rgb(246, 173, 119)",
"rgb(240, 142, 98)",
"rgb(231, 109, 84)",
"rgb(216, 80, 83)",
"rgb(195, 56, 90)",
"rgb(168, 40, 96)",
"rgb(138, 29, 99)",
"rgb(107, 24, 93)",
"rgb(76, 21, 80)",
"rgb(47, 15, 61)",
]
speed = [
"rgb(254, 252, 205)",
"rgb(239, 225, 156)",
"rgb(221, 201, 106)",
"rgb(194, 182, 59)",
"rgb(157, 167, 21)",
"rgb(116, 153, 5)",
"rgb(75, 138, 20)",
"rgb(35, 121, 36)",
"rgb(11, 100, 44)",
"rgb(18, 78, 43)",
"rgb(25, 56, 34)",
"rgb(23, 35, 18)",
]
amp = [
"rgb(241, 236, 236)",
"rgb(230, 209, 203)",
"rgb(221, 182, 170)",
"rgb(213, 156, 137)",
"rgb(205, 129, 103)",
"rgb(196, 102, 73)",
"rgb(186, 74, 47)",
"rgb(172, 44, 36)",
"rgb(149, 19, 39)",
"rgb(120, 14, 40)",
"rgb(89, 13, 31)",
"rgb(60, 9, 17)",
]
tempo = [
"rgb(254, 245, 244)",
"rgb(222, 224, 210)",
"rgb(189, 206, 181)",
"rgb(153, 189, 156)",
"rgb(110, 173, 138)",
"rgb(65, 157, 129)",
"rgb(25, 137, 125)",
"rgb(18, 116, 117)",
"rgb(25, 94, 106)",
"rgb(28, 72, 93)",
"rgb(25, 51, 80)",
"rgb(20, 29, 67)",
]
phase = [
"rgb(167, 119, 12)",
"rgb(197, 96, 51)",
"rgb(217, 67, 96)",
"rgb(221, 38, 163)",
"rgb(196, 59, 224)",
"rgb(153, 97, 244)",
"rgb(95, 127, 228)",
"rgb(40, 144, 183)",
"rgb(15, 151, 136)",
"rgb(39, 153, 79)",
"rgb(119, 141, 17)",
"rgb(167, 119, 12)",
]
balance = [
"rgb(23, 28, 66)",
"rgb(41, 58, 143)",
"rgb(11, 102, 189)",
"rgb(69, 144, 185)",
"rgb(142, 181, 194)",
"rgb(210, 216, 219)",
"rgb(230, 210, 204)",
"rgb(213, 157, 137)",
"rgb(196, 101, 72)",
"rgb(172, 43, 36)",
"rgb(120, 14, 40)",
"rgb(60, 9, 17)",
]
delta = [
"rgb(16, 31, 63)",
"rgb(38, 62, 144)",
"rgb(30, 110, 161)",
"rgb(60, 154, 171)",
"rgb(140, 193, 186)",
"rgb(217, 229, 218)",
"rgb(239, 226, 156)",
"rgb(195, 182, 59)",
"rgb(115, 152, 5)",
"rgb(34, 120, 36)",
"rgb(18, 78, 43)",
"rgb(23, 35, 18)",
]
curl = [
"rgb(20, 29, 67)",
"rgb(28, 72, 93)",
"rgb(18, 115, 117)",
"rgb(63, 156, 129)",
"rgb(153, 189, 156)",
"rgb(223, 225, 211)",
"rgb(241, 218, 206)",
"rgb(224, 160, 137)",
"rgb(203, 101, 99)",
"rgb(164, 54, 96)",
"rgb(111, 23, 91)",
"rgb(51, 13, 53)",
]
algae_r = algae[::-1]
amp_r = amp[::-1]
balance_r = balance[::-1]
curl_r = curl[::-1]
deep_r = deep[::-1]
delta_r = delta[::-1]
dense_r = dense[::-1]
gray_r = gray[::-1]
haline_r = haline[::-1]
ice_r = ice[::-1]
matter_r = matter[::-1]
oxy_r = oxy[::-1]
phase_r = phase[::-1]
solar_r = solar[::-1]
speed_r = speed[::-1]
tempo_r = tempo[::-1]
thermal_r = thermal[::-1]
turbid_r = turbid[::-1]

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"""
Color scales and sequences from the colorbrewer 2 project
Learn more at http://colorbrewer2.org
colorbrewer is made available under an Apache license: http://colorbrewer2.org/export/LICENSE.txt
"""
from ._swatches import _swatches
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
BrBG = [
"rgb(84,48,5)",
"rgb(140,81,10)",
"rgb(191,129,45)",
"rgb(223,194,125)",
"rgb(246,232,195)",
"rgb(245,245,245)",
"rgb(199,234,229)",
"rgb(128,205,193)",
"rgb(53,151,143)",
"rgb(1,102,94)",
"rgb(0,60,48)",
]
PRGn = [
"rgb(64,0,75)",
"rgb(118,42,131)",
"rgb(153,112,171)",
"rgb(194,165,207)",
"rgb(231,212,232)",
"rgb(247,247,247)",
"rgb(217,240,211)",
"rgb(166,219,160)",
"rgb(90,174,97)",
"rgb(27,120,55)",
"rgb(0,68,27)",
]
PiYG = [
"rgb(142,1,82)",
"rgb(197,27,125)",
"rgb(222,119,174)",
"rgb(241,182,218)",
"rgb(253,224,239)",
"rgb(247,247,247)",
"rgb(230,245,208)",
"rgb(184,225,134)",
"rgb(127,188,65)",
"rgb(77,146,33)",
"rgb(39,100,25)",
]
PuOr = [
"rgb(127,59,8)",
"rgb(179,88,6)",
"rgb(224,130,20)",
"rgb(253,184,99)",
"rgb(254,224,182)",
"rgb(247,247,247)",
"rgb(216,218,235)",
"rgb(178,171,210)",
"rgb(128,115,172)",
"rgb(84,39,136)",
"rgb(45,0,75)",
]
RdBu = [
"rgb(103,0,31)",
"rgb(178,24,43)",
"rgb(214,96,77)",
"rgb(244,165,130)",
"rgb(253,219,199)",
"rgb(247,247,247)",
"rgb(209,229,240)",
"rgb(146,197,222)",
"rgb(67,147,195)",
"rgb(33,102,172)",
"rgb(5,48,97)",
]
RdGy = [
"rgb(103,0,31)",
"rgb(178,24,43)",
"rgb(214,96,77)",
"rgb(244,165,130)",
"rgb(253,219,199)",
"rgb(255,255,255)",
"rgb(224,224,224)",
"rgb(186,186,186)",
"rgb(135,135,135)",
"rgb(77,77,77)",
"rgb(26,26,26)",
]
RdYlBu = [
"rgb(165,0,38)",
"rgb(215,48,39)",
"rgb(244,109,67)",
"rgb(253,174,97)",
"rgb(254,224,144)",
"rgb(255,255,191)",
"rgb(224,243,248)",
"rgb(171,217,233)",
"rgb(116,173,209)",
"rgb(69,117,180)",
"rgb(49,54,149)",
]
RdYlGn = [
"rgb(165,0,38)",
"rgb(215,48,39)",
"rgb(244,109,67)",
"rgb(253,174,97)",
"rgb(254,224,139)",
"rgb(255,255,191)",
"rgb(217,239,139)",
"rgb(166,217,106)",
"rgb(102,189,99)",
"rgb(26,152,80)",
"rgb(0,104,55)",
]
Spectral = [
"rgb(158,1,66)",
"rgb(213,62,79)",
"rgb(244,109,67)",
"rgb(253,174,97)",
"rgb(254,224,139)",
"rgb(255,255,191)",
"rgb(230,245,152)",
"rgb(171,221,164)",
"rgb(102,194,165)",
"rgb(50,136,189)",
"rgb(94,79,162)",
]
Set1 = [
"rgb(228,26,28)",
"rgb(55,126,184)",
"rgb(77,175,74)",
"rgb(152,78,163)",
"rgb(255,127,0)",
"rgb(255,255,51)",
"rgb(166,86,40)",
"rgb(247,129,191)",
"rgb(153,153,153)",
]
Pastel1 = [
"rgb(251,180,174)",
"rgb(179,205,227)",
"rgb(204,235,197)",
"rgb(222,203,228)",
"rgb(254,217,166)",
"rgb(255,255,204)",
"rgb(229,216,189)",
"rgb(253,218,236)",
"rgb(242,242,242)",
]
Dark2 = [
"rgb(27,158,119)",
"rgb(217,95,2)",
"rgb(117,112,179)",
"rgb(231,41,138)",
"rgb(102,166,30)",
"rgb(230,171,2)",
"rgb(166,118,29)",
"rgb(102,102,102)",
]
Set2 = [
"rgb(102,194,165)",
"rgb(252,141,98)",
"rgb(141,160,203)",
"rgb(231,138,195)",
"rgb(166,216,84)",
"rgb(255,217,47)",
"rgb(229,196,148)",
"rgb(179,179,179)",
]
Pastel2 = [
"rgb(179,226,205)",
"rgb(253,205,172)",
"rgb(203,213,232)",
"rgb(244,202,228)",
"rgb(230,245,201)",
"rgb(255,242,174)",
"rgb(241,226,204)",
"rgb(204,204,204)",
]
Set3 = [
"rgb(141,211,199)",
"rgb(255,255,179)",
"rgb(190,186,218)",
"rgb(251,128,114)",
"rgb(128,177,211)",
"rgb(253,180,98)",
"rgb(179,222,105)",
"rgb(252,205,229)",
"rgb(217,217,217)",
"rgb(188,128,189)",
"rgb(204,235,197)",
"rgb(255,237,111)",
]
Accent = [
"rgb(127,201,127)",
"rgb(190,174,212)",
"rgb(253,192,134)",
"rgb(255,255,153)",
"rgb(56,108,176)",
"rgb(240,2,127)",
"rgb(191,91,23)",
"rgb(102,102,102)",
]
Paired = [
"rgb(166,206,227)",
"rgb(31,120,180)",
"rgb(178,223,138)",
"rgb(51,160,44)",
"rgb(251,154,153)",
"rgb(227,26,28)",
"rgb(253,191,111)",
"rgb(255,127,0)",
"rgb(202,178,214)",
"rgb(106,61,154)",
"rgb(255,255,153)",
"rgb(177,89,40)",
]
Blues = [
"rgb(247,251,255)",
"rgb(222,235,247)",
"rgb(198,219,239)",
"rgb(158,202,225)",
"rgb(107,174,214)",
"rgb(66,146,198)",
"rgb(33,113,181)",
"rgb(8,81,156)",
"rgb(8,48,107)",
]
BuGn = [
"rgb(247,252,253)",
"rgb(229,245,249)",
"rgb(204,236,230)",
"rgb(153,216,201)",
"rgb(102,194,164)",
"rgb(65,174,118)",
"rgb(35,139,69)",
"rgb(0,109,44)",
"rgb(0,68,27)",
]
BuPu = [
"rgb(247,252,253)",
"rgb(224,236,244)",
"rgb(191,211,230)",
"rgb(158,188,218)",
"rgb(140,150,198)",
"rgb(140,107,177)",
"rgb(136,65,157)",
"rgb(129,15,124)",
"rgb(77,0,75)",
]
GnBu = [
"rgb(247,252,240)",
"rgb(224,243,219)",
"rgb(204,235,197)",
"rgb(168,221,181)",
"rgb(123,204,196)",
"rgb(78,179,211)",
"rgb(43,140,190)",
"rgb(8,104,172)",
"rgb(8,64,129)",
]
Greens = [
"rgb(247,252,245)",
"rgb(229,245,224)",
"rgb(199,233,192)",
"rgb(161,217,155)",
"rgb(116,196,118)",
"rgb(65,171,93)",
"rgb(35,139,69)",
"rgb(0,109,44)",
"rgb(0,68,27)",
]
Greys = [
"rgb(255,255,255)",
"rgb(240,240,240)",
"rgb(217,217,217)",
"rgb(189,189,189)",
"rgb(150,150,150)",
"rgb(115,115,115)",
"rgb(82,82,82)",
"rgb(37,37,37)",
"rgb(0,0,0)",
]
OrRd = [
"rgb(255,247,236)",
"rgb(254,232,200)",
"rgb(253,212,158)",
"rgb(253,187,132)",
"rgb(252,141,89)",
"rgb(239,101,72)",
"rgb(215,48,31)",
"rgb(179,0,0)",
"rgb(127,0,0)",
]
Oranges = [
"rgb(255,245,235)",
"rgb(254,230,206)",
"rgb(253,208,162)",
"rgb(253,174,107)",
"rgb(253,141,60)",
"rgb(241,105,19)",
"rgb(217,72,1)",
"rgb(166,54,3)",
"rgb(127,39,4)",
]
PuBu = [
"rgb(255,247,251)",
"rgb(236,231,242)",
"rgb(208,209,230)",
"rgb(166,189,219)",
"rgb(116,169,207)",
"rgb(54,144,192)",
"rgb(5,112,176)",
"rgb(4,90,141)",
"rgb(2,56,88)",
]
PuBuGn = [
"rgb(255,247,251)",
"rgb(236,226,240)",
"rgb(208,209,230)",
"rgb(166,189,219)",
"rgb(103,169,207)",
"rgb(54,144,192)",
"rgb(2,129,138)",
"rgb(1,108,89)",
"rgb(1,70,54)",
]
PuRd = [
"rgb(247,244,249)",
"rgb(231,225,239)",
"rgb(212,185,218)",
"rgb(201,148,199)",
"rgb(223,101,176)",
"rgb(231,41,138)",
"rgb(206,18,86)",
"rgb(152,0,67)",
"rgb(103,0,31)",
]
Purples = [
"rgb(252,251,253)",
"rgb(239,237,245)",
"rgb(218,218,235)",
"rgb(188,189,220)",
"rgb(158,154,200)",
"rgb(128,125,186)",
"rgb(106,81,163)",
"rgb(84,39,143)",
"rgb(63,0,125)",
]
RdPu = [
"rgb(255,247,243)",
"rgb(253,224,221)",
"rgb(252,197,192)",
"rgb(250,159,181)",
"rgb(247,104,161)",
"rgb(221,52,151)",
"rgb(174,1,126)",
"rgb(122,1,119)",
"rgb(73,0,106)",
]
Reds = [
"rgb(255,245,240)",
"rgb(254,224,210)",
"rgb(252,187,161)",
"rgb(252,146,114)",
"rgb(251,106,74)",
"rgb(239,59,44)",
"rgb(203,24,29)",
"rgb(165,15,21)",
"rgb(103,0,13)",
]
YlGn = [
"rgb(255,255,229)",
"rgb(247,252,185)",
"rgb(217,240,163)",
"rgb(173,221,142)",
"rgb(120,198,121)",
"rgb(65,171,93)",
"rgb(35,132,67)",
"rgb(0,104,55)",
"rgb(0,69,41)",
]
YlGnBu = [
"rgb(255,255,217)",
"rgb(237,248,177)",
"rgb(199,233,180)",
"rgb(127,205,187)",
"rgb(65,182,196)",
"rgb(29,145,192)",
"rgb(34,94,168)",
"rgb(37,52,148)",
"rgb(8,29,88)",
]
YlOrBr = [
"rgb(255,255,229)",
"rgb(255,247,188)",
"rgb(254,227,145)",
"rgb(254,196,79)",
"rgb(254,153,41)",
"rgb(236,112,20)",
"rgb(204,76,2)",
"rgb(153,52,4)",
"rgb(102,37,6)",
]
YlOrRd = [
"rgb(255,255,204)",
"rgb(255,237,160)",
"rgb(254,217,118)",
"rgb(254,178,76)",
"rgb(253,141,60)",
"rgb(252,78,42)",
"rgb(227,26,28)",
"rgb(189,0,38)",
"rgb(128,0,38)",
]
Accent_r = Accent[::-1]
Blues_r = Blues[::-1]
BrBG_r = BrBG[::-1]
BuGn_r = BuGn[::-1]
BuPu_r = BuPu[::-1]
Dark2_r = Dark2[::-1]
GnBu_r = GnBu[::-1]
Greens_r = Greens[::-1]
Greys_r = Greys[::-1]
OrRd_r = OrRd[::-1]
Oranges_r = Oranges[::-1]
PRGn_r = PRGn[::-1]
Paired_r = Paired[::-1]
Pastel1_r = Pastel1[::-1]
Pastel2_r = Pastel2[::-1]
PiYG_r = PiYG[::-1]
PuBu_r = PuBu[::-1]
PuBuGn_r = PuBuGn[::-1]
PuOr_r = PuOr[::-1]
PuRd_r = PuRd[::-1]
Purples_r = Purples[::-1]
RdBu_r = RdBu[::-1]
RdGy_r = RdGy[::-1]
RdPu_r = RdPu[::-1]
RdYlBu_r = RdYlBu[::-1]
RdYlGn_r = RdYlGn[::-1]
Reds_r = Reds[::-1]
Set1_r = Set1[::-1]
Set2_r = Set2[::-1]
Set3_r = Set3[::-1]
Spectral_r = Spectral[::-1]
YlGn_r = YlGn[::-1]
YlGnBu_r = YlGnBu[::-1]
YlOrBr_r = YlOrBr[::-1]
YlOrRd_r = YlOrRd[::-1]

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"""
Cyclical color scales are appropriate for continuous data that has a natural cyclical \
structure, such as temporal data (hour of day, day of week, day of year, seasons) or
complex numbers or other phase data.
"""
from ._swatches import _swatches, _swatches_continuous, _swatches_cyclical
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
def swatches_continuous(template=None):
return _swatches_continuous(__name__, globals(), template)
swatches_continuous.__doc__ = _swatches_continuous.__doc__
def swatches_cyclical(template=None):
return _swatches_cyclical(__name__, globals(), template)
swatches_cyclical.__doc__ = _swatches_cyclical.__doc__
Twilight = [
"#e2d9e2",
"#9ebbc9",
"#6785be",
"#5e43a5",
"#421257",
"#471340",
"#8e2c50",
"#ba6657",
"#ceac94",
"#e2d9e2",
]
IceFire = [
"#000000",
"#001f4d",
"#003786",
"#0e58a8",
"#217eb8",
"#30a4ca",
"#54c8df",
"#9be4ef",
"#e1e9d1",
"#f3d573",
"#e7b000",
"#da8200",
"#c65400",
"#ac2301",
"#820000",
"#4c0000",
"#000000",
]
Edge = [
"#313131",
"#3d019d",
"#3810dc",
"#2d47f9",
"#2593ff",
"#2adef6",
"#60fdfa",
"#aefdff",
"#f3f3f1",
"#fffda9",
"#fafd5b",
"#f7da29",
"#ff8e25",
"#f8432d",
"#d90d39",
"#97023d",
"#313131",
]
Phase = [
"rgb(167, 119, 12)",
"rgb(197, 96, 51)",
"rgb(217, 67, 96)",
"rgb(221, 38, 163)",
"rgb(196, 59, 224)",
"rgb(153, 97, 244)",
"rgb(95, 127, 228)",
"rgb(40, 144, 183)",
"rgb(15, 151, 136)",
"rgb(39, 153, 79)",
"rgb(119, 141, 17)",
"rgb(167, 119, 12)",
]
HSV = [
"#ff0000",
"#ffa700",
"#afff00",
"#08ff00",
"#00ff9f",
"#00b7ff",
"#0010ff",
"#9700ff",
"#ff00bf",
"#ff0000",
]
mrybm = [
"#f884f7",
"#f968c4",
"#ea4388",
"#cf244b",
"#b51a15",
"#bd4304",
"#cc6904",
"#d58f04",
"#cfaa27",
"#a19f62",
"#588a93",
"#2269c4",
"#3e3ef0",
"#6b4ef9",
"#956bfa",
"#cd7dfe",
"#f884f7",
]
mygbm = [
"#ef55f1",
"#fb84ce",
"#fbafa1",
"#fcd471",
"#f0ed35",
"#c6e516",
"#96d310",
"#61c10b",
"#31ac28",
"#439064",
"#3d719a",
"#284ec8",
"#2e21ea",
"#6324f5",
"#9139fa",
"#c543fa",
"#ef55f1",
]
Edge_r = Edge[::-1]
HSV_r = HSV[::-1]
IceFire_r = IceFire[::-1]
Phase_r = Phase[::-1]
Twilight_r = Twilight[::-1]
mrybm_r = mrybm[::-1]
mygbm_r = mygbm[::-1]
__all__ = [
"swatches",
"swatches_cyclical",
]

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"""
Diverging color scales are appropriate for continuous data that has a natural midpoint \
other otherwise informative special value, such as 0 altitude, or the boiling point
of a liquid. The color scales in this module are \
mostly meant to be passed in as the `color_continuous_scale` argument to various \
functions, and to be used with the `color_continuous_midpoint` argument.
"""
from .colorbrewer import ( # noqa: F401
BrBG,
PRGn,
PiYG,
PuOr,
RdBu,
RdGy,
RdYlBu,
RdYlGn,
Spectral,
BrBG_r,
PRGn_r,
PiYG_r,
PuOr_r,
RdBu_r,
RdGy_r,
RdYlBu_r,
RdYlGn_r,
Spectral_r,
)
from .cmocean import ( # noqa: F401
balance,
delta,
curl,
oxy,
balance_r,
delta_r,
curl_r,
oxy_r,
)
from .carto import ( # noqa: F401
Armyrose,
Fall,
Geyser,
Temps,
Tealrose,
Tropic,
Earth,
Armyrose_r,
Fall_r,
Geyser_r,
Temps_r,
Tealrose_r,
Tropic_r,
Earth_r,
)
from .plotlyjs import Picnic, Portland, Picnic_r, Portland_r # noqa: F401
from ._swatches import _swatches, _swatches_continuous
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
def swatches_continuous(template=None):
return _swatches_continuous(__name__, globals(), template)
swatches_continuous.__doc__ = _swatches_continuous.__doc__
__all__ = ["swatches"]

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# Copied from
# https://github.com/plotly/plotly.js/blob/master/src/components/colorscale/scales.js
# NOTE: these differ slightly from plotly.colors.PLOTLY_SCALES from Plotly.js because
# those ones don't have perfectly evenly spaced steps ...
# not sure when this skew was introduced, possibly as early as Plotly.py v4.0
Blackbody = [
"rgb(0,0,0)",
"rgb(230,0,0)",
"rgb(230,210,0)",
"rgb(255,255,255)",
"rgb(160,200,255)",
]
Bluered = ["rgb(0,0,255)", "rgb(255,0,0)"]
Blues = [
"rgb(5,10,172)",
"rgb(40,60,190)",
"rgb(70,100,245)",
"rgb(90,120,245)",
"rgb(106,137,247)",
"rgb(220,220,220)",
]
Cividis = [
"rgb(0,32,76)",
"rgb(0,42,102)",
"rgb(0,52,110)",
"rgb(39,63,108)",
"rgb(60,74,107)",
"rgb(76,85,107)",
"rgb(91,95,109)",
"rgb(104,106,112)",
"rgb(117,117,117)",
"rgb(131,129,120)",
"rgb(146,140,120)",
"rgb(161,152,118)",
"rgb(176,165,114)",
"rgb(192,177,109)",
"rgb(209,191,102)",
"rgb(225,204,92)",
"rgb(243,219,79)",
"rgb(255,233,69)",
]
Earth = [
"rgb(0,0,130)",
"rgb(0,180,180)",
"rgb(40,210,40)",
"rgb(230,230,50)",
"rgb(120,70,20)",
"rgb(255,255,255)",
]
Electric = [
"rgb(0,0,0)",
"rgb(30,0,100)",
"rgb(120,0,100)",
"rgb(160,90,0)",
"rgb(230,200,0)",
"rgb(255,250,220)",
]
Greens = [
"rgb(0,68,27)",
"rgb(0,109,44)",
"rgb(35,139,69)",
"rgb(65,171,93)",
"rgb(116,196,118)",
"rgb(161,217,155)",
"rgb(199,233,192)",
"rgb(229,245,224)",
"rgb(247,252,245)",
]
Greys = ["rgb(0,0,0)", "rgb(255,255,255)"]
Hot = ["rgb(0,0,0)", "rgb(230,0,0)", "rgb(255,210,0)", "rgb(255,255,255)"]
Jet = [
"rgb(0,0,131)",
"rgb(0,60,170)",
"rgb(5,255,255)",
"rgb(255,255,0)",
"rgb(250,0,0)",
"rgb(128,0,0)",
]
Picnic = [
"rgb(0,0,255)",
"rgb(51,153,255)",
"rgb(102,204,255)",
"rgb(153,204,255)",
"rgb(204,204,255)",
"rgb(255,255,255)",
"rgb(255,204,255)",
"rgb(255,153,255)",
"rgb(255,102,204)",
"rgb(255,102,102)",
"rgb(255,0,0)",
]
Portland = [
"rgb(12,51,131)",
"rgb(10,136,186)",
"rgb(242,211,56)",
"rgb(242,143,56)",
"rgb(217,30,30)",
]
Rainbow = [
"rgb(150,0,90)",
"rgb(0,0,200)",
"rgb(0,25,255)",
"rgb(0,152,255)",
"rgb(44,255,150)",
"rgb(151,255,0)",
"rgb(255,234,0)",
"rgb(255,111,0)",
"rgb(255,0,0)",
]
RdBu = [
"rgb(5,10,172)",
"rgb(106,137,247)",
"rgb(190,190,190)",
"rgb(220,170,132)",
"rgb(230,145,90)",
"rgb(178,10,28)",
]
Reds = ["rgb(220,220,220)", "rgb(245,195,157)", "rgb(245,160,105)", "rgb(178,10,28)"]
Viridis = [
"#440154",
"#48186a",
"#472d7b",
"#424086",
"#3b528b",
"#33638d",
"#2c728e",
"#26828e",
"#21918c",
"#1fa088",
"#28ae80",
"#3fbc73",
"#5ec962",
"#84d44b",
"#addc30",
"#d8e219",
"#fde725",
]
YlGnBu = [
"rgb(8,29,88)",
"rgb(37,52,148)",
"rgb(34,94,168)",
"rgb(29,145,192)",
"rgb(65,182,196)",
"rgb(127,205,187)",
"rgb(199,233,180)",
"rgb(237,248,217)",
"rgb(255,255,217)",
]
YlOrRd = [
"rgb(128,0,38)",
"rgb(189,0,38)",
"rgb(227,26,28)",
"rgb(252,78,42)",
"rgb(253,141,60)",
"rgb(254,178,76)",
"rgb(254,217,118)",
"rgb(255,237,160)",
"rgb(255,255,204)",
]
Blackbody_r = Blackbody[::-1]
Bluered_r = Bluered[::-1]
Blues_r = Blues[::-1]
Cividis_r = Cividis[::-1]
Earth_r = Earth[::-1]
Electric_r = Electric[::-1]
Greens_r = Greens[::-1]
Greys_r = Greys[::-1]
Hot_r = Hot[::-1]
Jet_r = Jet[::-1]
Picnic_r = Picnic[::-1]
Portland_r = Portland[::-1]
Rainbow_r = Rainbow[::-1]
RdBu_r = RdBu[::-1]
Reds_r = Reds[::-1]
Viridis_r = Viridis[::-1]
YlGnBu_r = YlGnBu[::-1]
YlOrRd_r = YlOrRd[::-1]

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"""
Qualitative color sequences are appropriate for data that has no natural ordering, such \
as categories, colors, names, countries etc. The color sequences in this module are \
mostly meant to be passed in as the `color_discrete_sequence` argument to various functions.
"""
from ._swatches import _swatches
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
Plotly = [
"#636EFA",
"#EF553B",
"#00CC96",
"#AB63FA",
"#FFA15A",
"#19D3F3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52",
]
D3 = [
"#1F77B4",
"#FF7F0E",
"#2CA02C",
"#D62728",
"#9467BD",
"#8C564B",
"#E377C2",
"#7F7F7F",
"#BCBD22",
"#17BECF",
]
G10 = [
"#3366CC",
"#DC3912",
"#FF9900",
"#109618",
"#990099",
"#0099C6",
"#DD4477",
"#66AA00",
"#B82E2E",
"#316395",
]
T10 = [
"#4C78A8",
"#F58518",
"#E45756",
"#72B7B2",
"#54A24B",
"#EECA3B",
"#B279A2",
"#FF9DA6",
"#9D755D",
"#BAB0AC",
]
Alphabet = [
"#AA0DFE",
"#3283FE",
"#85660D",
"#782AB6",
"#565656",
"#1C8356",
"#16FF32",
"#F7E1A0",
"#E2E2E2",
"#1CBE4F",
"#C4451C",
"#DEA0FD",
"#FE00FA",
"#325A9B",
"#FEAF16",
"#F8A19F",
"#90AD1C",
"#F6222E",
"#1CFFCE",
"#2ED9FF",
"#B10DA1",
"#C075A6",
"#FC1CBF",
"#B00068",
"#FBE426",
"#FA0087",
]
Dark24 = [
"#2E91E5",
"#E15F99",
"#1CA71C",
"#FB0D0D",
"#DA16FF",
"#222A2A",
"#B68100",
"#750D86",
"#EB663B",
"#511CFB",
"#00A08B",
"#FB00D1",
"#FC0080",
"#B2828D",
"#6C7C32",
"#778AAE",
"#862A16",
"#A777F1",
"#620042",
"#1616A7",
"#DA60CA",
"#6C4516",
"#0D2A63",
"#AF0038",
]
Light24 = [
"#FD3216",
"#00FE35",
"#6A76FC",
"#FED4C4",
"#FE00CE",
"#0DF9FF",
"#F6F926",
"#FF9616",
"#479B55",
"#EEA6FB",
"#DC587D",
"#D626FF",
"#6E899C",
"#00B5F7",
"#B68E00",
"#C9FBE5",
"#FF0092",
"#22FFA7",
"#E3EE9E",
"#86CE00",
"#BC7196",
"#7E7DCD",
"#FC6955",
"#E48F72",
]
Alphabet_r = Alphabet[::-1]
D3_r = D3[::-1]
Dark24_r = Dark24[::-1]
G10_r = G10[::-1]
Light24_r = Light24[::-1]
Plotly_r = Plotly[::-1]
T10_r = T10[::-1]
from .colorbrewer import ( # noqa: E402 F401
Set1,
Pastel1,
Dark2,
Set2,
Pastel2,
Set3,
Set1_r,
Pastel1_r,
Dark2_r,
Set2_r,
Pastel2_r,
Set3_r,
)
from .carto import ( # noqa: E402 F401
Antique,
Bold,
Pastel,
Prism,
Safe,
Vivid,
Antique_r,
Bold_r,
Pastel_r,
Prism_r,
Safe_r,
Vivid_r,
)
__all__ = ["swatches"]

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"""
Sequential color scales are appropriate for most continuous data, but in some cases it \
can be helpful to use a `plotly.colors.diverging` or \
`plotly.colors.cyclical` scale instead. The color scales in this module are \
mostly meant to be passed in as the `color_continuous_scale` argument to various functions.
"""
from ._swatches import _swatches, _swatches_continuous
def swatches(template=None):
return _swatches(__name__, globals(), template)
swatches.__doc__ = _swatches.__doc__
def swatches_continuous(template=None):
return _swatches_continuous(__name__, globals(), template)
swatches_continuous.__doc__ = _swatches_continuous.__doc__
Plotly3 = [
"#0508b8",
"#1910d8",
"#3c19f0",
"#6b1cfb",
"#981cfd",
"#bf1cfd",
"#dd2bfd",
"#f246fe",
"#fc67fd",
"#fe88fc",
"#fea5fd",
"#febefe",
"#fec3fe",
]
Viridis = [
"#440154",
"#482878",
"#3e4989",
"#31688e",
"#26828e",
"#1f9e89",
"#35b779",
"#6ece58",
"#b5de2b",
"#fde725",
]
Cividis = [
"#00224e",
"#123570",
"#3b496c",
"#575d6d",
"#707173",
"#8a8678",
"#a59c74",
"#c3b369",
"#e1cc55",
"#fee838",
]
Inferno = [
"#000004",
"#1b0c41",
"#4a0c6b",
"#781c6d",
"#a52c60",
"#cf4446",
"#ed6925",
"#fb9b06",
"#f7d13d",
"#fcffa4",
]
Magma = [
"#000004",
"#180f3d",
"#440f76",
"#721f81",
"#9e2f7f",
"#cd4071",
"#f1605d",
"#fd9668",
"#feca8d",
"#fcfdbf",
]
Plasma = [
"#0d0887",
"#46039f",
"#7201a8",
"#9c179e",
"#bd3786",
"#d8576b",
"#ed7953",
"#fb9f3a",
"#fdca26",
"#f0f921",
]
Turbo = [
"#30123b",
"#4145ab",
"#4675ed",
"#39a2fc",
"#1bcfd4",
"#24eca6",
"#61fc6c",
"#a4fc3b",
"#d1e834",
"#f3c63a",
"#fe9b2d",
"#f36315",
"#d93806",
"#b11901",
"#7a0402",
]
Cividis_r = Cividis[::-1]
Inferno_r = Inferno[::-1]
Magma_r = Magma[::-1]
Plasma_r = Plasma[::-1]
Plotly3_r = Plotly3[::-1]
Turbo_r = Turbo[::-1]
Viridis_r = Viridis[::-1]
from .plotlyjs import ( # noqa: E402 F401
Blackbody,
Bluered,
Electric,
Hot,
Jet,
Rainbow,
Blackbody_r,
Bluered_r,
Electric_r,
Hot_r,
Jet_r,
Rainbow_r,
)
from .colorbrewer import ( # noqa: E402 F401
Blues,
BuGn,
BuPu,
GnBu,
Greens,
Greys,
OrRd,
Oranges,
PuBu,
PuBuGn,
PuRd,
Purples,
RdBu,
RdPu,
Reds,
YlGn,
YlGnBu,
YlOrBr,
YlOrRd,
Blues_r,
BuGn_r,
BuPu_r,
GnBu_r,
Greens_r,
Greys_r,
OrRd_r,
Oranges_r,
PuBu_r,
PuBuGn_r,
PuRd_r,
Purples_r,
RdBu_r,
RdPu_r,
Reds_r,
YlGn_r,
YlGnBu_r,
YlOrBr_r,
YlOrRd_r,
)
from .cmocean import ( # noqa: E402 F401
turbid,
thermal,
haline,
solar,
ice,
gray,
deep,
dense,
algae,
matter,
speed,
amp,
tempo,
turbid_r,
thermal_r,
haline_r,
solar_r,
ice_r,
gray_r,
deep_r,
dense_r,
algae_r,
matter_r,
speed_r,
amp_r,
tempo_r,
)
from .carto import ( # noqa: E402 F401
Burg,
Burgyl,
Redor,
Oryel,
Peach,
Pinkyl,
Mint,
Blugrn,
Darkmint,
Emrld,
Aggrnyl,
Bluyl,
Teal,
Tealgrn,
Purp,
Purpor,
Sunset,
Magenta,
Sunsetdark,
Agsunset,
Brwnyl,
Burg_r,
Burgyl_r,
Redor_r,
Oryel_r,
Peach_r,
Pinkyl_r,
Mint_r,
Blugrn_r,
Darkmint_r,
Emrld_r,
Aggrnyl_r,
Bluyl_r,
Teal_r,
Tealgrn_r,
Purp_r,
Purpor_r,
Sunset_r,
Magenta_r,
Sunsetdark_r,
Agsunset_r,
Brwnyl_r,
)
__all__ = ["swatches"]

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from io import BytesIO
import base64
from .png import Writer, from_array
try:
from PIL import Image
pil_imported = True
except ImportError:
pil_imported = False
def image_array_to_data_uri(img, backend="pil", compression=4, ext="png"):
"""Converts a numpy array of uint8 into a base64 png or jpg string.
Parameters
----------
img: ndarray of uint8
array image
backend: str
'auto', 'pil' or 'pypng'. If 'auto', Pillow is used if installed,
otherwise pypng.
compression: int, between 0 and 9
compression level to be passed to the backend
ext: str, 'png' or 'jpg'
compression format used to generate b64 string
"""
# PIL and pypng error messages are quite obscure so we catch invalid compression values
if compression < 0 or compression > 9:
raise ValueError("compression level must be between 0 and 9.")
alpha = False
if img.ndim == 2:
mode = "L"
elif img.ndim == 3 and img.shape[-1] == 3:
mode = "RGB"
elif img.ndim == 3 and img.shape[-1] == 4:
mode = "RGBA"
alpha = True
else:
raise ValueError("Invalid image shape")
if backend == "auto":
backend = "pil" if pil_imported else "pypng"
if ext != "png" and backend != "pil":
raise ValueError("jpg binary strings are only available with PIL backend")
if backend == "pypng":
ndim = img.ndim
sh = img.shape
if ndim == 3:
img = img.reshape((sh[0], sh[1] * sh[2]))
w = Writer(
sh[1], sh[0], greyscale=(ndim == 2), alpha=alpha, compression=compression
)
img_png = from_array(img, mode=mode)
prefix = "data:image/png;base64,"
with BytesIO() as stream:
w.write(stream, img_png.rows)
base64_string = prefix + base64.b64encode(stream.getvalue()).decode("utf-8")
else: # pil
if not pil_imported:
raise ImportError(
"pillow needs to be installed to use `backend='pil'. Please"
"install pillow or use `backend='pypng'."
)
pil_img = Image.fromarray(img)
if ext == "jpg" or ext == "jpeg":
prefix = "data:image/jpeg;base64,"
ext = "jpeg"
else:
prefix = "data:image/png;base64,"
ext = "png"
with BytesIO() as stream:
pil_img.save(stream, format=ext, compress_level=compression)
base64_string = prefix + base64.b64encode(stream.getvalue()).decode("utf-8")
return base64_string

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class PlotlyError(Exception):
pass
class PlotlyEmptyDataError(PlotlyError):
pass
class PlotlyGraphObjectError(PlotlyError):
def __init__(self, message="", path=(), notes=()):
"""
General graph object error for validation failures.
:param (str|unicode) message: The error message.
:param (iterable) path: A path pointing to the error.
:param notes: Add additional notes, but keep default exception message.
"""
self.message = message
self.plain_message = message # for backwards compat
self.path = list(path)
self.notes = notes
super(PlotlyGraphObjectError, self).__init__(message)
def __str__(self):
"""This is called by Python to present the error message."""
format_dict = {
"message": self.message,
"path": "[" + "][".join(repr(k) for k in self.path) + "]",
"notes": "\n".join(self.notes),
}
return "{message}\n\nPath To Error: {path}\n\n{notes}".format(**format_dict)
class PlotlyDictKeyError(PlotlyGraphObjectError):
def __init__(self, obj, path, notes=()):
"""See PlotlyGraphObjectError.__init__ for param docs."""
format_dict = {"attribute": path[-1], "object_name": obj._name}
message = "'{attribute}' is not allowed in '{object_name}'".format(
**format_dict
)
notes = [obj.help(return_help=True)] + list(notes)
super(PlotlyDictKeyError, self).__init__(
message=message, path=path, notes=notes
)
class PlotlyDictValueError(PlotlyGraphObjectError):
def __init__(self, obj, path, notes=()):
"""See PlotlyGraphObjectError.__init__ for param docs."""
format_dict = {"attribute": path[-1], "object_name": obj._name}
message = "'{attribute}' has invalid value inside '{object_name}'".format(
**format_dict
)
notes = [obj.help(path[-1], return_help=True)] + list(notes)
super(PlotlyDictValueError, self).__init__(
message=message, notes=notes, path=path
)
class PlotlyListEntryError(PlotlyGraphObjectError):
def __init__(self, obj, path, notes=()):
"""See PlotlyGraphObjectError.__init__ for param docs."""
format_dict = {"index": path[-1], "object_name": obj._name}
message = "Invalid entry found in '{object_name}' at index, '{index}'".format(
**format_dict
)
notes = [obj.help(return_help=True)] + list(notes)
super(PlotlyListEntryError, self).__init__(
message=message, path=path, notes=notes
)
class PlotlyDataTypeError(PlotlyGraphObjectError):
def __init__(self, obj, path, notes=()):
"""See PlotlyGraphObjectError.__init__ for param docs."""
format_dict = {"index": path[-1], "object_name": obj._name}
message = "Invalid entry found in '{object_name}' at index, '{index}'".format(
**format_dict
)
note = "It's invalid because it doesn't contain a valid 'type' value."
notes = [note] + list(notes)
super(PlotlyDataTypeError, self).__init__(
message=message, path=path, notes=notes
)
class PlotlyKeyError(KeyError):
"""
KeyErrors are not printed as beautifully as other errors (this is so that
{}[''] prints "KeyError: ''" and not "KeyError:"). So here we use
LookupError's __str__ to make a PlotlyKeyError object which will print nicer
error messages for KeyErrors.
"""
def __str__(self):
return LookupError.__str__(self)

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import os
PLOTLY_DIR = os.environ.get(
"PLOTLY_DIR", os.path.join(os.path.expanduser("~"), ".plotly")
)
TEST_FILE = os.path.join(PLOTLY_DIR, ".permission_test")
def _permissions():
try:
if not os.path.exists(PLOTLY_DIR):
try:
os.mkdir(PLOTLY_DIR)
except Exception:
# in case of race
if not os.path.isdir(PLOTLY_DIR):
raise
with open(TEST_FILE, "w") as f:
f.write("testing\n")
try:
os.remove(TEST_FILE)
except Exception:
pass
return True
except Exception: # Do not trap KeyboardInterrupt.
return False
_file_permissions = None
def ensure_writable_plotly_dir():
# Cache permissions status
global _file_permissions
if _file_permissions is None:
_file_permissions = _permissions()
return _file_permissions

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import importlib
def relative_import(parent_name, rel_modules=(), rel_classes=()):
"""
Helper function to import submodules lazily in Python 3.7+
Parameters
----------
rel_modules: list of str
list of submodules to import, of the form .submodule
rel_classes: list of str
list of submodule classes/variables to import, of the form ._submodule.Foo
Returns
-------
tuple
Tuple that should be assigned to __all__, __getattr__ in the caller
"""
module_names = {rel_module.split(".")[-1]: rel_module for rel_module in rel_modules}
class_names = {rel_path.split(".")[-1]: rel_path for rel_path in rel_classes}
def __getattr__(import_name):
# In Python 3.7+, lazy import submodules
# Check for submodule
if import_name in module_names:
rel_import = module_names[import_name]
return importlib.import_module(rel_import, parent_name)
# Check for submodule class
if import_name in class_names:
rel_path_parts = class_names[import_name].split(".")
rel_module = ".".join(rel_path_parts[:-1])
class_name = import_name
class_module = importlib.import_module(rel_module, parent_name)
return getattr(class_module, class_name)
raise AttributeError(
"module {__name__!r} has no attribute {name!r}".format(
name=import_name, __name__=parent_name
)
)
__all__ = list(module_names) + list(class_names)
def __dir__():
return __all__
return __all__, __getattr__, __dir__

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"""
Stand-alone module to provide information about whether optional deps exist.
"""
from importlib import import_module
import logging
import sys
logger = logging.getLogger(__name__)
_not_importable = set()
def get_module(name, should_load=True):
"""
Return module or None. Absolute import is required.
:param (str) name: Dot-separated module path. E.g., 'scipy.stats'.
:raise: (ImportError) Only when exc_msg is defined.
:return: (module|None) If import succeeds, the module will be returned.
"""
if not should_load:
return sys.modules.get(name, None)
if name not in _not_importable:
try:
return import_module(name)
except ImportError:
_not_importable.add(name)
except Exception:
_not_importable.add(name)
msg = f"Error importing optional module {name}"
logger.exception(msg)
return None

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import base64
import decimal
import json as _json
import sys
import re
from functools import reduce
from _plotly_utils.optional_imports import get_module
from _plotly_utils.basevalidators import (
ImageUriValidator,
copy_to_readonly_numpy_array,
is_homogeneous_array,
)
int8min = -128
int8max = 127
int16min = -32768
int16max = 32767
int32min = -2147483648
int32max = 2147483647
uint8max = 255
uint16max = 65535
uint32max = 4294967295
plotlyjsShortTypes = {
"int8": "i1",
"uint8": "u1",
"int16": "i2",
"uint16": "u2",
"int32": "i4",
"uint32": "u4",
"float32": "f4",
"float64": "f8",
}
def to_typed_array_spec(v):
"""
Convert numpy array to plotly.js typed array spec
If not possible return the original value
"""
v = copy_to_readonly_numpy_array(v)
# Skip b64 encoding if numpy is not installed,
# or if v is not a numpy array, or if v is empty
np = get_module("numpy", should_load=False)
if not np or not isinstance(v, np.ndarray) or v.size == 0:
return v
dtype = str(v.dtype)
# convert default Big Ints until we could support them in plotly.js
if dtype == "int64":
max = v.max()
min = v.min()
if max <= int8max and min >= int8min:
v = v.astype("int8")
elif max <= int16max and min >= int16min:
v = v.astype("int16")
elif max <= int32max and min >= int32min:
v = v.astype("int32")
else:
return v
elif dtype == "uint64":
max = v.max()
min = v.min()
if max <= uint8max and min >= 0:
v = v.astype("uint8")
elif max <= uint16max and min >= 0:
v = v.astype("uint16")
elif max <= uint32max and min >= 0:
v = v.astype("uint32")
else:
return v
dtype = str(v.dtype)
if dtype in plotlyjsShortTypes:
arrObj = {
"dtype": plotlyjsShortTypes[dtype],
"bdata": base64.b64encode(v).decode("ascii"),
}
if v.ndim > 1:
arrObj["shape"] = str(v.shape)[1:-1]
return arrObj
return v
def is_skipped_key(key):
"""
Return whether the key is skipped for conversion to the typed array spec
"""
skipped_keys = ["geojson", "layer", "layers", "range"]
return any(skipped_key == key for skipped_key in skipped_keys)
def convert_to_base64(obj):
if isinstance(obj, dict):
for key, value in obj.items():
if is_skipped_key(key):
continue
elif is_homogeneous_array(value):
obj[key] = to_typed_array_spec(value)
else:
convert_to_base64(value)
elif isinstance(obj, list) or isinstance(obj, tuple):
for value in obj:
convert_to_base64(value)
def cumsum(x):
"""
Custom cumsum to avoid a numpy import.
"""
def _reducer(a, x):
if len(a) == 0:
return [x]
return a + [a[-1] + x]
ret = reduce(_reducer, x, [])
return ret
class PlotlyJSONEncoder(_json.JSONEncoder):
"""
Meant to be passed as the `cls` kwarg to json.dumps(obj, cls=..)
See PlotlyJSONEncoder.default for more implementation information.
Additionally, this encoder overrides nan functionality so that 'Inf',
'NaN' and '-Inf' encode to 'null'. Which is stricter JSON than the Python
version.
"""
def coerce_to_strict(self, const):
"""
This is used to ultimately *encode* into strict JSON, see `encode`
"""
# before python 2.7, 'true', 'false', 'null', were include here.
if const in ("Infinity", "-Infinity", "NaN"):
return None
else:
return const
def encode(self, o):
"""
Load and then dump the result using parse_constant kwarg
Note that setting invalid separators will cause a failure at this step.
"""
# this will raise errors in a normal-expected way
encoded_o = super(PlotlyJSONEncoder, self).encode(o)
# Brute force guessing whether NaN or Infinity values are in the string
# We catch false positive cases (e.g. strings such as titles, labels etc.)
# but this is ok since the intention is to skip the decoding / reencoding
# step when it's completely safe
if not ("NaN" in encoded_o or "Infinity" in encoded_o):
return encoded_o
# now:
# 1. `loads` to switch Infinity, -Infinity, NaN to None
# 2. `dumps` again so you get 'null' instead of extended JSON
try:
new_o = _json.loads(encoded_o, parse_constant=self.coerce_to_strict)
except ValueError:
# invalid separators will fail here. raise a helpful exception
raise ValueError(
"Encoding into strict JSON failed. Did you set the separators "
"valid JSON separators?"
)
else:
return _json.dumps(
new_o,
sort_keys=self.sort_keys,
indent=self.indent,
separators=(self.item_separator, self.key_separator),
)
def default(self, obj):
"""
Accept an object (of unknown type) and try to encode with priority:
1. builtin: user-defined objects
2. sage: sage math cloud
3. pandas: dataframes/series
4. numpy: ndarrays
5. datetime: time/datetime objects
Each method throws a NotEncoded exception if it fails.
The default method will only get hit if the object is not a type that
is naturally encoded by json:
Normal objects:
dict object
list, tuple array
str, unicode string
int, long, float number
True true
False false
None null
Extended objects:
float('nan') 'NaN'
float('infinity') 'Infinity'
float('-infinity') '-Infinity'
Therefore, we only anticipate either unknown iterables or values here.
"""
# TODO: The ordering if these methods is *very* important. Is this OK?
encoding_methods = (
self.encode_as_plotly,
self.encode_as_sage,
self.encode_as_numpy,
self.encode_as_pandas,
self.encode_as_datetime,
self.encode_as_date,
self.encode_as_list, # because some values have `tolist` do last.
self.encode_as_decimal,
self.encode_as_pil,
)
for encoding_method in encoding_methods:
try:
return encoding_method(obj)
except NotEncodable:
pass
return _json.JSONEncoder.default(self, obj)
@staticmethod
def encode_as_plotly(obj):
"""Attempt to use a builtin `to_plotly_json` method."""
try:
return obj.to_plotly_json()
except AttributeError:
raise NotEncodable
@staticmethod
def encode_as_list(obj):
"""Attempt to use `tolist` method to convert to normal Python list."""
if hasattr(obj, "tolist"):
return obj.tolist()
else:
raise NotEncodable
@staticmethod
def encode_as_sage(obj):
"""Attempt to convert sage.all.RR to floats and sage.all.ZZ to ints"""
sage_all = get_module("sage.all")
if not sage_all:
raise NotEncodable
if obj in sage_all.RR:
return float(obj)
elif obj in sage_all.ZZ:
return int(obj)
else:
raise NotEncodable
@staticmethod
def encode_as_pandas(obj):
"""Attempt to convert pandas.NaT / pandas.NA"""
pandas = get_module("pandas", should_load=False)
if not pandas:
raise NotEncodable
if obj is pandas.NaT:
return None
# pandas.NA was introduced in pandas 1.0
if hasattr(pandas, "NA") and obj is pandas.NA:
return None
raise NotEncodable
@staticmethod
def encode_as_numpy(obj):
"""Attempt to convert numpy.ma.core.masked"""
numpy = get_module("numpy", should_load=False)
if not numpy:
raise NotEncodable
if obj is numpy.ma.core.masked:
return float("nan")
elif isinstance(obj, numpy.ndarray) and obj.dtype.kind == "M":
try:
return numpy.datetime_as_string(obj).tolist()
except TypeError:
pass
raise NotEncodable
@staticmethod
def encode_as_datetime(obj):
"""Convert datetime objects to iso-format strings"""
try:
return obj.isoformat()
except AttributeError:
raise NotEncodable
@staticmethod
def encode_as_date(obj):
"""Attempt to convert to utc-iso time string using date methods."""
try:
time_string = obj.isoformat()
except AttributeError:
raise NotEncodable
else:
return iso_to_plotly_time_string(time_string)
@staticmethod
def encode_as_decimal(obj):
"""Attempt to encode decimal by converting it to float"""
if isinstance(obj, decimal.Decimal):
return float(obj)
else:
raise NotEncodable
@staticmethod
def encode_as_pil(obj):
"""Attempt to convert PIL.Image.Image to base64 data uri"""
image = get_module("PIL.Image")
if image is not None and isinstance(obj, image.Image):
return ImageUriValidator.pil_image_to_uri(obj)
else:
raise NotEncodable
class NotEncodable(Exception):
pass
def iso_to_plotly_time_string(iso_string):
"""Remove timezone info and replace 'T' delimeter with ' ' (ws)."""
# make sure we don't send timezone info to plotly
if (iso_string.split("-")[:3] == "00:00") or (iso_string.split("+")[0] == "00:00"):
raise Exception(
"Plotly won't accept timestrings with timezone info.\n"
"All timestrings are assumed to be in UTC."
)
iso_string = iso_string.replace("-00:00", "").replace("+00:00", "")
if iso_string.endswith("T00:00:00"):
return iso_string.replace("T00:00:00", "")
else:
return iso_string.replace("T", " ")
def template_doc(**names):
def _decorator(func):
if not sys.version_info[:2] == (3, 2):
if func.__doc__ is not None:
func.__doc__ = func.__doc__.format(**names)
return func
return _decorator
def _natural_sort_strings(vals, reverse=False):
def key(v):
v_parts = re.split(r"(\d+)", v)
for i in range(len(v_parts)):
try:
v_parts[i] = int(v_parts[i])
except ValueError:
# not an int
pass
return tuple(v_parts)
return sorted(vals, key=key, reverse=reverse)
def _get_int_type():
np = get_module("numpy", should_load=False)
if np:
int_type = (int, np.integer)
else:
int_type = (int,)
return int_type
def split_multichar(ss, chars):
"""
Split all the strings in ss at any of the characters in chars.
Example:
>>> ss = ["a.string[0].with_separators"]
>>> chars = list(".[]_")
>>> split_multichar(ss, chars)
['a', 'string', '0', '', 'with', 'separators']
:param (list) ss: A list of strings.
:param (list) chars: Is a list of chars (note: not a string).
"""
if len(chars) == 0:
return ss
c = chars.pop()
ss = reduce(lambda x, y: x + y, map(lambda x: x.split(c), ss))
return split_multichar(ss, chars)
def split_string_positions(ss):
"""
Given a list of strings split using split_multichar, return a list of
integers representing the indices of the first character of every string in
the original string.
Example:
>>> ss = ["a.string[0].with_separators"]
>>> chars = list(".[]_")
>>> ss_split = split_multichar(ss, chars)
>>> ss_split
['a', 'string', '0', '', 'with', 'separators']
>>> split_string_positions(ss_split)
[0, 2, 9, 11, 12, 17]
:param (list) ss: A list of strings.
"""
return list(
map(
lambda t: t[0] + t[1],
zip(range(len(ss)), cumsum([0] + list(map(len, ss[:-1])))),
)
)
def display_string_positions(p, i=None, offset=0, length=1, char="^", trim=True):
"""
Return a string that is whitespace except at p[i] which is replaced with char.
If i is None then all the indices of the string in p are replaced with char.
Example:
>>> ss = ["a.string[0].with_separators"]
>>> chars = list(".[]_")
>>> ss_split = split_multichar(ss, chars)
>>> ss_split
['a', 'string', '0', '', 'with', 'separators']
>>> ss_pos = split_string_positions(ss_split)
>>> ss[0]
'a.string[0].with_separators'
>>> display_string_positions(ss_pos,4)
' ^'
>>> display_string_positions(ss_pos,4,offset=1,length=3,char="~",trim=False)
' ~~~ '
>>> display_string_positions(ss_pos)
'^ ^ ^ ^^ ^'
:param (list) p: A list of integers.
:param (integer|None) i: Optional index of p to display.
:param (integer) offset: Allows adding a number of spaces to the replacement.
:param (integer) length: Allows adding a replacement that is the char
repeated length times.
:param (str) char: allows customizing the replacement character.
:param (boolean) trim: trims the remaining whitespace if True.
"""
s = [" " for _ in range(max(p) + 1 + offset + length)]
maxaddr = 0
if i is None:
for p_ in p:
for temp in range(length):
maxaddr = p_ + offset + temp
s[maxaddr] = char
else:
for temp in range(length):
maxaddr = p[i] + offset + temp
s[maxaddr] = char
ret = "".join(s)
if trim:
ret = ret[: maxaddr + 1]
return ret
def chomp_empty_strings(strings, c, reverse=False):
"""
Given a list of strings, some of which are the empty string "", replace the
empty strings with c and combine them with the closest non-empty string on
the left or "" if it is the first string.
Examples:
for c="_"
['hey', '', 'why', '', '', 'whoa', '', ''] -> ['hey_', 'why__', 'whoa__']
['', 'hi', '', "I'm", 'bob', '', ''] -> ['_', 'hi_', "I'm", 'bob__']
['hi', "i'm", 'a', 'good', 'string'] -> ['hi', "i'm", 'a', 'good', 'string']
Some special cases are:
[] -> []
[''] -> ['']
['', ''] -> ['_']
['', '', '', ''] -> ['___']
If reverse is true, empty strings are combined with closest non-empty string
on the right or "" if it is the last string.
"""
def _rev(vals):
return [s[::-1] for s in vals][::-1]
if reverse:
return _rev(chomp_empty_strings(_rev(strings), c))
if not len(strings):
return strings
if sum(map(len, strings)) == 0:
return [c * (len(strings) - 1)]
class _Chomper:
def __init__(self, c):
self.c = c
def __call__(self, x, y):
# x is list up to now
# y is next item in list
# x should be [""] initially, and then empty strings filtered out at the
# end
if len(y) == 0:
return x[:-1] + [x[-1] + self.c]
else:
return x + [y]
return list(filter(len, reduce(_Chomper(c), strings, [""])))
# taken from
# https://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance#Python
def levenshtein(s1, s2):
if len(s1) < len(s2):
return levenshtein(s2, s1) # len(s1) >= len(s2)
if len(s2) == 0:
return len(s1)
previous_row = range(len(s2) + 1)
for i, c1 in enumerate(s1):
current_row = [i + 1]
for j, c2 in enumerate(s2):
# j+1 instead of j since previous_row and current_row are one character longer
# than s2
insertions = previous_row[j + 1] + 1
deletions = current_row[j] + 1
substitutions = previous_row[j] + (c1 != c2)
current_row.append(min(insertions, deletions, substitutions))
previous_row = current_row
return previous_row[-1]
def find_closest_string(string, strings):
def _key(s):
# sort by levenshtein distance and lexographically to maintain a stable
# sort for different keys with the same levenshtein distance
return (levenshtein(s, string), s)
return sorted(strings, key=_key)[0]