Coverage for src/colorspace/hcl_palettes.py: 100%
52 statements
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3def divergingx_palettes(n = 5, **kwargs):
4 """Diverging X HCL Palettes
6 Returns pre-defined 'diverging xtra' color palettes based on the HCL
7 (Hue-Chroma-Luminance) color model.
9 Args:
10 n (int): number of colors used when plotting, defaults to `5`.
11 **kwargs: forwarded to :py:func:`hcl_palettes`. For a list and description
12 of available arguments see the description of :py:func:`hcl_palettes`.
14 Return:
15 See :py:func:`hcl_palettes`.
17 Examples:
18 >>> from colorspace import divergingx_palettes
19 >>>
20 >>> # Get palettes
21 >>> divergingx_palettes()
22 >>>
23 >>> #: Visualize palettes
24 >>> divergingx_palettes(n = 15, ncol = 2, plot = True, figsize = (7, 5));
25 """
27 from .hcl_palettes import hcl_palettes
28 return hcl_palettes(n = n, **kwargs, files_regex = ".*divergingx.*")
31def hcl_palettes(n = 5, type_ = None, name = None, plot = False, custom = None, ncol = 4, **kwargs):
32 """Pre-Defined HCL Palettes
34 Function to retrieve and/or display pre-defined color palettes based on the
35 HCL (Hue-Chroma-Luminance) color model, excludes 'diverging xtra'
36 (see :py:func:`divergingx_palettes`).
38 The inputs `type_` and `name` can be used to retrieve a custom subset,
39 `custom` can be used to add custom palettes if if needed.
41 If `plot = True`, `**kwargs` can be used to specify the figure size of the resulting
42 image by specifying `figsize = (height, width)` where both, `height`
43 and `width` must be int/float, specifying the height and width in inches.
44 Note that `matplotlib` must be installed when `plot = True`.
47 Args:
48 n (int): The number of colors to be plotted, defaults to `7`.
49 Only used if `plot = True`.
50 type_ (None, str, list): Given a str or a list of str,
51 only a subset of all available default color maps will
52 returned/displayed. Can be used in combination with input argument
53 `name`. Uses partial matching, not case sensitive.
54 name (None, str, list): Similar to `type_`. If not specified
55 all palettes will be returned. Can be set to a str or a list of
56 str containing the names of the palettes which should be
57 returned/plotted.
58 plot (bool): If `False` (default) an object of type
59 :py:class:`hclpalettes <colorspace.palettes.hclpalettes>` is returned, containing the
60 (subset) of pre-defined HCL color palettes.
61 custom (defaultpalette): One or multiple
62 defaultpalettes can be provided in addition.
63 ncol (int): Positive int, number of columns, defaults to `4`.
64 **kwargs: Forwarded to the main
65 :py:func:`swatchplot <colorspace.swatchplot.swatchplot>`
66 function if `plot = True`.
68 Returns:
69 Object of type `hclpalettes` or a `matplotlib.figure.Figure` object. If `plot = True`
70 a plot will be created and the figure handler returned. If `plot = False` (default)
71 an object of class :py:class:`hclpalettes <colorspace.palettes.hclpalettes>` is returned.
73 Raises:
74 TypeError: If `n`/`ncol` not of type int.
75 TypeError: If `type_` is not None or str.
76 TypeError: If not is bool `plot`.
77 TypeError: In case `custom` is an invalid input.
78 ValueError: If `n` or `ncol` are not positive.
79 Exception: If no palettes can be found matching the `type_` argument.
81 Examples:
83 Basic usage:
85 >>> from colorspace import hcl_palettes
86 >>> # Get all pre-defined HCL palettes shipped with the package
87 >>> hcl_palettes()
88 >>> #: Get all diverging HCL palettes (basic and advanced)
89 >>> hcl_palettes(type_ = "Diverging")
90 >>> #: Get only basic diverging HCL palettes
91 >>> hcl_palettes(type_ = "Basic: Diverging")
92 >>> #: Get specific HCL palettes by name
93 >>> hcl_palettes(name = ["Oranges", "Tropic"])
94 >>>
95 >>> #: Visualize all diverging HCL palettes
96 >>> hcl_palettes(type_ = "Diverging", ncol = 2,
97 >>> plot = True, figsize = (6, 4));
98 >>> #: Visualize specific palettes selected by name
99 >>> hcl_palettes(name = ["Oranges", "Tropic"],
100 >>> plot = True, ncol = 1, figsize = (6, 2));
101 >>>
102 >>> #: Specify number of colors shown
103 >>> hcl_palettes(n = 5, type_ = "Basic: Diverging",
104 >>> plot = True, ncol = 1, figsize = (6, 3));
105 >>> #:
106 >>> hcl_palettes(n = 51, type_ = "Advanced: Diverging",
107 >>> plot = True, ncol = 1, figsize = (6, 8));
108 >>>
109 >>> #: Extract specific palettes after loading
110 >>> palettes = hcl_palettes()
111 >>> c1 = palettes.get_palette("Oranges")
112 >>> c1
113 >>> #:
114 >>> c2 = palettes.get_palette("Greens")
115 >>> c2
116 >>>
117 >>> #: Modify palettes by overwriting palette settings
118 >>> c1.set(h1 = 99, l2 = 30, l1 = 30)
119 >>> c1.rename("Custom Palette #1")
120 >>> c2.set(h1 = -30, l1 = 40, l2 = 30, c1 = 30, c2 = 40)
121 >>> c2.rename("Custom Palette #2")
122 >>>
123 >>> # Visualize customized palettes
124 >>> hcl_palettes(type_ = "Custom", custom = [c1, c2],
125 >>> plot = True, ncol = 1, figsize = (6, 1));
127 """
129 # Loading pre-defined palettes from within the package
130 from . import hclpalettes
131 # Loading palettes. Ignore all files labeled 'divergingx' in some way as long
132 # as no files_regex is provided on **kwargs
133 files_regex = "(?!.*divergingx.*)" if not "files_regex" in kwargs.keys() else kwargs["files_regex"]
134 pals = hclpalettes(files_regex = files_regex)
136 # Sanity type checks
137 if not isinstance(n, int): raise TypeError("argument `n` must be int")
138 if not isinstance(ncol, int): raise TypeError("argument `ncol` must be int")
139 if not isinstance(type_, (type(None), str)):
140 raise TypeError("Argument 'type_' must be None (default) or str.")
141 if not isinstance(plot, bool): raise TypeError("argument `plot` must be bool")
143 # Sanity value checks
144 if not n > 0 or not ncol > 0: raise ValueError("arguments `n` and `ncol` must be positive int")
146 # If custom palettes have been added: add them as well (if
147 # the types are correct, of course).
148 if not custom is None:
149 from numpy import all
150 from .palettes import defaultpalette
151 def customerror():
152 import inspect
153 str = "List with custom palettes provided to {:s}".format(inspect.stack()[0][3])
154 str += " but not all elements are of type defaultpalette"
155 raise TypeError(str)
157 if isinstance(custom, defaultpalette):
158 pals._palettes_["Custom"] = [custom]
159 # Check if all inputs are of correct type
160 elif isinstance(custom, list):
161 if not all([isinstance(x, defaultpalette) for x in custom]): customerror()
162 pals._palettes_["Custom"] = custom
163 # Else append pals._palettes_["Custom"] = custom
164 else:
165 raise TypeError("argument `custom` not one of the allowed types")
168 if not type_ is None:
169 if isinstance(type_, str): type_ = [type_]
171 # Drop palettes from hclpalettes object not requested
172 # by the user.
173 for t in pals.get_palette_types():
174 if not any([x.upper() in t.upper() for x in type_]):
175 del pals._palettes_[t]
176 else:
177 type_ = pals.get_palette_types()
179 # Now dropping all color maps not matching a name, if the
180 # user has set a name.
181 if not name is None:
182 if isinstance(name, str): name = [name]
183 # Looping over palette types
184 for t in pals.get_palette_types():
185 palettenames = [p.name() for p in pals.get_palettes(t)]
186 drop = []
187 for i in range(0, len(palettenames)):
188 if not palettenames[i] in name: drop.append(i)
189 # Drop all?
190 if len(drop) == len(palettenames):
191 del pals._palettes_[t]
192 else:
193 drop.sort(reverse = True)
194 for i in drop: del pals._palettes_[t][i]
196 # No palettes survived the selection above?
197 if len(pals.get_palettes()) == 0:
198 raise Exception(f"no palettes found matching one of: {', '.join(type_)}")
200 # Return if plot is not required
201 if not plot:
202 return pals
203 else:
204 from .swatchplot import swatchplot
205 from numpy import ceil
206 nrow = int(ceil((pals.length() + len(pals.get_palette_types())) / ncol))
207 return swatchplot(pals, nrow = nrow, n = n, **kwargs)