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custom_color_palette/creates_custom_palette.py

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+# -*- coding: utf-8 -*-
+#-----------------------------------------------------------------------------------------------------------------------------------
+'''
+Description: Creates python custom colors palette
+Author: Joao Henry Huaman Chinchay
+E-mail: [email protected]
+Created date: Sep 07, 2019
+Modification date: Jan 12, 2021
+'''
+#-----------------------------------------------------------------------------------------------------------------------------------
+import numpy as np
+from matplotlib.colors import LinearSegmentedColormap
+from matplotlib.colors import BoundaryNorm
+import sys
+#-----------------------------------------------------------------------------------------------------------------------------------
+
+def range(vmin,vmax,step):
+
+    """
+    Creates a range of numbers that include the extreme values.
+
+    Parameters
+    ----------
+    vmin: int or float
+        First value of sequence of numbers.
+
+    vmax: int or float
+        Last value of sequence of numbers.
+
+    step: int or float
+        Step used to create sequence of numbers between vmin and vmax.
+
+
+
+    Returns
+    -------
+    Return a numpy.ndarray with range of number between vmin and vmax.
+
+    """
+
+    ndec = 0
+
+    for item in [vmin,vmax,step]:
+        if isinstance(item,float):
+            dec = len(str(item).split('.')[1])
+            if dec > ndec:
+                ndec = dec
+
+    values = np.arange(vmin*(10**ndec),vmax*(10**ndec)+step*(10**ndec),step*(10**ndec))/(10**ndec)
+    return np.trunc(values*10**ndec)/(10**ndec)
+
+#-----------------------------------------------------------------------------------------------------------------------------------
+
+def creates_palette(Palette_Attr, extend='neither', lower_color=None, upper_color=None, nan_color=None):
+
+    """
+    Creates a custom color palette from color list.
+
+    Parameters
+    ----------
+    Palette_Attr : list
+        List that contains sublists with the characteristics of the
+        colors that will be used to create a custom color palette.
+        Each sublist must has three elements: [Colors, Limits, Stretch]
+
+        Colors : list or Matplotlib's Colormap
+            Defines the colors that will be used to create the
+            palette. Colors must be a Matplotlib's Colormap,
+            a list with Matplotlib's colors name,
+            a list with Hex color code or
+            a list with RGB color code.
+
+        Limits : list or numpy.ndarray
+            Defines the limits of each color of palette.
+
+        Stretch : list, optional
+            Optional list used to stretch the color palette
+            in order to obtain colors from a specific region.
+            Stretch must have 3 elements: [Values, Vini, Vfin]
+
+            Values : list or numpy.ndarray
+                Sequence of numbers that will be cut.
+
+            Vini : int or float
+                First value used to cut Values.
+
+            Vfin : int or float
+                Last value used to cut Values.
+
+            If Stretch is defined, the number of colors between
+            Vini and Vfin must be equal to Colors.
+
+
+    extend : str, default 'neither'
+        It is an optional parameter that is used to sets the extreme color of
+        palette. The valid options are 'neither', 'min', 'max', and
+        'both'.
+
+
+    lower_color : str, tuple, or None, default None
+        It defines lower color of palette.
+
+
+    upper_color : str, tuple, or None, default None
+        It defines upper color of palette.
+
+
+    nan_color : str, tuple, or None, default None
+        It defines color of nan values.
+
+
+
+    Returns
+    -------
+    Palette: object
+        Custom color palette
+
+    Ticks: list
+        Limits of each color in the palette.
+
+    Norm: class matplotlib.colors.BoundaryNorm
+        Norm of limits of each color.
+
+    Bounds: list
+        List with limits of each colors of Palette, including the extend values.
+
+    """
+
+    idxfin = len(Palette_Attr)-1
+    lowercolor = None
+    uppercolor = None
+
+    #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
+
+    for idx, subpalette in enumerate(Palette_Attr):
+        cols = subpalette[0]
+        levs = subpalette[1]
+
+        if isinstance(levs,np.ndarray)==False:
+            levs = np.array(levs)
+
+        addlowercol = 0
+        adduppercol = 0
+
+        if idx == 0 and ( extend == 'min' or extend == 'both'):
+            addlowercol = 1
+
+        if idx == idxfin and ( extend == 'max' or extend == 'both'):
+            adduppercol = 1
+
+        #  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .
+
+        if len(subpalette) == 3:
+            extlevs = subpalette[2][0]
+            vmin = subpalette[2][1]
+            vmax = subpalette[2][2]
+
+            if isinstance(extlevs,np.ndarray)==False:
+                extlevs = np.array(extlevs)
+
+            if [vmin] in list(extlevs):
+                argvmin = np.argwhere(vmin==extlevs)[0][0]
+            else:
+                print('\n\t{} was not found in {}\n'.format(vmin,extlevs))
+                sys.exit()
+
+            if [vmax] in list(extlevs):
+                argvmax = np.argwhere(vmax==extlevs)[0][0]
+            else:
+                print('\n\t{} was not found in {}\n'.format(vmax,extlevs))
+                sys.exit()
+
+            levs2 = extlevs[argvmin:argvmax+1]
+
+            if levs.shape[0] != levs2.shape[0]:
+                print('\n\t{}  and  {} have not the same size\n'.format(levs,levs2))
+                sys.exit()
+
+        #  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .
+            ncolors = extlevs.shape[0]-1+addlowercol+adduppercol
+
+        else:
+            argvmin = 0
+            argvmax = levs.shape[0]-1
+            ncolors = levs.shape[0]-1+addlowercol+adduppercol
+
+        #  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .  .
+
+        if isinstance(cols,list):
+            if len(cols)==1:
+                cols = cols + cols
+            subccp = LinearSegmentedColormap.from_list(name='CCP', colors=cols, N=ncolors)(np.linspace(0.0,1.0,ncolors))
+        else:
+            subccp = cols(np.linspace(0.0,1.0,ncolors))
+
+        if addlowercol>0:
+            lowercolor = subccp[0]
+
+        if adduppercol>0:
+            uppercolor = subccp[-1]
+
+
+        subccp = subccp[addlowercol:ncolors-adduppercol]
+        subccp = subccp[argvmin:argvmax]
+
+
+        if idx == 0:
+            ccp = subccp
+            labs = levs
+        else:
+            ccp = np.vstack((ccp,subccp))
+            labs = np.concatenate((labs,levs[1:]))
+
+    #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
+
+    Palette = LinearSegmentedColormap.from_list('ccp', ccp, N=ccp.shape[0])
+    Norm = BoundaryNorm(labs, ncolors=Palette.N)
+    Ticks = list(labs)
+    Bounds = [Ticks[0]-1.0] + Ticks + [Ticks[-1]+1.0]
+
+
+    if isinstance(lowercolor,np.ndarray):
+        Palette.set_under(lowercolor)
+
+    if isinstance(uppercolor,np.ndarray):
+        Palette.set_over(uppercolor)
+
+    if lower_color != None:
+        Palette.set_under(lower_color)
+
+    if upper_color != None:
+        Palette.set_over(upper_color)
+
+    if nan_color != None:
+        Palette.set_bad(nan_color)
+
+    return Palette, Ticks, Norm, Bounds;
+
+#-----------------------------------------------------------------------------------------------------------------------------------
+
+