Color swatches from color maps that are suitable for grayscale printing

README.md

@@ -90,3 +90,29 @@ plt.show()
 
 <!-- Links -->
 [poetry]: https://python-poetry.org
+
+
+## `generate_hex_colors`
+
+This function generates the hex numbers for the colours extracted from a `matplotlib` colour map based on the number of points of interest.
+The colors change gradually from bright to dark or vice versa.
+```python
+import matplotlib.pyplot as plt
+import cosmoplots
+
+axes_size = cosmoplots.set_rcparams_dynamo(plt.rcParams, num_cols=1, ls="thin")
+
+color_list = cosmoplots.generate_hex_colors(5, 'viridis', show_swatch=True, ascending=True)
+plt.savefig("./assets/hex_colors.png")
+
+# Print color_list to retrieve the hex numbers
+print(color_list) #['#fde725', '#5ec962', '#21918c', '#3b528b', '#440154']
+
+for i, color in enumerate(color_list):
+    plt.plot([1,2],[i,i+1], c = color)
+
+plt.savefig("./assets/hex_colors_example.png")
+```
+| `hex_colors.png` | hex_colors_example.png |
+| :--------: | :--------: | 
+| ![colors](./assets/hex_colors.png) | ![colors](./assets/hex_colors_example.png) |

cosmoplots/__init__.py

@@ -1,4 +1,5 @@
 from .figure_defs import *
 from .axes import *
+from .colors import *
 
 __version__ = "0.1.6"

cosmoplots/colors.py

@@ -0,0 +1,86 @@
+import numpy as np
+from colour import Color
+from matplotlib.colors import LinearSegmentedColormap
+import matplotlib.pyplot as plt
+from matplotlib import cm, colors
+from typing import List
+
+
+def make_color_swatch(color_list: list):
+    """
+    Generate plot of the desired color swatches. This is useful if you want to see what the swatches look like.
+    This function is used in generate_hex_colors() where the plot of the swatches will show by default if used in Jupyter Notebook.
+
+    Args:
+        color_list: list
+            List of colors from color map
+
+    Return:
+        color_swatch:
+            A plot of the color swatches
+    """
+
+    color_swatch = LinearSegmentedColormap.from_list(
+        "my_list", [Color(x).rgb for x in color_list]
+    )
+
+    plt.figure(figsize=(5, 3))
+    plt.imshow(
+        [list(np.arange(0, len(color_list), 1))],
+        interpolation="nearest",
+        origin="lower",
+        cmap=color_swatch,
+    )
+    plt.xticks([])
+    plt.yticks([])
+
+    return color_swatch
+
+
+def generate_hex_colors(
+    number_data_points: int,
+    color_map: str,
+    show_swatch: bool = True,
+    ascending: bool = True,
+) -> List[str]:
+    """
+    Function to generate colors picked out of the matplolib color maps as hex numbers.
+    If using this function in Jupyter Notebook, by default since show_swatch = True, a plot of the swatches will automatically appear.
+
+    Args:
+        number_data_points: int
+            The number of data points
+        color_map: str
+            The name of the colour map from matplotlib. Grayscale friendly colors are:
+            'viridis', 'plasma', 'inferno', 'magma', 'cubehelix', 'cividis'
+            See more here: https://matplotlib.org/stable/tutorials/colors/colormaps.html
+        show_swatch: bool = True
+            Show the color swatches based on the number of data points. 'True' means that a plot will show containing the swatches.
+        ascending: bool = True
+            Show the color swatches and list in ascending order, from light to dark. Set to True by default.
+
+    Returns:
+        color_list: List[str]
+            List of hex numbers from the desired color map. Simply do print(color_list) to get this list.
+
+    """
+
+    cmap = cm.get_cmap(color_map, number_data_points)
+
+    color_list = []
+
+    for i in range(cmap.N):
+        rgba = cmap(i)
+
+        # rgb2hex accepts rgb or rgba
+        color_list.append(colors.rgb2hex(rgba))
+
+    # return light to darkest if ascending
+    if ascending:
+        if show_swatch:
+            make_color_swatch(color_list[::-1])
+        return color_list[::-1]
+    else:
+        if show_swatch:
+            make_color_swatch(color_list)
+        return color_list

pyproject.toml

@@ -11,6 +11,7 @@ readme = 'README.md'
 python = ">=3.8"
 numpy = ">=1.15.0"
 matplotlib = ">=3.3.2"
+colour = ">=0.1.5"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]