diff --git a/README.md b/README.md
index c039945..53e364c 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,10 @@
# Scientific color maps
+## Blog post
+
+[Scicomap Medium blog post (free)](https://towardsdatascience.com/your-colour-map-is-bad-heres-how-to-fix-it-lessons-learnt-from-the-event-horizon-telescope-b82523f09469)
+
## Installation
```shell
@@ -97,7 +101,7 @@ import scicomap as sc
import matplotlib.pyplot as plt
# the thing that should not be
-ugly_jet = plt.get_cmap("YlOrBr")
+ugly_jet = plt.get_cmap("jet")
sc_map = sc.ScicoMiscellaneous(cmap=ugly_jet)
f=sc_map.assess_cmap(figsize=(22,10))
```
@@ -219,6 +223,74 @@ which render as
 |
+# Use with matplotlib
+
+## Use a corrected colormap in a matplotlib figure
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+import scicomap as sc
+from scicomap.utils import _fn_with_roots
+
+# load the color map
+div_map = sc.ScicoDiverging(cmap='watermelon')
+
+# correct the colormap
+div_map.unif_sym_cmap(lift=15,
+ bitonic=False,
+ diffuse=True)
+
+# get the fixed color map
+fixed_cmap = div_map.get_mpl_color_map()
+print(type(fixed_cmap))
+
+# use it as you like
+im = _fn_with_roots()
+norm = mpl.colors.CenteredNorm()
+divnorm = mpl.colors.TwoSlopeNorm(vmin=-1, vcenter=0, vmax=1.25)
+fig = plt.figure(figsize=(3,3), facecolor="white")
+ax = fig.add_subplot(1, 1, 1, facecolor="white")
+pos = ax.imshow(im, cmap=fixed_cmap, aspect="auto", norm=divnorm)
+fig.colorbar(pos, ax=ax);
+```
+ |
+
+## Correct a matplotlib colormap
+
+
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+import scicomap as sc
+from scicomap.utils import _fn_with_roots
+
+# load the color map
+mpl_cmap_obj = plt.get_cmap("PRGn")
+div_map = sc.ScicoDiverging(cmap=mpl_cmap_obj)
+
+# correct the colormap
+div_map.unif_sym_cmap(lift=None,
+ bitonic=False,
+ diffuse=True)
+
+# get the fixed color map
+fixed_cmap = div_map.get_mpl_color_map()
+print(type(fixed_cmap))
+
+# use it as you like
+im = _fn_with_roots()
+norm = mpl.colors.CenteredNorm()
+divnorm = mpl.colors.TwoSlopeNorm(vmin=-1, vcenter=0, vmax=1.25)
+fig = plt.figure(figsize=(3,3), facecolor="white")
+ax = fig.add_subplot(1, 1, 1, facecolor="white")
+pos = ax.imshow(im, cmap=fixed_cmap, aspect="auto", norm=divnorm)
+fig.colorbar(pos, ax=ax);
+```
+
+ |
+
# Comparing color maps
You can easily compare, raw or corrected, color maps using a picture of your choice
@@ -353,6 +425,11 @@ sc.plot_colormap(ctype='qualitative',
# Changes log
+### 0.3
+
+ - Add a section "how to use with matplotlib"
+ - [Bug] Center diverging color map in examples
+
### 0.2
- [Bug] Fix typo in chart titles
diff --git a/pics/mpl.png b/pics/mpl.png
new file mode 100644
index 0000000..c735bbb
Binary files /dev/null and b/pics/mpl.png differ
diff --git a/pics/mpl2.png b/pics/mpl2.png
new file mode 100644
index 0000000..c58a0b6
Binary files /dev/null and b/pics/mpl2.png differ
diff --git a/scicomap/__init__.py b/scicomap/__init__.py
index 144390f..af3fe56 100644
--- a/scicomap/__init__.py
+++ b/scicomap/__init__.py
@@ -3,7 +3,7 @@
from . import cmath
from . import cblind
-__version__ = "0.2"
+__version__ = "0.3"
__all__ = ["scicomap", "datasets", "cmath", "cblind", "utils"]
# bound to upper level
diff --git a/scicomap/scicomap.py b/scicomap/scicomap.py
index 17f2a4c..b5ac477 100644
--- a/scicomap/scicomap.py
+++ b/scicomap/scicomap.py
@@ -577,7 +577,8 @@ def draw_example(self, facecolor="black", figsize=(20, 20)):
arr_3d=[(xpyr, ypyr, zpyr), (per_x, per_z, per_z)],
figsize=figsize,
facecolor=facecolor,
- cname=self.cname)
+ cname=self.cname,
+ norm=True)
return fig
@@ -747,7 +748,8 @@ def draw_example(self, facecolor="black", figsize=(20, 20)):
arr_3d=[(xpyr, ypyr, zpyr), (per_x, per_z, per_z)],
figsize=figsize,
facecolor=facecolor,
- cname=self.cname)
+ cname=self.cname,
+ norm=True)
return fig
diff --git a/scicomap/utils.py b/scicomap/utils.py
index 92c950e..799fa49 100644
--- a/scicomap/utils.py
+++ b/scicomap/utils.py
@@ -1,5 +1,6 @@
import itertools
import numpy as np
+import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from matplotlib.colors import ListedColormap
@@ -151,7 +152,7 @@ def _plot_e_field(ax, cmap, n_neg_charges=2, facecolor="black", title=False):
return ax
-def _plot_examples(color_map, images, arr_3d, figsize, facecolor, cname, cblind=True):
+def _plot_examples(color_map, images, arr_3d, figsize, facecolor, cname, cblind=True, norm=False):
"""Create the figure based on the provided images, continuous colormaps"""
fig = plt.figure(figsize=figsize, facecolor=facecolor)
n_images = len(images)
@@ -167,6 +168,7 @@ def _plot_examples(color_map, images, arr_3d, figsize, facecolor, cname, cblind=
idx_3d = 0
n_rows = len(c_maps)
n_cols = len(images)
+
for c_map, im in itertools.product(c_maps, images):
if isinstance(im, str) and ('3D' in im):
@@ -186,8 +188,9 @@ def _plot_examples(color_map, images, arr_3d, figsize, facecolor, cname, cblind=
ax = fig.add_subplot(n_rows, n_cols, axi, facecolor=facecolor)
ax = _plot_complex_arg(ax, c_map, facecolor, title=axi <= n_cols)
else:
+ cmap_norm = mpl.colors.CenteredNorm() if norm else None
ax = fig.add_subplot(n_rows, n_cols, axi, facecolor=facecolor)
- ax.imshow(im, cmap=c_map, aspect="auto")
+ ax.imshow(im, cmap=c_map, aspect="auto", norm=cmap_norm)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.set_title(sub_title[axi - 1], color=title_color, fontsize=16, loc="left")
diff --git a/setup.py b/setup.py
index 59e7adf..609616b 100644
--- a/setup.py
+++ b/setup.py
@@ -27,7 +27,7 @@
setup(
name="scicomap",
- version="0.2",
+ version="0.3",
description="Scientific color maps",
long_description=README,
long_description_content_type="text/markdown",