Colorbar in Python. Fast and lightweight!
Project description
colorbar
Add a colorbar to an image in milliseconds (faster than plt.imshow
+plt.colorbar
) 💨
colorbar
achieves its speed by avoiding matplotlib
and instead using numpy
, pillow
, cmap
and pycairo
!
🛠️ Install via: pip install colorbar
(+ if pycairo causes trouble try conda install anaconda::pycairo
)
Usage 💡
import numpy as np
from colorbar import CBar
shape = (400, 800)
im = np.linspace(0, 1, shape[0] * shape[1]).reshape(*shape) # dummy image
cbar = CBar(cmap='gray', # see https://cmap-docs.readthedocs.io/en/latest/catalog/
vmin=im.min(), # pixels <= vmin become first color of cmap
vmax=im.max()) # pixels >= vmax become last color of cmap
im_cbar = cbar.draw(im) # draw colorbar!
im_cbar.show()
draw()
returns a PIL.Image
that is shown via show()
and saved via save()
im_cbar.save('cbar.png')
Use cbar.save()
instead of im=cbar.draw()
+im.save()
to save the image as a vector graphic
...
cbar.save('cbar.pdf', im) # .pdf, .svg, .ps or .eps
To customize the colorbar, draw()
and save()
take the arguments:
vertical
: If True, colorbar is vertical. Default:True
pad
: Added pixel rows on the colorbar-side of the image. Default:0
pad_color
: Color-string of added pixels. Default:'k'
(=black)x
: Position of the colorbar center relative to image in width-direction. Default:.9
y
: Position of the colorbar center relative to image in length-direction. Default:.5
width
: Size of the colorbar relative to image. Default:.05
length
: Size of the colorbar relative to image. Default:.8
label
: Label above the colorbar. Default:None
ticks
: List (e.g.[0, 1]
) or dict (e.g.{0: 'low', 1: 'high'}
) of ticks. Default:None
fontsize
: Fontsize of labels and ticks. Default:20
linecolor
: Color of the lines and the font used to write labels and ticks. Default:w
(=white)linewidth
: Width of ticklines and outlines. Default:2
tick_len
: Length of ticklines. Default:2
Finally, if you want draw()
to return a numpy
array use asarray=True
im_cbar = cbar.draw(im, asarray=True)
to e.g. plot it with matplotlib
via plt.imshow(im_cbar)
.
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