Load cmap

`pypalettes.load_cmap`

`load_cmap(name='random', cmap_type='discrete', reverse=False, keep_first_n=None, keep_last_n=None, keep=None, repeat=1, shuffle=False, remove=None)`

Load a matplotlib colormap from one of the 2500+ available palettes.

You can find all valid palette names here

Parameters:

Name	Type	Description	Default
`name`	`Union[str, list[str]]`	Name of the palette	`'random'`
`cmap_type`	`str`	Type of colormap: 'continuous' or 'discrete'	`'discrete'`
`reverse`	`bool`	Whether to reverse the order of the colors or not	`False`
`keep_first_n`	`Optional[int]`	Keep only the first n colors of the palette	`None`
`keep`	`Optional[list[bool]]`	Specify which colors to keep in the palette	`None`
`repeat`	`int`	The number of times the palette must be present in the output. Used to access larger palettes that are repeated.	`1`
`shuffle`	`Union[bool, int]`	Used to mix the order of colors. If an integer is supplied, it will be used as the seed.	`False`
`remove`	`Optional[Union[int, list[int]]]`	Remove colors at specified indices (0-indexed). Can be a single int or list of ints. For example, remove=2 removes the 3rd color, remove=[1, 3] removes the 2nd and 4th colors.	`None`

Returns:

Type	Description
`Union[LinearSegmentedColormap, ListedColormap]`	A matplotlib colormap.

Examples

# mkdocs: render
import matplotlib.pyplot as plt
import numpy as np
from pypalettes import load_cmap

np.random.seed(0)
data = np.random.randn(20, 20)

cmap = load_cmap("Sunset", cmap_type="continuous")

plt.imshow(
   X=data,
   cmap=cmap
)
plt.colorbar()

# mkdocs: render
import matplotlib.pyplot as plt
import numpy as np
from pypalettes import load_cmap

np.random.seed(0)
data = np.random.randn(20, 20)

cmap = load_cmap("Acadia", cmap_type="continuous")

plt.imshow(
   X=data,
   cmap=cmap
)
plt.colorbar()

# mkdocs: render
import matplotlib.pyplot as plt
import numpy as np
from pypalettes import load_cmap

np.random.seed(0)
data = np.random.randn(20, 20)

cmap = load_cmap("Acanthurus_olivaceus", cmap_type="continuous")

plt.imshow(
   X=data,
   cmap=cmap
)
plt.colorbar()

See all palettes