Maximum intensity Projection (MIP) plot

Visualization of 3d categorical or numerical values with maximum intensity projection.

mip

[2]:

%matplotlib inline

import anndata
from spacipy import mip_spatial

[3]:

adata = anndata.read_h5ad('../_static/data/example.mipplot.h5ad')

[4]:

adata

[4]:

AnnData object with n_obs × n_vars = 1260 × 5
    obs: 'spc', 'x', 'y', 'z'

[5]:

adata.obs['spc'] = 'c' + adata.obs['spc'].astype(str)
adata.obs['spc'].unique()

[5]:

array(['c25', 'c28', 'c31', 'c19', 'c30', 'c29'], dtype=object)

[6]:

adata.uns['3d_spatial'] = adata.obs[['x', 'y', 'z']].values

[7]:

color_dict = {
    'c25': '#8c3bff',
    'c28': '#f2007b',
    'c31': '#15e18c',
    'c19': '#ff7ed1',
    'c30': '#bac389',
    'c29': '#ff7752'
    }

[8]:

mip_spatial(adata,
            color='spc',
            cmap=color_dict,
            ps=1
            )

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[9]:

adata.var

[9]:


SMESG000004222.1
SMESG000066476.1
SMESG000005043.1
SMESG000068488.1
SMESG000008973.1

[10]:

cyan = '#00FFFF'
magenta = '#FF00FF'
colors = [cyan, magenta]
genes = ['SMESG000008973.1', 'SMESG000005043.1']

mip_spatial(adata,
            color=genes,
            cmap=colors,
            ps=1
            )

<Figure size 886x274 with 0 Axes>

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