Plot the Results of the Noised Mouse Spleen Dataset

Packages Loading

import warnings
warnings.filterwarnings('ignore')

import matplotlib.pyplot as plt
import scanpy as sc

import sys
sys.path.append(r'../../../../')

Results Loading

adata_results = sc.read_h5ad(f'../../../Mouse_Thymus_Noised.h5ad')

adata_results.uns['MultiMAP_level_1_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#f9c74f', '#99582a', '#fdf0d5', '#ee6055']
adata_results.uns['MultiMAP_level_2_colors'] = ['#264653', '#ee6055', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#2a9d8f']
adata_results.uns['MultiMAP_level_3_colors'] = ['#264653', '#ee6055', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#2a9d8f']

adata_results.uns['SpatialGlue_level_1_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#99582a', '#fdf0d5', '#f9c74f', '#ee6055']
adata_results.uns['SpatialGlue_level_2_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#ee6055']
adata_results.uns['SpatialGlue_level_3_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#ee6055']

adata_results.uns['SpaKnit_level_1_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#ee6055']
adata_results.uns['SpaKnit_level_2_colors'] = ['#264653', '#2a9d8f', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#ee6055']
adata_results.uns['SpaKnit_level_3_colors'] = ['#2a9d8f', '#264653', '#83c5be', '#fdf0d5', '#99582a', '#f9c74f', '#ee6055']

Plot the Spatial Domain Identifications

plt.rcParams['font.sans-serif'] = ['Arial']

for result in adata_results.obs:
    color_key = f'{result}_colors'
    print(result)
    fig, ax = plt.subplots(1, 1, figsize=(6, 6))
    sc.pl.embedding(adata_results, basis='spatial', color=result, ax=ax, s=90, show=False, palette=adata_results.uns[color_key])
    ax.set_title(f"")
    ax.set_xlabel('')
    ax.set_ylabel('')
    ax.invert_yaxis()
    ax.get_legend().remove()

    # Hide axis borders
    for spine in ax.spines.values():
        spine.set_visible(False)

    # Adjust subplot parameters
    plt.subplots_adjust(left=0, right=1, top=1, bottom=0)
    plt.tight_layout()

    plt.savefig(f'{result}.png', dpi=500)
    plt.savefig(f'{result}.eps')

    plt.show()

SpatialGlue_level_1

SpatialGlue_level_2

SpatialGlue_level_3

SpaKnit_level_1

SpaKnit_level_2

SpaKnit_level_3

MultiMAP_level_1

MultiMAP_level_2

MultiMAP_level_3