SCMCP

from scmcp.util import add_op_log from scmcp.tool.util import mark_var, list_var, list_obs, check_gene, merge_adata, run_util_func import anndata import numpy as np from functools import partial import pandas as pd def test_add_op_log(): # Create a simple AnnData object for testing adata = anndata.AnnData(X=np.array([[1, 2], [3, 4]])) # Test case 1: Adding operation log when there's no initial record def test_func1(): pass add_op_log(adata, test_func1, {"param1": "value1"}) # Verify operation record is correctly created assert "operation" in adata.uns assert "adata" in adata.uns["operation"] assert len(adata.uns["operation"]["adata"]) == 1 assert "0" in adata.uns["operation"]["adata"] assert "test_func1" in adata.uns["operation"]["adata"]["0"] assert adata.uns["operation"]["adata"]["0"]["test_func1"] == {"param1": "value1"} # Test case 2: Adding operation log when there's existing record def test_func2(): pass add_op_log(adata, test_func2, {"param2": "value2"}) # Verify new operation record is correctly added assert len(adata.uns["operation"]["adata"]) == 2 assert "1" in adata.uns["operation"]["adata"] assert "test_func2" in adata.uns["operation"]["adata"]["1"] assert adata.uns["operation"]["adata"]["1"]["test_func2"] == {"param2": "value2"} # Test case 3: Using partial function test_partial = partial(test_func1, extra_arg="value") add_op_log(adata, test_partial, {"param3": "value3"}) # Verify operation record is correctly added when using partial function assert len(adata.uns["operation"]["adata"]) == 3 assert "2" in adata.uns["operation"]["adata"] assert "test_func1" in adata.uns["operation"]["adata"]["2"] assert adata.uns["operation"]["adata"]["2"]["test_func1"] == {"param3": "value3"} def test_mark_var(): # Create a test AnnData object with gene names var_names = ['MT-1', 'MT-2', 'RPS1', 'RPL2', 'HBA1', 'GENE1'] adata = anndata.AnnData( X=np.random.rand(3, len(var_names)), var=pd.DataFrame(index=var_names) ) # Test mitochondrial gene marking result = mark_var(adata, gene_class="mitochondrion") assert "mt" in adata.var.columns assert adata.var["mt"].sum() == 2 # Two MT genes assert "mt" in result assert "msg" in result # Test ribosomal gene marking result = mark_var(adata, gene_class="ribosomal") assert "ribo" in adata.var.columns assert adata.var["ribo"].sum() == 2 # Two ribosomal genes # Test hemoglobin gene marking result = mark_var(adata, gene_class="hemoglobin") assert "hb" in adata.var.columns assert adata.var["hb"].sum() == 1 # One hemoglobin gene # Test custom pattern (startswith) result = mark_var(adata, var_name="custom_start", pattern_type="startswith", patterns="GE") assert "custom_start" in adata.var.columns assert adata.var["custom_start"].sum() == 1 # One gene starting with GE # Test custom pattern (contains) result = mark_var(adata, var_name="custom_contains", pattern_type="contains", patterns="PS") assert "custom_contains" in adata.var.columns assert adata.var["custom_contains"].sum() == 1 # One gene containing PS def test_list_var(): # Create a test AnnData object with var columns adata = anndata.AnnData( X=np.random.rand(3, 4), var=pd.DataFrame({ "gene_type": ["protein_coding"] * 4, "chromosome": ["chr1"] * 4 }) ) # Test listing var columns result = list_var(adata) assert isinstance(result, list) assert "gene_type" in result assert "chromosome" in result assert len(result) == 2 def test_list_obs(): # Create a test AnnData object with obs columns adata = anndata.AnnData( X=np.random.rand(3, 4), obs=pd.DataFrame({ "cell_type": ["T-cell"] * 3, "condition": ["control"] * 3 }) ) # Test listing obs columns result = list_obs(adata) assert isinstance(result, list) assert "cell_type" in result assert "condition" in result assert len(result) == 2 def test_check_gene(): # Create a test AnnData object with specific gene names var_names = ['GENE1', 'GENE2', 'GENE3'] adata = anndata.AnnData( X=np.random.rand(3, len(var_names)), var=pd.DataFrame(index=var_names) ) # Test checking existing and non-existing genes result = check_gene(adata, var_names=['GENE1', 'GENE4']) assert isinstance(result, dict) assert result['GENE1'] is True assert result['GENE4'] is False def test_merge_adata(): # Create two test AnnData objects adata1 = anndata.AnnData( X=np.random.rand(3, 4), obs=pd.DataFrame(index=['cell1', 'cell2', 'cell3']), var=pd.DataFrame(index=['gene1', 'gene2', 'gene3', 'gene4']) ) adata2 = anndata.AnnData( X=np.random.rand(2, 4), obs=pd.DataFrame(index=['cell4', 'cell5']), var=pd.DataFrame(index=['gene1', 'gene2', 'gene3', 'gene4']) ) # Test merging AnnData objects adata_dict = {'adata1': adata1, 'adata2': adata2} result = merge_adata(adata_dict) assert isinstance(result, anndata.AnnData) assert result.n_obs == 5 # 3 + 2 cells assert result.n_vars == 4 # Same genes class MockAnnDataStore: def __init__(self): self.adata_dic = {} self.active = None def test_run_util_func(): # Create a mock AnnDataStore ads = MockAnnDataStore() # Create a test AnnData object var_names = ['MT-1', 'GENE1'] adata = anndata.AnnData( X=np.random.rand(3, len(var_names)), var=pd.DataFrame(index=var_names) ) # Set up the mock AnnDataStore ads.active = "test_adata" ads.adata_dic["test_adata"] = adata # Test running mark_var function result = run_util_func(ads, "mark_var", {"gene_class": "mitochondrion"}) assert "mt" in result assert "msg" in result assert "mt" in ads.adata_dic["test_adata"].var.columns # Test running list_var function result = run_util_func(ads, "list_var", {}) assert isinstance(result, list) assert "mt" in result # Test running check_gene function result = run_util_func(ads, "check_gene", {"var_names": ["MT-1", "NONEXISTENT"]}) assert result["MT-1"] is True assert result["NONEXISTENT"] is False # Test running merge_adata function adata2 = anndata.AnnData( X=np.random.rand(2, len(var_names)), var=pd.DataFrame(index=var_names) ) ads.adata_dic["test_adata2"] = adata2 result = run_util_func(ads, "merge_adata", {}) assert isinstance(result, anndata.AnnData) assert ads.active == "merge_adata" assert "merge_adata" in ads.adata_dic assert len(ads.adata_dic) == 1 # Only the merged adata remains assert ads.adata_dic["merge_adata"].n_obs == 5 # 3 + 2 cells