added test cases for helper functions (#8)

* added test cases for helper functions; making copy of lists inside functions likely to have side effects

requirements.txt

@@ -1,9 +1,13 @@
 anndata>=0.7.6
 scanpy>=1.7.2
 POT==0.9.0
-numpy
-scipy
+numpy~=1.24.4
+scipy~=1.10.1
 scikit-learn>=0.24.0
 IPython>=7.18.1
-pytest
-
+pytest~=8.3.2
+seaborn~=0.13.2
+matplotlib~=3.7.5
+pandas~=2.0.3
+statsmodels~=0.14.1
+networkx~=3.1

src/paste/PASTE.py

@@ -3,7 +3,7 @@
 from anndata import AnnData
 import ot
 from sklearn.decomposition import NMF
-from .helper import intersect, kl_divergence_backend, to_dense_array, extract_data_matrix
+from paste.helper import intersect, kl_divergence_backend, to_dense_array, extract_data_matrix
 
 def pairwise_align(
     sliceA: AnnData, 

src/paste/__init__.py

@@ -1,3 +0,0 @@
-from .PASTE import pairwise_align, center_align, center_ot, center_NMF, my_fused_gromov_wasserstein, solve_gromov_linesearch
-from .helper import match_spots_using_spatial_heuristic, filter_for_common_genes, apply_trsf, intersect,extract_data_matrix, to_dense_array, kl_divergence_backend
-from .visualization import plot_slice, stack_slices_pairwise, stack_slices_center

src/paste/paste-cmd-line.py

@@ -4,7 +4,8 @@
 import pandas as pd
 import argparse
 import os
-from src.paste import pairwise_align, center_align, stack_slices_pairwise, stack_slices_center
+from paste.PASTE import pairwise_align, center_align
+from paste.visualization import stack_slices_pairwise, stack_slices_center
 
 def main(args):
     # print(args)
@@ -56,7 +57,7 @@ def main(args):
         pis_init = [pd.read_csv(args.start[i],index_col=0).to_numpy() for i in range(len(args.start))]
 
     # create output folder
-    output_path = os.path.join(args.direc, "../../paste_output")
+    output_path = os.path.join(args.direc, "paste_output")
     if not os.path.exists(output_path):
         os.mkdir(output_path)
 
@@ -82,8 +83,8 @@ def main(args):
         center_slice, pis = center_align(initial_slice, slices, lmbda, args.alpha, args.n_components, args.threshold, dissimilarity=args.cost, distributions=[slices[i].obsm['weights'] for i in range(n_slices)], pis_init=pis_init)
         W = pd.DataFrame(center_slice.uns['paste_W'], index = center_slice.obs.index)
         H = pd.DataFrame(center_slice.uns['paste_H'], columns = center_slice.var.index)
-        W.to_csv(os.path.join(args.direc, "../../paste_output/W_center"))
-        H.to_csv(os.path.join(args.direc, "../../paste_output/H_center"))
+        W.to_csv(os.path.join(args.direc, "paste_output/W_center"))
+        H.to_csv(os.path.join(args.direc, "paste_output/H_center"))
         for i in range(len(pis)):
             output_filename = "paste_output/slice_center_slice" + str(i+1) + "_pairwise.csv"
             pi = pd.DataFrame(pis[i], index = center_slice.obs.index, columns = slices[i].obs.index)

tests/conftest.py

@@ -2,7 +2,7 @@
 import numpy as np
 import scanpy as sc
 import pytest
-from src.paste import intersect
+from paste.helper import intersect
 
 test_dir = Path(__file__).parent
 input_dir = test_dir / "data/input"
@@ -27,6 +27,9 @@ def slices():
 
 @pytest.fixture(scope="session")
 def intersecting_slices(slices):
+    # Make a copy of the list
+    slices = list(slices)
+
     common_genes = slices[0].var.index
     for slice in slices[1:]:
         common_genes = intersect(common_genes, slice.var.index)