Add Jaccard Index Function (#150)

src/nuc2seg/benchmark.py

@@ -1,5 +1,6 @@
-import numpy as np
 import logging
+
+import numpy as np
 import tqdm
 
 logger = logging.getLogger(__name__)

src/nuc2seg/celltyping.py

@@ -1,14 +1,13 @@
-import tqdm
-import numpy as np
-import geopandas
 import anndata
-
+import geopandas
+import numpy as np
+import tqdm
 from kneed import KneeLocator
-
+from scipy.special import logsumexp
 from scipy.special import softmax
-from nuc2seg.xenium import logger
+
 from nuc2seg.data import CelltypingResults
-from scipy.special import logsumexp
+from nuc2seg.xenium import logger
 
 
 def aic_bic(gene_counts, expression_profiles, prior_probs):

src/nuc2seg/celltyping_test.py

@@ -1,3 +1,7 @@
+import geopandas
+import numpy as np
+from shapely import Polygon, Point
+
 from nuc2seg.celltyping import (
     fit_celltype_em_model,
     fit_celltyping_on_segments_and_transcripts,
@@ -6,10 +10,6 @@
     predict_celltypes_for_segments_and_transcripts,
     predict_celltype_probabilities_for_all_segments,
 )
-import numpy as np
-import geopandas
-from shapely import Polygon, Point
-from nuc2seg.data import CelltypingResults
 
 
 def test_fit_celltype_em_model():

src/nuc2seg/cli/autofluorescence_benchmark.py

@@ -3,11 +3,11 @@
 import os.path
 
 import nuc2seg.post_xenium_imaging
+from nuc2seg import benchmark
 from nuc2seg import log_config
+from nuc2seg import plotting
 from nuc2seg.data import SegmentationResults
 from nuc2seg.xenium import read_xenium_cell_segmentation_masks
-from nuc2seg import benchmark
-from nuc2seg import plotting
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/baysor_postprocess.py

@@ -21,8 +21,6 @@
     stitch_shapes,
     filter_baysor_shapes_to_most_significant_nucleus_overlap,
     read_baysor_shapefile,
-)
-from nuc2seg.segment import (
     convert_transcripts_to_anndata,
 )
 from nuc2seg.utils import get_tile_idx

src/nuc2seg/cli/baysor_postprocess_test.py

@@ -1,18 +1,18 @@
+import json
+import math
 import os
 import shutil
 import tempfile
-import json
-import geopandas as gpd
 from unittest import mock
+
 import anndata
-import pandas
+import geopandas as gpd
+import numpy as np
+from blended_tiling import TilingModule
 
+from nuc2seg.cli import baysor_postprocess
 from nuc2seg.data import CelltypingResults
 from nuc2seg.utils import generate_tiles
-from blended_tiling import TilingModule
-import numpy as np
-import math
-from nuc2seg.cli import baysor_postprocess
 
 
 def test_baysor_postprocess(

src/nuc2seg/cli/celltyping.py

@@ -1,14 +1,15 @@
 import argparse
 import logging
+
 import numpy as np
 
 from nuc2seg import log_config
+from nuc2seg.celltyping import fit_celltyping_on_segments_and_transcripts
 from nuc2seg.xenium import (
     load_nuclei,
     load_and_filter_transcripts_as_points,
     create_shapely_rectangle,
 )
-from nuc2seg.celltyping import fit_celltyping_on_segments_and_transcripts
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/combine_segmentations.py

@@ -1,26 +1,25 @@
 import argparse
 import logging
 import os.path
+from typing import Optional
 
 import anndata
 import geopandas as gpd
 import numpy as np
 import pandas
 import shapely
-from typing import Optional
-from shapely.geometry import Polygon
 from blended_tiling import TilingModule
+from shapely.geometry import Polygon
 
 from nuc2seg import log_config
-from nuc2seg.data import Nuc2SegDataset, SegmentationResults
+from nuc2seg.data import Nuc2SegDataset
 from nuc2seg.plotting import (
     plot_segmentation_class_assignment,
     celltype_histogram,
     celltype_area_violin,
 )
-from nuc2seg.segment import segmentation_array_to_shapefile
-from nuc2seg.utils import get_tile_idx, generate_tiles
 from nuc2seg.preprocessing import create_shapely_rectangle
+from nuc2seg.utils import get_tile_idx, generate_tiles
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/plot_predictions.py

@@ -1,8 +1,9 @@
 import argparse
 import logging
 import os.path
-import tqdm
+
 import numpy as np
+import tqdm
 
 from nuc2seg import log_config
 from nuc2seg.data import (
@@ -11,8 +12,8 @@
     ModelPredictions,
     SegmentationResults,
 )
-from nuc2seg.utils import generate_tiles
 from nuc2seg.plotting import plot_model_predictions
+from nuc2seg.utils import generate_tiles
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/preprocess.py

@@ -1,22 +1,23 @@
 import argparse
 import logging
-import pandas
 import os.path
 
-from nuc2seg import log_config
+import pandas
 from matplotlib import pyplot as plt
-from nuc2seg.xenium import (
-    load_nuclei,
-    load_and_filter_transcripts_as_points,
-    create_shapely_rectangle,
-)
+
+from nuc2seg import log_config
 from nuc2seg.celltyping import (
     select_best_celltyping_chain,
     predict_celltypes_for_segments_and_transcripts,
 )
-from nuc2seg.preprocessing import create_rasterized_dataset, create_nuc2seg_dataset
 from nuc2seg.data import CelltypingResults
 from nuc2seg.plotting import plot_celltype_estimation_results, rank_genes_groups_plot
+from nuc2seg.preprocessing import create_rasterized_dataset, create_nuc2seg_dataset
+from nuc2seg.xenium import (
+    load_nuclei,
+    load_and_filter_transcripts_as_points,
+    create_shapely_rectangle,
+)
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/preprocess_test.py

@@ -1,18 +1,12 @@
 import os
 import shutil
 import tempfile
-import json
-import geopandas as gpd
 from unittest import mock
-import anndata
-import pandas
 
-from nuc2seg.data import CelltypingResults, Nuc2SegDataset
-from nuc2seg.utils import generate_tiles
-from blended_tiling import TilingModule
 import numpy as np
-import math
+
 from nuc2seg.cli import preprocess
+from nuc2seg.data import CelltypingResults, Nuc2SegDataset
 
 
 def test_baysor_postprocess(

src/nuc2seg/cli/segment.py

@@ -13,8 +13,8 @@
 from nuc2seg.segment import (
     greedy_cell_segmentation,
     convert_segmentation_to_shapefile,
-    convert_transcripts_to_anndata,
 )
+from nuc2seg.postprocess import convert_transcripts_to_anndata
 from nuc2seg.xenium import (
     load_and_filter_transcripts_as_points,
 )

src/nuc2seg/cli/tile_dataset.py

@@ -2,10 +2,10 @@
 import logging
 
 from nuc2seg import log_config
+from nuc2seg.data import Nuc2SegDataset
 from nuc2seg.preprocessing import (
     tile_dataset_to_disk,
 )
-from nuc2seg.data import Nuc2SegDataset
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/tile_xenium.py

@@ -1,17 +1,18 @@
 import argparse
 import logging
-import pandas as pd
 import math
 
+import pandas as pd
+from shapely import box
+
 from nuc2seg import log_config
-from nuc2seg.xenium import (
-    load_and_filter_transcripts_as_table,
-)
 from nuc2seg.preprocessing import (
     tile_transcripts_to_disk,
     tile_nuclei_to_disk,
 )
-from shapely import box
+from nuc2seg.xenium import (
+    load_and_filter_transcripts_as_table,
+)
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/cli/train.py

@@ -1,14 +1,15 @@
 import argparse
 import logging
-import numpy as np
 import os.path
 
+import numpy as np
+from pytorch_lightning import Trainer
+from pytorch_lightning.callbacks import ModelCheckpoint
+from pytorch_lightning.loggers import WandbLogger
+
 from nuc2seg import log_config
 from nuc2seg.data import Nuc2SegDataset, TiledDataset, TrainTestSplit
 from nuc2seg.unet_model import SparseUNet, Nuc2SegDataModule
-from pytorch_lightning import Trainer, Callback
-from pytorch_lightning.loggers import WandbLogger
-from pytorch_lightning.callbacks import ModelCheckpoint
 
 logger = logging.getLogger(__name__)
 

src/nuc2seg/conftest.py

@@ -1,6 +1,6 @@
-import pytest
-import pandas
 import geopandas
+import pandas
+import pytest
 import shapely
 
 

src/nuc2seg/data.py

@@ -1,12 +1,12 @@
-import h5py
 import logging
-import torch
-import pandas
-import numpy as np
 
+import h5py
+import numpy as np
+import pandas
+import torch
+from blended_tiling import TilingModule
 from torch.nn.utils.rnn import pad_sequence
 from torch.utils.data import Dataset
-from blended_tiling import TilingModule
 
 from nuc2seg.utils import generate_tiles
 

src/nuc2seg/data_test.py

@@ -1,16 +1,18 @@
+import os.path
 import shutil
+import tempfile
+
+import numpy as np
 import pytest
+from blended_tiling import TilingModule
+
 from nuc2seg.data import (
     Nuc2SegDataset,
     TiledDataset,
     CelltypingResults,
     RasterizedDataset,
 )
 from nuc2seg.utils import generate_tiles
-import numpy as np
-import tempfile
-import os.path
-from blended_tiling import TilingModule
 
 
 @pytest.fixture(scope="package")

src/nuc2seg/evaluate.py

@@ -1,13 +1,13 @@
-import torch
 import numpy as np
+import torch
+import torch.nn.functional as F
+import tqdm
+from matplotlib import pyplot as plt
 from scipy.special import softmax, expit
 from torch import Tensor
-from matplotlib import pyplot as plt
-import tqdm
 
-from nuc2seg.preprocessing import pol2cart
 from nuc2seg.data import collate_tiles
-import torch.nn.functional as F
+from nuc2seg.preprocessing import pol2cart
 
 
 def dice_coeff(

src/nuc2seg/evaluate_test.py

@@ -1,3 +1,5 @@
+import torch
+
 from nuc2seg.evaluate import (
     dice_coeff,
     multiclass_dice_coeff,
@@ -6,7 +8,6 @@
     angle_accuracy,
     celltype_accuracy,
 )
-import torch
 
 
 def test_dice_coeff():

src/nuc2seg/plotting.py

@@ -3,19 +3,20 @@
 import geopandas
 import numpy as np
 import pandas
+import seaborn as sns
 import tqdm
 from matplotlib import cm, gridspec, animation
 from matplotlib import pyplot as plt
 from shapely import box
-import seaborn as sns
-from nuc2seg.segment import greedy_cell_segmentation
+
 from nuc2seg.data import (
     Nuc2SegDataset,
     ModelPredictions,
     SegmentationResults,
     CelltypingResults,
 )
 from nuc2seg.preprocessing import pol2cart
+from nuc2seg.segment import greedy_cell_segmentation
 
 
 def plot_tiling(bboxes, output_path):