Merge branch 'main' into overwrite_option

.github/workflows/test.yml

@@ -22,7 +22,7 @@ jobs:
           python-version: 3.8
           cache-dependency-path: "**/pyproject.toml"
           cache: "pip"
-      
+
       - name: Get Example Dataset Cache
         uses: actions/cache@v3
         with:

src/ark/analysis/spatial_analysis.py

@@ -11,7 +11,7 @@
 from tqdm.notebook import tqdm
 
 import ark.settings as settings
-from ark.utils import spatial_analysis_utils
+from ark.analysis import spatial_analysis_utils
 
 
 def generate_channel_spatial_enrichment_stats(label_dir, dist_mat_dir, marker_thresholds, all_data,

src/ark/segmentation/marker_quantification.py

@@ -10,7 +10,7 @@
 import ark.settings as settings
 from ark.segmentation.regionprops_extraction import REGIONPROPS_FUNCTION
 from ark.segmentation.signal_extraction import EXTRACTION_FUNCTION
-from ark.utils import segmentation_utils
+from ark.segmentation import segmentation_utils
 
 
 def get_single_compartment_props(segmentation_labels, regionprops_base,

src/ark/utils/data_utils.py

@@ -421,71 +421,6 @@ def generate_and_save_neighborhood_cluster_masks(fovs: List[str],
             neigh_mask_progress.update(1)
 
 
-# TODO: Add metadata for channel name (eliminates need for fixed-order channels)
-def generate_deepcell_input(data_dir, tiff_dir, nuc_channels, mem_channels, fovs,
-                            is_mibitiff=False, img_sub_folder="TIFs", dtype="int16"):
-    """Saves nuclear and membrane channels into deepcell input format.
-    Either nuc_channels or mem_channels should be specified.
-
-    Writes summed channel images out as multitiffs (channels first).
-
-    Args:
-        data_dir (str):
-            location to save deepcell input tifs
-        tiff_dir (str):
-            directory containing folders of images, is_mibitiff determines what type
-        nuc_channels (list):
-            nuclear channels to be summed over
-        mem_channels (list):
-            membrane channels to be summed over
-        fovs (list):
-            list of folders to or MIBItiff files to load imgs from
-        is_mibitiff (bool):
-            if the images are of type MIBITiff
-        img_sub_folder (str):
-            if is_mibitiff is False, define the image subfolder for each fov
-            ignored if is_mibitiff is True
-        dtype (str/type):
-            optional specifier of image type.  Overwritten with warning for float images
-    Raises:
-        ValueError:
-            Raised if nuc_channels and mem_channels are both None or empty
-    """
-
-    # cannot have no nuclear and no membrane channels
-    if not nuc_channels and not mem_channels:
-        raise ValueError('Either nuc_channels or mem_channels should be non-empty.')
-
-    # define the channels list by combining nuc_channels and mem_channels
-    channels = (nuc_channels if nuc_channels else []) + (mem_channels if mem_channels else [])
-
-    # filter channels for None (just in case)
-    channels = [channel for channel in channels if channel is not None]
-
-    for fov in fovs:
-        # load the images in the current fov batch
-        if is_mibitiff:
-            data_xr = load_utils.load_imgs_from_mibitiff(
-                tiff_dir, mibitiff_files=[fov], channels=channels
-            )
-        else:
-            data_xr = load_utils.load_imgs_from_tree(
-                tiff_dir, img_sub_folder=img_sub_folder, fovs=[fov], channels=channels
-            )
-
-        fov_name = data_xr.fovs.values[0]
-        out = np.zeros((2, data_xr.shape[1], data_xr.shape[2]), dtype=data_xr.dtype)
-
-        # sum over channels and add to output
-        if nuc_channels:
-            out[0] = np.sum(data_xr.loc[fov_name, :, :, nuc_channels].values, axis=2)
-        if mem_channels:
-            out[1] = np.sum(data_xr.loc[fov_name, :, :, mem_channels].values, axis=2)
-
-        save_path = os.path.join(data_dir, f"{fov_name}.tiff")
-        image_utils.save_image(save_path, out)
-
-
 def split_img_stack(stack_dir, output_dir, stack_list, indices, names, channels_first=True):
     """Splits the channels in a given directory of images into separate files
 

src/ark/utils/deepcell_service_utils.py

@@ -14,7 +14,7 @@
 from requests.exceptions import RetryError
 from requests.packages.urllib3.util import Retry
 from tifffile import imread
-from alpineer import image_utils, io_utils, misc_utils
+from alpineer import image_utils, io_utils, misc_utils, load_utils
 from tqdm.notebook import tqdm
 
 
@@ -326,6 +326,71 @@ def run_deepcell_direct(input_dir, output_dir, host='https://deepcell.org',
     return 0
 
 
+# TODO: Add metadata for channel name (eliminates need for fixed-order channels)
+def generate_deepcell_input(data_dir, tiff_dir, nuc_channels, mem_channels, fovs,
+                            is_mibitiff=False, img_sub_folder="TIFs", dtype="int16"):
+    """Saves nuclear and membrane channels into deepcell input format.
+    Either nuc_channels or mem_channels should be specified.
+
+    Writes summed channel images out as multitiffs (channels first).
+
+    Args:
+        data_dir (str):
+            location to save deepcell input tifs
+        tiff_dir (str):
+            directory containing folders of images, is_mibitiff determines what type
+        nuc_channels (list):
+            nuclear channels to be summed over
+        mem_channels (list):
+            membrane channels to be summed over
+        fovs (list):
+            list of folders to or MIBItiff files to load imgs from
+        is_mibitiff (bool):
+            if the images are of type MIBITiff
+        img_sub_folder (str):
+            if is_mibitiff is False, define the image subfolder for each fov
+            ignored if is_mibitiff is True
+        dtype (str/type):
+            optional specifier of image type.  Overwritten with warning for float images
+    Raises:
+        ValueError:
+            Raised if nuc_channels and mem_channels are both None or empty
+    """
+
+    # cannot have no nuclear and no membrane channels
+    if not nuc_channels and not mem_channels:
+        raise ValueError('Either nuc_channels or mem_channels should be non-empty.')
+
+    # define the channels list by combining nuc_channels and mem_channels
+    channels = (nuc_channels if nuc_channels else []) + (mem_channels if mem_channels else [])
+
+    # filter channels for None (just in case)
+    channels = [channel for channel in channels if channel is not None]
+
+    for fov in fovs:
+        # load the images in the current fov batch
+        if is_mibitiff:
+            data_xr = load_utils.load_imgs_from_mibitiff(
+                tiff_dir, mibitiff_files=[fov], channels=channels
+            )
+        else:
+            data_xr = load_utils.load_imgs_from_tree(
+                tiff_dir, img_sub_folder=img_sub_folder, fovs=[fov], channels=channels
+            )
+
+        fov_name = data_xr.fovs.values[0]
+        out = np.zeros((2, data_xr.shape[1], data_xr.shape[2]), dtype=data_xr.dtype)
+
+        # sum over channels and add to output
+        if nuc_channels:
+            out[0] = np.sum(data_xr.loc[fov_name, :, :, nuc_channels].values, axis=2)
+        if mem_channels:
+            out[1] = np.sum(data_xr.loc[fov_name, :, :, mem_channels].values, axis=2)
+
+        save_path = os.path.join(data_dir, f"{fov_name}.tiff")
+        image_utils.save_image(save_path, out)
+
+
 def _convert_deepcell_seg_masks(seg_mask: bytes) -> np.ndarray:
     """Converts the segmentation masks provided by deepcell from `np.float32` to `inp.nt32`.
 

templates/1_Segment_Image_Data.ipynb

@@ -30,9 +30,9 @@
     "import xarray as xr\n",
     "from alpineer import io_utils\n",
     "\n",
-    "from ark.segmentation import marker_quantification\n",
-    "from ark.utils import (data_utils, deepcell_service_utils, example_dataset,\n",
-    "                       plot_utils, segmentation_utils)"
+    "from ark.segmentation import marker_quantification, segmentation_utils\n",
+    "from ark.utils import (deepcell_service_utils, example_dataset,\n",
+    "                       plot_utils)"
    ]
   },
   {
@@ -213,9 +213,9 @@
    },
    "outputs": [],
    "source": [
-    "# generate and save deepcell input tifs\n",
+    "# generate and save deepcell input tiffs\n",
     "# set img_sub_folder param to None if the image files in tiff_dir are not in a separate sub folder \n",
-    "data_utils.generate_deepcell_input(\n",
+    "deepcell_service_utils.generate_deepcell_input(\n",
     "    deepcell_input_dir,\n",
     "    tiff_dir,\n",
     "    nucs,\n",