diff --git a/src/wela/imageviewer.py b/src/wela/imageviewer.py
index 75f5363fed233fc4da0580ff8b6e8015594b6f46..2a349f408bf6d3c9007b92ec13aacbe6e45551e0 100644
--- a/src/wela/imageviewer.py
+++ b/src/wela/imageviewer.py
@@ -161,7 +161,20 @@ class ImageViewer:
return tile_dict
def get_data_for_viewing(self, trap_id, tps, channels_to_skip):
- """Get images and outlines as multidimensional arrays for Napari."""
+ """
+ Get images and outlines as multidimensional arrays for Napari.
+
+ Returns
+ -------
+ ts_images: array
+ An array of images ordered by time points, channels, z stack,
+ x and y values.
+ ts_labels: array
+ An array of images of cell outlines ordered by time points,
+ z stack, x and y values.
+ channels: list of str
+ List of channel names.
+ """
# get outlines and tiles
outlines = self.get_outlines(trap_id, tps)
tiles_dict = self.get_tiles(trap_id, tps, channels_to_skip)
@@ -183,7 +196,65 @@ class ImageViewer:
ts_labels[tp_index, 0, ...] = outlines[tp_index]
return ts_images, ts_labels, channels
- def view(self, trap_id, tpt_end=10, tpt_start=0, channels_to_skip=None):
+ def concat(self, arrangement, image_dict, axis):
+ """
+ Concat dict of images into one image array.
+
+ Following the vertical layout in arrangment.
+ """
+ # concatenate vertically into a list
+ images_v = [
+ np.concatenate(
+ [image_dict[trap_id] for trap_id in v_stack], axis=axis
+ )
+ for v_stack in arrangement
+ ]
+ # concatenate horizontally into an array
+ if len(arrangement) > 1:
+ images = np.concatenate(
+ [image_v_stack for image_v_stack in images_v], axis=axis + 1
+ )
+ else:
+ images = images_v[0]
+ return images
+
+ def combine_tiles(self, ts_images_dict, ts_labels_dict, no_vertical_tiles):
+ """Combine tiles into one image first vertically then horizontally."""
+ no_tiles = len(ts_images_dict)
+ trap_ids = list(ts_images_dict.keys())
+ # find how tiles will be arranged in the concatenated image
+ if no_tiles < no_vertical_tiles:
+ arrangement = [trap_ids]
+ else:
+ arrangement = [
+ trap_ids[i : min(i + no_vertical_tiles, no_tiles)]
+ for i in range(
+ 0,
+ int(
+ np.floor(no_tiles / no_vertical_tiles)
+ * no_vertical_tiles
+ ),
+ no_vertical_tiles,
+ )
+ ]
+ if no_tiles > np.array(arrangement).size:
+ print(
+ f"Too many tiles: {no_tiles - np.array(arrangement).size}"
+ " will be ignored."
+ )
+ # concatenate images
+ ts_images = self.concat(arrangement, ts_images_dict, axis=3)
+ ts_labels = self.concat(arrangement, ts_labels_dict, axis=2)
+ return ts_images, ts_labels
+
+ def view(
+ self,
+ trap_ids,
+ tpt_end=10,
+ tpt_start=0,
+ channels_to_skip=None,
+ no_vertical_tiles=3,
+ ):
"""
Use Napari to view all channels and outlines for a particular trap.
@@ -200,10 +271,22 @@ class ImageViewer:
will be slow.
"""
tps = np.arange(tpt_start, tpt_end + 1)
- ts_images, ts_labels, channels = self.get_data_for_viewing(
- trap_id, tps, channels_to_skip
+ if isinstance(trap_ids, int):
+ trap_ids = [trap_ids]
+ ts_images_dict, ts_labels_dict = {}, {}
+ for trap_id in trap_ids:
+ ts_images_dict[trap_id], ts_labels_dict[trap_id], channels = (
+ self.get_data_for_viewing(trap_id, tps, channels_to_skip)
+ )
+ # combine tiles
+ ts_images, ts_labels = self.combine_tiles(
+ ts_images_dict, ts_labels_dict, no_vertical_tiles
)
# launch napari
+ self.launch_napari(ts_images, ts_labels, channels)
+
+ def launch_napari(self, ts_images, ts_labels, channels):
+ """Use Napari to see the images and outlines."""
viewer = napari.Viewer()
viewer.add_image(
ts_images[:, channels.index("Brightfield"), ...],
@@ -222,57 +305,7 @@ class ImageViewer:
)
-# class LocalImageViewer(BaseImageViewer):
-# """
-# View images from local files.
-
-# Files are either zarr or organised in directories.
-# """
-
-# def __init__(self, h5file: str, image_file: str):
-# """Initialise using a h5file and a zarr file of images."""
-# h5file_path = Path(h5file)
-# image_file_path = Path(image_file)
-# if h5file_path.exists() and image_file_path.exists():
-# super().__init__(h5file_path)
-# with dispatch_image(image_file_path)(image_file_path) as image:
-# self.tiler = Tiler.from_h5(image, h5file_path)
-# self.cells = Cells.from_source(h5file_path)
-# else:
-# if not h5file_path.exists():
-# print(f" Trouble loading {h5file}.")
-# if not image_file_path.exists():
-# print(f" Trouble loading {image_file}.")
-
-
-# class RemoteImageViewer(BaseImageViewer):
-# """View images from OMERO."""
-
-# def __init__(
-# self, h5file: str, server_info: t.Dict[str, str], omero_id: int
-# ):
-# """Initialise using a h5file and importing aliby.io.omero."""
-# h5file_path = Path(h5file)
-# super().__init__(h5file_path)
-# with h5py.File(h5file_path, "r") as f:
-# # get image_id from the h5 file
-# image_id = f.attrs.get("image_id")
-# if image_id is None:
-# # get image_id from OMERO
-# with Dataset(omero_id, **server_info) as dataset_om:
-# positions = dataset_om.get_position_ids()
-# image_id = positions.get(h5file_path.name.split(".")[0])
-# if image_id is None:
-# print("Can't find an image.")
-# else:
-# print(f"Using image ID {image_id}.")
-# self.image_id = image_id
-# image = OImage(image_id, **server_info)
-# print("Connected to OMERO.")
-# self.tiler = Tiler.from_h5(image, h5file_path)
-# self.cells = Cells.from_source(h5file_path)
-
-
+####
def colormap(channel):
"""Find default colormap."""
if "GFP" in channel: