I am getting an error when i include a segmentation mask file:
# Pre- subset the anndata to prevent indexing error. Also, don't use `imageid` and `subset` args to image_viewer().
#selected = adata[adata.obs['Unique_ID'].isin(['PT7.ROI_1']), :] # This doesn't work
selected = adata[adata.obs['Unique_ID'].isin(['PT7.ROI_1']), :].copy() # Making a copy makes it work
sm.pl.image_viewer(image_path=img_path,
seg_mask=seg_mask, # seg_mask=None,
#adata=adata, imageid='Unique_ID', subset = 'PT7.ROI_1', # Don't do this, Use pre-subsetted data instead
adata=selected,
overlay='spatial_kmeans',
channel_names=layers_order,
x_coordinate='X', y_coordinate='Y', flip_y=False, point_size=4)
The segmentation mask file is readable, as in, I am able to display it in napari by running this chunk of code from sm.pl.image_viewer (minus the last two lines that I commented out—those break):
# Load the segmentation mask
if seg_mask is not None:
seg_m = tiff.imread(seg_mask)
# if seg_m.shape[0] > 1:
# seg_m = seg_m[0]
followed by:
napari.view_image(seg_m)
However, I get the error below when trying to open it with image_viewer().
Click to expand error
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Input In [198], in <cell line: 5>()
1 # Pre- subset the anndata to prevent indexing error. Also, don't use imageid and subset args to image_viewer().
2 #selected = adata[adata.obs['Unique_ID'].isin(['PT7.ROI_1'])] # This doesn't work
3 selected = adata[adata.obs['Unique_ID'].isin(['PT7.ROI_1']), :].copy() # Making a copy makes it work
----> 5 viewer=sm.pl.image_viewer(image_path=img_path,
6 seg_mask=seg_path,
7 #adata=adata, imageid='Unique_ID', subset = 'PT7.ROI_1', # Don't do this, Use pre-subsetted data instead
8 adata=selected,
9 overlay='cellsimple2', # 'spatial_kmeans', #
10 channel_names=layers_order,
11 x_coordinate='X', y_coordinate='Y', flip_y=False, point_size=4)
File ~/anaconda3/envs/napari-imc/lib/python3.9/site-packages/scimap/plotting/_image_viewer.py:184, in image_viewer(image_path, adata, overlay, flip_y, overlay_category, markers, channel_names, x_coordinate, y_coordinate, point_size, point_color, subset, imageid, seg_mask, **kwargs)
182 # Add the seg mask
183 if seg_mask is not None:
--> 184 viewer.add_labels(seg_m, name='segmentation mask', visible=False)
186 # Add phenotype layer function
187 def add_phenotype_layer (adata, overlay, phenotype_layer,x,y,viewer,point_size,point_color):
File ~/anaconda3/envs/napari-imc/lib/python3.9/site-packages/napari/components/viewer_model.py:4, in add_labels(self, data, num_colors, features, properties, color, seed, name, metadata, scale, translate, rotate, shear, affine, opacity, blending, rendering, depiction, visible, multiscale, cache, plane, experimental_clipping_planes)
1 from __future__ import annotations
3 import inspect
----> 4 import itertools
5 import os
6 import warnings
File ~/anaconda3/envs/napari-imc/lib/python3.9/site-packages/napari/layers/labels/labels.py:259, in Labels.__init__(self, data, num_colors, features, properties, color, seed, name, metadata, scale, translate, rotate, shear, affine, opacity, blending, rendering, depiction, visible, multiscale, cache, plane, experimental_clipping_planes)
256 self._show_selected_label = False
257 self._contour = 0
--> 259 data = self._ensure_int_labels(data)
260 self._color_lookup_func = None
262 super().__init__(
263 data,
264 rgb=False,
(...)
284 experimental_clipping_planes=experimental_clipping_planes,
285 )
File ~/anaconda3/envs/napari-imc/lib/python3.9/site-packages/napari/layers/labels/labels.py:554, in Labels._ensure_int_labels(self, data)
552 def _ensure_int_labels(self, data):
553 """Ensure data is integer by converting from bool if required, raising an error otherwise."""
--> 554 looks_multiscale, data = guess_multiscale(data)
555 if not looks_multiscale:
556 data = [data]
File ~/anaconda3/envs/napari-imc/lib/python3.9/site-packages/napari/layers/image/_image_utils.py:76, in guess_multiscale(data)
72 consistent = bool(np.all(sizes[:-1] > sizes[1:]))
73 if np.all(sizes == sizes[0]):
74 # note: the individual array case should be caught by the first
75 # code line in this function, hasattr(ndim) and ndim > 1.
---> 76 raise ValueError(
77 trans._(
78 'Input data should be an array-like object, or a sequence of arrays of decreasing size. Got arrays of single shape: {shape}',
79 deferred=True,
80 shape=shapes[0],
81 )
82 )
83 if not consistent:
84 raise ValueError(
85 trans._(
86 'Input data should be an array-like object, or a sequence of arrays of decreasing size. Got arrays in incorrect order, shapes: {shapes}',
(...)
89 )
90 )
ValueError: Input data should be an array-like object, or a sequence of arrays of decreasing size. Got arrays of single shape: ()
Thank you!
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