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TypeError: alpha must be a float or None
Hi Michalk8, I am very excited to use Squidpy/Tangram to deconvolute public Visium 10X datasets. I tried to run the tutorial that is explained in the vignette (https://squidpy.readthedocs.io/en/stable/external_tutorials/tutorial_tangram.html).
When I run:
sq.pl.spatial_scatter( adata_st, color="cluster", alpha=0.7, frameon=False, ax=axs[0] )
I get the following error:
TypeError Traceback (most recent call last)
Cell In[3], line 2
1 fig, axs = plt.subplots(1, 2, figsize=(20, 5))
----> 2 sq.pl.spatial_scatter(
3 adata_st, color="cluster", alpha=0.7, frameon=False, ax=axs[0]
4 )
5 sc.pl.umap(
6 adata_sc, color="cell_subclass", size=10, frameon=False, show=False, ax=axs[1]
7 )
8 plt.tight_layout()
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial.py:418, in spatial_scatter(adata, shape, **kwargs)
377 @d.dedent
378 @_wrap_signature
379 def spatial_scatter(
(...)
382 **kwargs: Any,
383 ) -> Optional[Union[Axes, Sequence[Axes]]]:
384 """
385 Plot spatial omics data with data overlayed on top.
386
(...)
416 %(spatial_plot.returns)s
417 """
--> 418 return _spatial_plot(adata, shape=shape, seg=None, seg_key=None, **kwargs)
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial.py:282, in _spatial_plot(adata, shape, color, groups, library_id, library_key, spatial_key, img, img_res_key, img_alpha, img_cmap, img_channel, seg, seg_key, seg_cell_id, seg_contourpx, seg_outline, use_raw, layer, alt_var, size, size_key, scale_factor, crop_coord, cmap, palette, alpha, norm, na_color, connectivity_key, edges_width, edges_color, library_first, frameon, wspace, hspace, ncols, outline, outline_color, outline_width, legend_loc, legend_fontsize, legend_fontweight, legend_fontoutline, legend_na, colorbar, scalebar_dx, scalebar_units, title, axis_label, fig, ax, return_ax, figsize, dpi, save, scalebar_kwargs, edges_kwargs, **kwargs)
277 if _seg is None and _cell_id is None:
278 outline_params, kwargs = _set_outline(
279 size=_size, outline=outline, outline_width=outline_width, outline_color=outline_color, **kwargs
280 )
--> 282 ax, cax = _plot_scatter(
283 coords=coords_sub,
284 ax=ax,
285 outline_params=outline_params,
286 cmap_params=cmap_params,
287 color_params=color_params,
288 size=_size,
289 color_vector=color_vector,
290 na_color=na_color,
291 **kwargs,
292 )
293 elif _seg is not None and _cell_id is not None:
294 ax, cax = _plot_segment(
295 seg=_seg,
296 cell_id=_cell_id,
(...)
306 **kwargs,
307 )
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial_utils.py:955, in _plot_scatter(coords, ax, outline_params, cmap_params, color_params, size, color_vector, na_color, **kwargs)
944 _cax = scatter(
945 coords[:, 0],
946 coords[:, 1],
(...)
952 **kwargs,
953 )
954 ax.add_collection(_cax)
--> 955 _cax = scatter(
956 coords[:, 0],
957 coords[:, 1],
958 c=color_vector,
959 s=size,
960 rasterized=sc_settings._vector_friendly,
961 cmap=cmap_params.cmap,
962 norm=norm,
963 **kwargs,
964 )
965 cax = ax.add_collection(_cax)
967 return ax, cax
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial_utils.py:531, in _shaped_scatter(x, y, s, c, shape, norm, **kwargs)
529 alpha = ColorConverter().to_rgba_array(c)[..., -1]
530 collection.set_facecolor(c)
--> 531 collection.set_alpha(alpha)
533 return collection
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/matplotlib/collections.py:834, in Collection.set_alpha(self, alpha)
832 def set_alpha(self, alpha):
833 # docstring inherited
--> 834 super().set_alpha(alpha)
835 self._update_dict['array'] = True
836 self._set_facecolor(self._original_facecolor)
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/matplotlib/artist.py:930, in Artist.set_alpha(self, alpha)
922 """
923 Set the alpha value used for blending - not supported on all backends.
924
(...)
927 alpha : float or None
928 """
929 if alpha is not None and not isinstance(alpha, Number):
--> 930 raise TypeError('alpha must be a float or None')
931 self._alpha = alpha
932 self.pchanged()
TypeError: alpha must be a float or None
Looking at your code, I think the TypeError is caused by the lines below. Where, besides the alpha that is given as a keyword argument in the _sq.pl.spatial.scatter function, an additional alpha is written if isinstance(c, np.ndarray) and np.issubdtype(c.dtype, np.number) != True. I think this causes the TypeError because the additional alpha is not a float or None? This also seems to be the case because the code runs without errors if I internally manually set the newly written alpha to 0.7.
if isinstance(c, np.ndarray) and np.issubdtype(c.dtype, np.number):
collection.set_array(np.ma.masked_invalid(c))
collection.set_norm(norm)
else:
alpha = ColorConverter().to_rgba_array(c)[..., -1]
collection.set_facecolor(c)
collection.set_alpha(alpha)
As I am just learning to read and write python code, I was wondering if you could help me figure out what goes wrong. Thanks in advance!
Package versions that I used:
scanpy==1.8.2 anndata==0.8.0 umap==0.5.3 numpy==1.23.5 scipy==1.5.2 pandas==1.5.2 scikit-learn==1.2.0 statsmodels==0.13.5 python-igraph==0.10.2 pynndescent==0.5.8
squidpy==1.2.2
tangram==1.0.3
...
Hi @giovp,
Thanks for your response. I am using 'matplotlib 3.3.1' and 'matplotlib_scalebar 0.8.1'.
hi @FvdBre sorry I can't reproduce, can you maybe post a reproducible example using some squidpy datasets in this issue?
Hi @giovp,
I got this error when I used a public 10X Visium dataset. But after running all the exact lines and data from the vignette listed above (https://squidpy.readthedocs.io/en/stable/external_tutorials/tutorial_tangram.html), I get the same error.
import scanpy as sc
import squidpy as sq
import numpy as np
import pandas as pd
from anndata import AnnData
import pathlib
import matplotlib.pyplot as plt
import matplotlib as mpl
import skimage
# import tangram for spatial deconvolution
import tangram as tg
sc.logging.print_header()
print(f"squidpy=={sq.__version__}")
print(f"tangram=={tg.__version__}")
Returns:
/opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
from .autonotebook import tqdm as notebook_tqdm
scanpy==1.8.2 anndata==0.8.0 umap==0.5.3 numpy==1.23.5 scipy==1.5.2 pandas==1.5.2 scikit-learn==1.2.0 statsmodels==0.13.5 python-igraph==0.10.2 pynndescent==0.5.8
squidpy==1.2.2
tangram==1.0.3
New line:
adata_st = sq.datasets.visium_fluo_adata_crop()
adata_st = adata_st[
adata_st.obs.cluster.isin([f"Cortex_{i}" for i in np.arange(1, 5)])
].copy()
img = sq.datasets.visium_fluo_image_crop()
adata_sc = sq.datasets.sc_mouse_cortex()
New line:
sq.im.process(img=img, layer="image", method="smooth")
sq.im.segment(
img=img,
layer="image_smooth",
method="watershed",
channel=0,
)
New line:
inset_y = 1500
inset_x = 1700
inset_sy = 400
inset_sx = 500
fig, axs = plt.subplots(1, 3, figsize=(30, 10))
sq.pl.spatial_scatter(
adata_st, color="cluster", alpha=0.7, frameon=False, ax=axs[0], title=""
)
axs[0].set_title("Clusters", fontdict={"fontsize": 20})
sf = adata_st.uns["spatial"]["V1_Adult_Mouse_Brain_Coronal_Section_2"]["scalefactors"][
"tissue_hires_scalef"
]
rect = mpl.patches.Rectangle(
(inset_y * sf, inset_x * sf),
width=inset_sx * sf,
height=inset_sy * sf,
ec="yellow",
lw=4,
fill=False,
)
axs[0].add_patch(rect)
axs[0].axes.xaxis.label.set_visible(False)
axs[0].axes.yaxis.label.set_visible(False)
axs[1].imshow(
img["image"][inset_y : inset_y + inset_sy, inset_x : inset_x + inset_sx, 0, 0]
/ 65536,
interpolation="none",
)
axs[1].grid(False)
axs[1].set_xticks([])
axs[1].set_yticks([])
axs[1].set_title("DAPI", fontdict={"fontsize": 20})
crop = img["segmented_watershed"][
inset_y : inset_y + inset_sy, inset_x : inset_x + inset_sx
].values.squeeze(-1)
crop = skimage.segmentation.relabel_sequential(crop)[0]
cmap = plt.cm.plasma
cmap.set_under(color="black")
axs[2].imshow(crop, interpolation="none", cmap=cmap, vmin=0.001)
axs[2].grid(False)
axs[2].set_xticks([])
axs[2].set_yticks([])
axs[2].set_title("Nucleous segmentation", fontdict={"fontsize": 20})
Returns:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[4], line 7
4 inset_sx = 500
6 fig, axs = plt.subplots(1, 3, figsize=(30, 10))
----> 7 sq.pl.spatial_scatter(
8 adata_st, color="cluster", alpha=0.7, frameon=False, ax=axs[0], title=""
9 )
10 axs[0].set_title("Clusters", fontdict={"fontsize": 20})
11 sf = adata_st.uns["spatial"]["V1_Adult_Mouse_Brain_Coronal_Section_2"]["scalefactors"][
12 "tissue_hires_scalef"
13 ]
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial.py:418, in spatial_scatter(adata, shape, **kwargs)
377 @d.dedent
378 @_wrap_signature
379 def spatial_scatter(
(...)
382 **kwargs: Any,
383 ) -> Optional[Union[Axes, Sequence[Axes]]]:
384 """
385 Plot spatial omics data with data overlayed on top.
386
(...)
416 %(spatial_plot.returns)s
417 """
--> 418 return _spatial_plot(adata, shape=shape, seg=None, seg_key=None, **kwargs)
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial.py:282, in _spatial_plot(adata, shape, color, groups, library_id, library_key, spatial_key, img, img_res_key, img_alpha, img_cmap, img_channel, seg, seg_key, seg_cell_id, seg_contourpx, seg_outline, use_raw, layer, alt_var, size, size_key, scale_factor, crop_coord, cmap, palette, alpha, norm, na_color, connectivity_key, edges_width, edges_color, library_first, frameon, wspace, hspace, ncols, outline, outline_color, outline_width, legend_loc, legend_fontsize, legend_fontweight, legend_fontoutline, legend_na, colorbar, scalebar_dx, scalebar_units, title, axis_label, fig, ax, return_ax, figsize, dpi, save, scalebar_kwargs, edges_kwargs, **kwargs)
277 if _seg is None and _cell_id is None:
278 outline_params, kwargs = _set_outline(
279 size=_size, outline=outline, outline_width=outline_width, outline_color=outline_color, **kwargs
280 )
--> 282 ax, cax = _plot_scatter(
283 coords=coords_sub,
284 ax=ax,
285 outline_params=outline_params,
286 cmap_params=cmap_params,
287 color_params=color_params,
288 size=_size,
289 color_vector=color_vector,
290 na_color=na_color,
291 **kwargs,
292 )
293 elif _seg is not None and _cell_id is not None:
294 ax, cax = _plot_segment(
295 seg=_seg,
296 cell_id=_cell_id,
(...)
306 **kwargs,
307 )
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial_utils.py:955, in _plot_scatter(coords, ax, outline_params, cmap_params, color_params, size, color_vector, na_color, **kwargs)
944 _cax = scatter(
945 coords[:, 0],
946 coords[:, 1],
(...)
952 **kwargs,
953 )
954 ax.add_collection(_cax)
--> 955 _cax = scatter(
956 coords[:, 0],
957 coords[:, 1],
958 c=color_vector,
959 s=size,
960 rasterized=sc_settings._vector_friendly,
961 cmap=cmap_params.cmap,
962 norm=norm,
963 **kwargs,
964 )
965 cax = ax.add_collection(_cax)
967 return ax, cax
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/squidpy/pl/_spatial_utils.py:531, in _shaped_scatter(x, y, s, c, shape, norm, **kwargs)
529 alpha = ColorConverter().to_rgba_array(c)[..., -1]
530 collection.set_facecolor(c)
--> 531 collection.set_alpha(alpha)
533 return collection
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/matplotlib/collections.py:834, in Collection.set_alpha(self, alpha)
832 def set_alpha(self, alpha):
833 # docstring inherited
--> 834 super().set_alpha(alpha)
835 self._update_dict['array'] = True
836 self._set_facecolor(self._original_facecolor)
File /opt/miniconda3/envs/tangram-env/lib/python3.8/site-packages/matplotlib/artist.py:930, in Artist.set_alpha(self, alpha)
922 """
923 Set the alpha value used for blending - not supported on all backends.
924
(...)
927 alpha : float or None
928 """
929 if alpha is not None and not isinstance(alpha, Number):
--> 930 raise TypeError('alpha must be a float or None')
931 self._alpha = alpha
932 self.pchanged()
TypeError: alpha must be a float or None
Hey there! Could you also provide your plotting backend? Your code also works for me.
print(matplotlib.get_backend()) #-> module://matplotlib_inline.backend_inline for jupyter
print(mpl.get_backend()) #-> module://matplotlib_inline.backend_inline for jupyter
Returns:
module://matplotlib_inline.backend_inline
Is this what you are looking for?
@FvdBre I also tried to reproduce and didn't manage. Can you try with a standard dataset from squidpy and see if it works>?
I ran the script as described in the vignette using the squidpy dataset:
adata_st = sq.datasets.visium_fluo_adata_crop()
adata_st
AnnData object with n_obs × n_vars = 324 × 16562
obs: 'in_tissue', 'array_row', 'array_col', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_MT', 'log1p_total_counts_MT', 'pct_counts_MT', 'n_counts', 'leiden', 'cluster'
var: 'gene_ids', 'feature_types', 'genome', 'MT', 'n_cells_by_counts', 'mean_counts', 'log1p_mean_counts', 'pct_dropout_by_counts', 'total_counts', 'log1p_total_counts', 'n_cells', 'highly_variable', 'highly_variable_rank', 'means', 'variances', 'variances_norm'
uns: 'cluster_colors', 'hvg', 'leiden', 'leiden_colors', 'neighbors', 'pca', 'spatial', 'umap'
obsm: 'X_pca', 'X_umap', 'spatial'
varm: 'PCs'
obsp: 'connectivities', 'distances'
My tangram environment seems fine, but when I run it on google colab I don't get the error. I guess this means I have a conflicting package installed on my base (all base packages listed below).
# packages in environment at /opt/miniconda3:
#
# Name Version Build Channel
brotlipy 0.7.0 py39h9ed2024_1003
ca-certificates 2021.10.26 hecd8cb5_2
certifi 2021.10.8 py39hecd8cb5_2
cffi 1.14.6 py39h2125817_0
charset-normalizer 2.0.4 pyhd3eb1b0_0
conda 4.11.0 py39hecd8cb5_0
conda-package-handling 1.7.3 py39h9ed2024_1
cryptography 36.0.0 py39hf6deb26_0
idna 3.3 pyhd3eb1b0_0
libcxx 12.0.0 h2f01273_0
libffi 3.3 hb1e8313_2
ncurses 6.3 hca72f7f_2
openssl 1.1.1m hca72f7f_0
pycosat 0.6.3 py39h9ed2024_0
pycparser 2.21 pyhd3eb1b0_0
pyopenssl 21.0.0 pyhd3eb1b0_1
pysocks 1.7.1 py39hecd8cb5_0
python 3.9.5 h88f2d9e_3
python.app 3 py39h9ed2024_0
readline 8.1.2 hca72f7f_1
requests 2.27.1 pyhd3eb1b0_0
ruamel_yaml 0.15.100 py39h9ed2024_0
setuptools 58.0.4 py39hecd8cb5_0
six 1.16.0 pyhd3eb1b0_0
sqlite 3.37.0 h707629a_0
tk 8.6.11 h7bc2e8c_0
tqdm 4.62.3 pyhd3eb1b0_1
tzdata 2021e hda174b7_0
urllib3 1.26.7 pyhd3eb1b0_0
xz 5.2.5 h1de35cc_0
yaml 0.2.5 haf1e3a3_0
zlib 1.2.11 h4dc903c_4
Therefore I will reinstall miniconda.
UPDATE:
After reinstalling miniconda and comparing the packages in the base there is one package that is not there by default:
yaml 0.2.5 haf1e3a3_0
If in a fresh conda env this problem doesn't persist then it must be some type of conflicts which is difficult to find