执行代码
from stereo import image as im
im.cell_seg(model_path, img_path, out_path)

1、原始数据内有6个tissue，只cut出5个tissue

2、分割的结果中出现了原始tif上并没有的信号（红框圈出来的）

I have extended a couple of functions for saving and reading results and key records from the pipeline as well as the raw expression matrix (https://github.com/nilsmechtel/stereopy). If you are interested in them, feel free to add them to the main branch.

After creating conda environment I'm getting an error when I run setup:

Processing dependencies for stereopy==0.7.0
Searching for gefpy>=0.6.7
Reading https://pypi.org/simple/gefpy/
No local packages or working download links found for gefpy>=0.6.7
error: Could not find suitable distribution for Requirement.parse('gefpy>=0.6.7')

I suppose it could be solved by providing a specific Conda repository where all specified package versions are available.

Hi,

I'm exploring Stereopy with the .h5ad files you have provided in the link here. However, on my Jupyter notebook I get the following error when trying to load stereopy

Below is what I am loading

import os
from os.path import join as jn
import warnings
warnings.filterwarnings('ignore')
import stereo as st

Here is the error

---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
Cell In [7], line 5
      2 from os.path import join as jn
      3 #import warnings
      4 #warnings.filterwarnings('ignore')
----> 5 import stereo as st

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/stereo/__init__.py:10
      8 from . import tools
      9 from . import utils
---> 10 from . import plots as plt
     11 from . import image

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/stereo/plots/__init__.py:13
     11 from .marker_genes import marker_genes_text, marker_genes_heatmap
     12 from .plot_collection import PlotCollection
---> 13 from .interact_plot.spatial_cluster import interact_spatial_cluster
     14 from .interact_plot.interactive_scatter import InteractiveScatter
     15 from .interact_plot.poly_selection import PolySelection

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/stereo/plots/interact_plot/spatial_cluster.py:8
      1 #!/usr/bin/env python3
      2 # coding: utf-8
      3 """
      4 @author: [email protected]
      5 @time:2021/09/06
      6 """
----> 8 import holoviews as hv
      9 import hvplot.pandas
     10 import panel as pn

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/holoviews/__init__.py:12
      8 __version__ = str(param.version.Version(fpath=__file__, archive_commit="$Format:%h$",
      9                                         reponame="holoviews"))
     11 from . import util                                       # noqa (API import)
---> 12 from .annotators import annotate                         # noqa (API import)
     13 from .core import archive, config                        # noqa (API import)
     14 from .core.boundingregion import BoundingBox             # noqa (API import)

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/holoviews/annotators.py:10
      6 from inspect import getmro
      8 import param
---> 10 from panel.pane import PaneBase
     11 from panel.layout import Row, Tabs
     12 from panel.util import param_name

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/__init__.py:1
----> 1 from . import layout # noqa
      2 from . import links # noqa
      3 from . import pane # noqa

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/layout/__init__.py:1
----> 1 from .accordion import Accordion # noqa
      2 from .base import Column, ListLike, ListPanel, Panel, Row, WidgetBox # noqa
      3 from .card import Card # noqa

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/layout/accordion.py:5
      1 import param
      3 from bokeh.models import Column as BkColumn, CustomJS
----> 5 from .base import NamedListPanel
      6 from .card import Card
      9 class Accordion(NamedListPanel):

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/layout/base.py:13
     11 from ..io.model import hold
     12 from ..io.state import state
---> 13 from ..reactive import Reactive
     14 from ..util import param_name, param_reprs
     16 _row = namedtuple("row", ["children"])

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/reactive.py:25
     22 from param.parameterized import ParameterizedMetaclass
     23 from tornado import gen
---> 25 from .config import config
     26 from .io.model import hold
     27 from .io.notebook import push

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/config.py:20
     14 import param
     16 from pyviz_comms import (
     17     JupyterCommManager as _JupyterCommManager, extension as _pyviz_extension
     18 )
---> 20 from .io.notebook import load_notebook
     21 from .io.state import state
     23 __version__ = str(param.version.Version(
     24     fpath=__file__, archive_commit="$Format:%h$", reponame="panel"))

File ~/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/io/__init__.py:9
      6 import logging
      7 import sys
----> 9 from ..config import config
     11 from .callbacks import PeriodicCallback # noqa
     12 from .embed import embed_state # noqa

ImportError: cannot import name 'config' from partially initialized module 'panel.config' (most likely due to a circular import) (/home/sama0023/miniconda3/envs/stereopy/lib/python3.8/site-packages/panel/config.py)

Is it because the name config is being used somewhere else? (ref here: https://stackoverflow.com/questions/64807163/importerror-cannot-import-name-from-partially-initialized-module-m)

Many thanks for your reply - looking forward to hearing from you soon.
Shani.

• write h5ad
• write txt

Hi,

I got another error when I tried to run the data.plt.interact_cluster(res_key='leiden') from the quick_start jupyter notebook:

It seems that package names conflict with each other. I would appreciate it if you would like to take a look at it.

Thanks,
Jianning

Hi stereopy teams!
I have generated cellbin.cgef and i want to convert to h5ad format, yet i got the error: [reader][429][ERROR]: convert to AnnData should have raw data. the code was:
path_high_res = "./data/nom_1d_highres_cellbin.gef"
data_high_res = st.io.read_gef(path_high_res, bin_type='cell_bins')
data_high_res.tl.cal_qc()
ins_high_res = data_high_res.plt.interact_spatial_scatter(width=500, height=500, poly_select=True)
ins_high_res.show()
adata = st.io.stereo_to_anndata(data_high_res,flavor='scanpy',output='nom_1d_highres_cellbin.h5ad')

TRACEBACK:
[2023-03-01 16:32:21][Stereo][14329][140019443029824][reader][429][ERROR]: convert to AnnData should have raw data

Exception Traceback (most recent call last)
Cell In[12], line 1
----> 1 adata = st.io.stereo_to_anndata(data_high_res,flavor='scanpy',output='nom_1d_highres_cellbin.h5ad')

File ~/miniconda3/envs/st/lib/python3.8/site-packages/stereo/io/reader.py:430, in stereo_to_anndata(data, flavor, sample_id, reindex, output, split_batches)
428 if data.tl.raw is None:
429 logger.error('convert to AnnData should have raw data')
--> 430 raise Exception
432 exp = data.tl.raw.exp_matrix if issparse(data.tl.raw.exp_matrix) else csr_matrix(data.tl.raw.exp_matrix)
433 cells = data.tl.raw.cells.to_df()

Exception:

Can you check this error, many thanks!

Dear Sir/Madam,

I cloned Stereopy form https://github.com/BGIResearch/stereopy, then installed the required packed locally (pycharm). Default installation was gefpy 0.1.0, how system warned requirement for gefpy>=0.1.1. Failure is always reminded, no matter installed from pycharm or pin from the terminal.
Thus, may I ask do you have any suggestions for this issue?

Thanks so much!

You have told how to draw the ssDNA image in the tutorial as indicated below.

However, we could not realize it as indicated below. So why?

And we do not know where to download the tutorial data.

Could you help us? Thank you.

Hello
Thanks for developing the package. I used read_gef in the io module of stereopy to parse the gef file, then a StereoExpData object was returned, which contains much information. But I don't understand the cell_names of the object. Because the gef file didn't contain the related information. They look like the id of the mask file. Please advise.

The cell_names of StereoExpData

>>> import stereo as st
>>> dat = st.io.read_gef('./FP200003336_L01_72.raw.gef', bin_size = 1, is_sparse=True)
>>> dat.cell_names
array([ 3590592669555, 37293201051182, 25997437066045, ...,
         794568965723, 19477676698069,  9083855849722])

The position id of the mask file.

HDF5 "/share/ShareData/Stereo-seq/Mask_file/E11.5_E1S3.barcodeToPos.h5" {
DATASET "/bpMatrix_1" {
   DATATYPE  H5T_STD_U64LE
   DATASPACE  SIMPLE { ( 26462, 26462, 1 ) / ( 26462, 26462, 1 ) }
   DATA {
   (0,0,0): 90894471210542,
   (0,1,0): 152917129528969,
   (0,2,0): 245238102184754,
   (0,3,0): 183680511537661,
   (0,4,0): 204000043738565,
   (0,5,0): 21505938126074,
   (0,6,0): 822201656293554,
   (0,7,0): 902627202106568,
   (0,8,0): 982822939930488,
   (0,9,0): 259155236519271,
   (0,10,0): 241356892181875,
   (0,11,0): 697765384657892,
   (0,12,0): 301210434339907,
   (0,13,0): 56003391889515,
   (0,14,0): 676778668696025,
   (0,15,0): 464497669882956,
   (0,16,0): 1099133513140956,
   (0,17,0): 1118933043153630,
   (0,18,0): 838006647635862,
   (0,19,0): 817678488407851,
   (0,20,0): 1081564470506869,
   (0,21,0): 795831308672738,
   (0,22,0): 340919166457846,
   (0,23,0): 570096918465330,
   (0,24,0): 576679295911424,
   (0,25,0): 76328420739723,
   (0,26,0): 728368681319792,
   (0,27,0): 523708119536022,
   (0,28,0): 219845555935278,
   (0,29,0): 21202826412319,
   (0,30,0): 652047660144813,
   (0,31,0): 770467494289177,
   (0,32,0): 799251329080094,
   (0,33,0): 1107366538726038,
   (0,34,0): 1072110141530501,

Quick start notebook is requesting data:

# read the GEF file
mouse_data_path = './stereomics.h5'

But, on the provided link in the notebook, this file is not present. Also, the page is in Chinese, and it is impossible without a translation tool to guess which button is for download.

I want to change the bin size when I read the .gem file. However, changing the 'bin' parameter of read_gem(v0.2.2) didn't work, and read_stereo_data(v0.1) worked. Is it a bug?

When I run the "dyn.tl.leiden(adata, result_key='spatial_leiden_res')", an error is reported:
“Fatal error at src/core/vector.c:483 : Assertion failed: v->stor_begin != NULL ”
and the Jupyter will appears to have died.
Is there any methods to solve it ? thx.

Hi there,

I just got an error when installing stereopy (version 0.2.4), it seems there is something wrong with the gefpy package, could you please help me out of this?

ERROR: Could not find a version that satisfies the requirement gefpy>=0.1.1 (from stereopy) (from versions: none)
ERROR: No matching distribution found for gefpy>=0.1.1

Hello, I used your model about cell segmentation.Can i use my dataset to get a new model?

• Cell division
• Image registration

I have followed instructions from stereopy instructions page through the following link (https://stereopy.readthedocs.io/en/latest/General/Installation.html) by typing the following commands
conda create --name st python=3.8
conda activate st
pip install stereopy

After installation, when I was trying to use stereopy by typing the following commands ( shown below) it's giving an error.
import warnings
warnings.filterwarnings('ignore')
import stereo as st

It would be really helpful, if you help on this.

I've been trying to follow the cell_segmentation tutorial v0.10.0 using data from MOSTA; however, when I try to run the cell_cut function, I run into the following error:

python3: /workitems/geftools/cgefCellgem.cpp:897: void cgefCellgem::readmask_new(const string&): Assertion `m_rows == cgefParam::GetInstance()->m_max_y - cgefParam::GetInstance()->m_min_y+1' failed.

This is the code I run on a linux computing cluster:

from stereo.tools.cell_cut import CellCut

cgef_out_dir = "./cgef"
bgef_path = "../E12.5_E1S3.bgef"
gem_path = "../E12.5_E1S3_bin1.gem"

mask_path = "./cgef/deep-learning/E12.5_E1S3_mask.tif"

image_path = "../image_spat/E12.5_E1S3.tif"
model_path = "./models/seg_model_20211210.pth"

cc = CellCut(cgef_out_dir=cgef_out_dir)

out_path = cc.cell_cut(gem_path=gem_path, mask_path=mask_path)
# out_path = cc.cell_cut(bgef_path=bgef_path, mask_path=mask_path)
# out_path = cc.cell_cut(bgef_path=bgef_path, image_path=image_path, model_path=model_path)

GEM File Source: https://ftp.cngb.org/pub/SciRAID/stomics/STDS0000058/Bin1_matrix/E12.5_E1S3_GEM_bin1.tsv.gz
Image File Source: https://ftp.cngb.org/pub/SciRAID/stomics/STDS0000058/Image/E12.5_E1S3.tif

I have also tried running the commented out versions as well. The mask generation and conversion from gem to bgef are successful, but get the same error for the cell binning.

Please check for the renewal of Jinja2 package.
It's no longer able to import Markup from jinja2 since version 3.1.0. You can either renew the script or restrict the Jinja2 version in requirement.txt. Otherwise, importing stereo would fail.

Another suggestion, hope developers can create a conda environment.yaml for the ease of installation. If installing through pip, it would be a mess to install the large amount of dependent libraries.

Sincerely,
magcurly

Hi authors:
when i read informations of tissue.gef, i got that error.

data_path = './SS200000385BR_E3.tissue.gef'
st.io.read_gef_info(data_path)

2022-07-04 11:11:09 Stereo 1068023 139744111322944 reader 576 INFO: This is BGEF file which contains traditional bin infomation.
2022-07-04 11:11:09 Stereo 1068023 139744111322944 reader 577 INFO: bin_type: bins
2022-07-04 11:11:09 Stereo 1068023 139744111322944 reader 580 INFO: Bin size list: ['bin1']

IndexError Traceback (most recent call last)
in
----> 1 st.io.read_gef_info(data_path)

/home/program/conda/anaconda3/envs/stereopy/lib/python3.8/site-packages/stereo/io/reader.py in read_gef_info(file_path)
580 logger.info('Bin size list: {0}'.format(info_dict['bin_list']))
581
--> 582 info_dict['resolution'] = h5_file['geneExp']['bin1']['expression'].attrs['resolution'][0]
583 logger.info('Resolution: {0}'.format(info_dict['resolution']))
584

IndexError: invalid index to scalar variable.

Hi to the developers,

Thank you very much for the thoughtful .h5ad to Seurat conversion R script.I tried using that on the data I downloaded form the STOMICS database, however I ran into a problem.

Here is the code I ran and the error ( I ran this with R/4.2)

sama0023@arxcss:~/STOMICS$ Rscript annh5ad2rds.R --infile ./Stomics_data/E16.5_E2S3.MOSTA.h5ad --outfile ./Stomics_data/E16.5_E2S3.MOSTA.RDS
Registered S3 method overwritten by 'SeuratDisk':
  method            from  
  as.sparse.H5Group Seurat
Attaching SeuratObject

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

[1] "Converting h5ad to h5seurat file."
Warning: Unknown file type: h5ad
Creating h5Seurat file for version 3.1.5.9900
Adding X as data
Adding X as counts
Adding meta.features from var
Adding spatial as cell embeddings for spatial
Warning: Cannot find a reduction named pca (PCs in varm)
Adding annotation_colors to miscellaneous data
Adding layer count as data in assay count
Adding layer count as counts in assay count
[1] "Loading h5seurat file."
Validating h5Seurat file
Initializing Spatial with data
Adding counts for Spatial
Adding feature-level metadata for Spatial
Initializing count with data
Adding counts for count
Adding reduction spatial
Adding cell embeddings for spatial
Adding miscellaneous information for spatial
Adding command information
Adding cell-level metadata
Warning: Invalid name supplied, making object name syntactically valid. New object name is n_genes_by_countslog1p_n_genes_by_countstotal_countslog1p_total_countsannotationRegulon...Acaa1aRegulon...AhrRegulon...Alx1Regulon...Alx4Regulon...Arid3aRegulon...ArntRegulon...Arnt2Regulon...ArxRegulon...Atf2Regulon...Atf3Regulon...Atf4Regulon...Atf6Regulon...Bach2Regulon...Barhl1Regulon...Barhl2Regulon...Bcl6Regulon...Bcl6bRegulon...Bclaf1Regulon...Bhlhe22Regulon...Bhlhe40Regulon...Bhlhe41Regulon...BmycRegulon...Borcs8Regulon...BptfRegulon...Brf1Regulon...CebpaRegulon...CebpbRegulon...CebpdRegulon...CebpgRegulon...CebpzRegulon...Chd1Regulon...CicRegulon...ClockRegulon...Cnot3Regulon...Creb1Regulon...Creb3Regulon...Creb3l1Regulon...Creb3l2Regulon...CrxRegulon...CtcfRegulon...Cux1Regulon...Cux2Regulon...DbpRegulon...Dbx1Regulon...Ddit3Regulon...Ddx4Regulon...Dlx1Regulon...Dlx2Regulon...Dlx3Regulon...Dlx5Regulon...Dlx6Regulon...Dmrt2Regulon...E2f1Regulon...E2f2Regulon...E2f3Regulon...E2f4Regulon...E2f5Regu [... truncated]
Adding miscellaneous information
Adding tool-specific results
Warning message:
Cannot add objects with duplicate keys (offending key: spatial_), setting key to 'spatialla_' 
Error in `[.data.frame`([email protected], , c("x", "y")) : 
  undefined columns selected
Calls: unique -> [ -> [.data.frame
Execution halted

Can you please explain how this can be corrected?

Many thanks in advance,
Shani.

Hi,
In the document, the explanation for x, and y is:

x, y are the spatial position of the gene in the tissue section.

And the explanation for .gem file looks like is:

When I load the file SS200000135TL_D1.tissue.gem, I can see the table like this:

The x values of Camk1d and Gabra1 are different(7566 / 7567), but they have the same cell id: 56203. So I got two questions here:

1. What's the exact meaning of x, and y here, do they represent the DNB barcode position? Or do they have other means?
2. I didn't find the explanation for cols CellID here, could you please tell me what it means here?

Thank you!

Hi stereopy team,
I followed the cell correct tutorial to cell correct my data, code as followed in #96
Yet i got the error:

Python 3.8.16 | packaged by conda-forge | (default, Feb 1 2023, 16:01:55)

In [1]: from stereo.tools.cell_correct import cell_correct
...: bgef_path = "./data/C01626E6F6.raw.gef"
...: mask_path = "./data/C01626E6F6_regist.tif"
...: out_dir = "./cell_correct_result"
...: only_save_result = False
...: fast = True
...: data = cell_correct(out_dir=out_dir,
...: bgef_path=bgef_path,
...: mask_path=mask_path,
...: process_count=10,
...: only_save_result=only_save_result,
...: fast=fast)
[2023-02-19 11:03:58][Stereo][328478][140382292883264][time_consume][55][INFO]: start to run cell_correct...
[2023-02-19 11:03:58][Stereo][328478][140382292883264][time_consume][55][INFO]: start to run correcting...
[2023-02-19 11:03:58][Stereo][328478][140382292883264][time_consume][55][INFO]: start to run generate_raw_data...
[2023-02-19 11:03:58][Stereo][328478][140382292883264][cell_correct][99][INFO]: start to generate raw cellbin gef (./cell_correct_result/C01626E6F6.raw.raw.cellbin.gef)
create h5 file: ./cell_correct_result/C01626E6F6.raw.raw.cellbin.gef
minx:0 miny:0 maxx:26459 maxy:44099
genecnt:28263 geneExpcnt:138988822 hashcnt:99139069
readBgef_new - elapsed time: 223833.54450 ms
img row:44100 col:26460
readmask_new - elapsed time: 3465.90027 ms
storeAttr - 0.000116 cpu sec
Segmentation fault (core dumped)

I don't know how to solve it? Thanks!

• dim reduce

• pca

• umap

• tsen

• low variance

• factor analysis

• clustering

• leiden

• louvain

• phenograph

• cell type annotation

• direct annotation using random forest

• gene pattern

• find pattern

• recode sparkx

• marker genes

• t-test

• wilcoxon-test

• spatial lag model

• enrich

• go enrich

• pathway activation

• RNA velocity

框架概述

设计思路

• IO：文件数据读写，生成数据类，目前使用AnnData

• 预处理：对数据类进行质控、过滤、标准化

• 分析：输入数据类以及相应参数设置，运行分析，将分析结果写回数据类

• 可视化：对分析结果进行可视化

  框架流程图

  

设计原则

1.模块化

考虑到框架的可拓展性，主要设计了三种基类，分别为数据类、分析类、结果类。整体实现流程是将数据类传入分析类，进行分析，
得到结果类，将结果写回数据类，或者输出文件，并可视化结果。

2.基类说明

• 数据基类（StereoData）

  下一版增加，目前暂时使用AnnData

Class StereoData:
    pass

• 分析基类（ToolBase）

Class ToolBase(data, method, name=None):
   参数：
     data：分析数据，AnnData（下一版调为StereoData）
     method: 分析方法，str
     name：分析名字，str，作为结果存取的key
   属性：
     self.data
     self.method
     self.name
     self.exp_matrix
   方法  
     check_param(): 检查参数
     sparse2array(): 将self.exp_matrix稀疏矩阵转换成np.array
     get_params(var_info): 获取参数变量名以及相应的值
     add_result(): 保存分析结果

• 结果基类（StereoResult）

Class StereoResult(name='stereo', param=None):
  参数：
    name： 名称， str
    param：参数信息，dict
  属性：
    self.name
    self.param
  方法：
    update_params(v): 更新参数
    __str__(): 返回类的参数信息及结果信息
    __repr__()：打印类的参数信息及结果信息

开发说明

1 tool分析模块开发
tool分析模块主要包含两个内容的开发，分别为分析类以及结果类的开发。

1.1 分析子类编写

1.1.1 子类需继承基类，以及主要重写和实现相关的方法

• 获取参数
• 继承父类构造方法，必须要有的参数：data、method、name
• 重写参数检查方法: self.check_param()
• 实现分析运行方法: self.fit()

1.1.2 可自定义分析需要的参数跟方法

编写示例：

from ..core.tool_base import ToolBase
from ..log_manager import logger


class DimReduce(ToolBase):
    def __init__(self, data: AnnData, method='pca', n_pcs=2, min_variance=0.01, n_iter=250,
                 n_neighbors=5, min_dist=0.3, inplace=False, name='dim_reduce'):
        # 获取参数
        self.params = self.get_params(locals())
        # 继承父类构造方法
        super(DimReduce, self).__init__(data=data, method=method, name=name)
        # 参数检查
        self.check_param()
        # 自定义分析所需属性，结合分析需要
        self.n_pcs = n_pcs
        self.min_variance = min_variance
        self.n_iter = n_iter
        self.n_neighbors = n_neighbors
        self.min_dist = min_dist
        self.result = DimReduceResult(name=name, param=self.params)
     
    def check_param(self): #  重写参数检查方法，根据分析所传参数以及其值范围进行检查约束
        """
        Check whether the parameters meet the requirements.
        :return:
        """
        super(DimReduce, self).check_param()
        if self.method.lower() not in ['pca', 'tsen', 'umap', 'factor_analysis', 'low_variance']:
            logger.error(f'{self.method} is out of range, please check.')
            raise ValueError(f'{self.method} is out of range, please check.')
    
    def fit(self, exp_matrix=None):
        # 自定义分析方法实现逻辑
        exp_matrix = exp_matrix if exp_matrix is not None else self.exp_matrix
        if self.method == 'low_variance':
            self.result.x_reduce = low_variance(exp_matrix, self.min_variance)
        elif self.method == 'umap':
            self.result.x_reduce = u_map(exp_matrix, self.n_pcs, self.n_neighbors, self.min_dist)
        else:
            pca_res = pca(exp_matrix, self.n_pcs)
            self.result.x_reduce = pca_res['x_pca']
            self.result.variance_ratio = pca_res['variance_ratio']
            self.result.variance_pca = pca_res['variance']
            self.result.pcs = pca_res['pcs']
         # 通过self.add_result()添加结果回数据类
        self.add_result(result=self.result, key_added=self.name)

1.2 结果子类编写

• 子类需继承结果基类

• 根据分析结果，自定义该结果类存放的内容以及实现的方法

编写示例：

class FindMarkerResult(StereoResult):
    def __init__(self, name: str = 'find_marker', param: Optional[dict] = None,
                 degs_data: Optional[pd.DataFrame] = None):
        super(FindMarkerResult, self).__init__(name, param)
        self.degs_data = degs_data

    def __str__(self):
        info = super(FindMarkerResult, self).__str__()
        if self.degs_data is not None:
            info += f'    result: a DataFrame which has `genes`,`pvalues`,`pvalues_adj`, `log2fc`, `score` columns.\n'
            info += f'    the shape is: {self.degs_data.shape}'
        return info

    def top_k_marker(self, top_k_genes=10, sort_key='pvalues', ascend=False):
        """
        obtain the first k significantly different genes
        :param top_k_genes:  the number of top k
        :param sort_key: sort by the column
        :param ascend: the ascend order of sorting.
        :return:
        """
        if self.degs_data is not None:
            top_k_data = self.degs_data.sort_values(by=sort_key, ascending=ascend).head(top_k_genes)
            return top_k_data
        else:
            logger.warning('the result of degs is None, return None.')
            return None

2 可视化模块

• 绘图基础单元目前包含热图以及散点图
• 每个可视化功能，主要基于分析需展示的结果来决定
• 目前传入数据类主要是anndata，但在获取绘图数据时，应尽可能与anndata抽离，可针对结果类进行数据获取的函数
• 目前采用的面向过程编程，后续看下是否需要改成面向对象

3 书写规范

1. 编码要求符合pep8编写规范
2. 文件命名统一采用小写、下划线；类的命名采用驼峰命名法。

   eg：文件名：dim_reduce.py 类名：DimReduce

3. 变量命名采用小写，应该尽可能有意义，避免采用无意的命名，如：a=1， b=2等等
4. 注释信息要完善，每个函数应该编写其注释信息
5. 建议使用pycharm进行编辑，编辑器可自动检查编写的代码是否符合规范，且有相关提示。其他编辑器也可以借助安装相关插件来检查。
   

Hello
Thanks for developing the stereopy. Recently, when I used stereopy for tissue segmentation (function: tissue_extraction_to_bgef), I found that the axolotl data on the official website of Huada spatiotemporal omics (https://db.cngb.org/stomics/artista/download.html) was not aligned with the genetic data. I checked the paper, mentioned that the author performed the alignment manually. so I want to know if there is a way to align and complete the segmentation of the tissue through the stereopy package?

gene scatter plot:

image:

tissue cut scatter plot:

Hello, Stereopy team,

When I use the data_helper.merge function to merge two slices and save them as an anndata file using st.io.stereo_to_anndata(data, flavor='scanpy'......), two files are generated .But i want get only one merged file.

I am looking forward to your response.

Sincerely

Hi, when I run 'data.tl.leiden(neighbors_res_key='neighbors', res_key='leiden')', there is an error below:

data.tl.filter_cells(min_gene=200, pct_counts_mt=10, min_n_genes_by_counts=3, inplace=True)
data.tl.filter_genes(min_cell=10)
data.tl.raw_checkpoint()
data.tl.normalize_total(target_sum=10000)
data.tl.log1p()
data.tl.highly_variable_genes(min_mean=0.0125, max_mean=3,min_disp=0.5,
                              n_top_genes=2000, res_key='highly_variable_genes')
data.tl.scale(max_value=10, zero_center=True)
data.tl.pca(use_highly_genes=False, n_pcs=50, res_key='pca')
data.tl.neighbors(pca_res_key='pca', n_pcs=50, res_key='neighbors')
data.tl.umap(pca_res_key='pca', neighbors_res_key='neighbors', res_key='umap')
data.tl.leiden(neighbors_res_key='neighbors', res_key='leiden')

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/NAS/lh/software/miniconda3/envs/st/lib/python3.8/site-packages/stereopy-0.9.0-py3.8.egg/stereo/core/st_pipeline.py", line 34, in wrapped
    res = func(*args, **kwargs)
  File "/NAS/lh/software/miniconda3/envs/st/lib/python3.8/site-packages/stereopy-0.9.0-py3.8.egg/stereo/core/st_pipeline.py", line 590, in leiden
    clusters = le(neighbor=neighbor, adjacency=connectivities, directed=directed, resolution=resolution,
  File "/NAS/lh/software/miniconda3/envs/st/lib/python3.8/site-packages/stereopy-0.9.0-py3.8.egg/stereo/algorithm/leiden.py", line 89, in leiden
    part = leidenalg.find_partition(g, partition_type, **partition_kwargs)
  File "/NAS/lh/software/miniconda3/envs/st/lib/python3.8/site-packages/leidenalg/functions.py", line 81, in find_partition
    partition = partition_type(graph,
  File "/NAS/lh/software/miniconda3/envs/st/lib/python3.8/site-packages/leidenalg/VertexPartition.py", line 840, in __init__
    self._partition = _c_leiden._new_RBConfigurationVertexPartition(pygraph_t,
BaseException: Could not construct partition: Weight vector not the same size as the number of edges.

I don't know how to solve it? Thanks!

这个stereopy的数据好像不能下载，想试试程序，请问有办法吗？

• core

• scatter: the basic func of scatter

• heatmap: the basic func of heatmap

• qc

• plot_spatial_distribution: draw the total_count and n_gene_by_count in the spatial position.

• plot_genes_count: draw the relation of total_count with n_gene_by count and mt_genes_pt.

• plot_violin_distribution: draw the violin distribution of total_count , n_gene_by count and mt_genes_pt.

• scatter

• plot_scatter: plot the scatter figure of the bins.

• dim_reduce

• plot_dim_reduce: specify a specific key and draw the distribution of the bin after dimension-reduction

• marker_genes

• plot_marker_genes: draw the gravel figure of marker gene whose score is in the top few

• plot_heatmap_marker_genes: draw the heatmap figure of marker gene whose score is in the top few in cluster groups.

• clustering

• plot_spatial_cluster: draw the spatial distribution of clusters.

Hi, I am on a mac (2.3 GHz 8-Core Intel Core i9) and I am having a lot of trouble getting stereopy to work. Is there a docker container/conda environment which can be used to install stereopy? While it says it is installed, when I run several tools it says it requires further modules/packages, a lot of these having incompatibilities with the existing modules. Any streamlined installation methods would be greatly appreciated.

dear authors:
error occurs when i trying 'import stereo' in python3.8, here is the message:

Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda3\envs\python38\lib\site-packages\stereo_init_.py", line 6, in
from . import io
File "D:\Anaconda3\envs\python38\lib\site-packages\stereo\io_init_.py", line 9, in
from .reader import read_gef, read_gem, read_ann_h5ad, read_stereo_h5ad, anndata_to_stereo, stereo_to_anndata
File "D:\Anaconda3\envs\python38\lib\site-packages\stereo\io\reader.py", line 28, in
from shapely.geometry import Point, MultiPoint
File "C:\Users\Administrator\AppData\Roaming\Python\Python38\site-packages\shapely\geometry_init_.py", line 4, in
from .base import CAP_STYLE, JOIN_STYLE
File "C:\Users\Administrator\AppData\Roaming\Python\Python38\site-packages\shapely\geometry\base.py", line 19, in
from shapely.coords import CoordinateSequence
File "C:\Users\Administrator\AppData\Roaming\Python\Python38\site-packages\shapely\coords.py", line 8, in
from shapely.geos import lgeos
File "C:\Users\Administrator\AppData\Roaming\Python\Python38\site-packages\shapely\geos.py", line 154, in
lgeos = CDLL(os.path.join(sys.prefix, 'Library', 'bin', 'geos_c.dll'))
File "D:\Anaconda3\envs\python38\lib\ctypes_init.py", line 373, in init
self._handle = _dlopen(self._name, mode)
FileNotFoundError: Could not find module 'D:\Anaconda3\envs\python38\Library\bin\geos_c.dll' (or one of its dependencies). Try using the full path with constructor syntax.

how can i fix it?
best wishes, thank you.
han

Hi,

So I manage to install Stereopy correctly and load it in my Jupyter notebook. However when I try to load my .h5ad data, I get the FileNotFoundError: Please ensure there is a file error.

Below is the code I used:

import os
from os.path import join as jn
import warnings
#warnings.filterwarnings('ignore')

import stereo as st


mouse_data = '~/STOMICS/Stomics_data/E16.5_E2S3.MOSTA.h5ad'
mouse_data

data = st.io.read_stereo_h5ad(file_path=mouse_data, use_raw=True, use_result=True)

This is the error in detail:

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
Cell In [21], line 1
----> 1 data = st.io.read_stereo_h5ad(file_path=mouse_data, use_raw=True, use_result=True)

File ~/miniconda3/envs/st/lib/python3.8/site-packages/stereo/utils/read_write_utils.py:19, in ReadWriteUtils.check_file_exists.<locals>.wrapped(*args, **kwargs)
     17     if kwargs.get('file_path'):
     18         if not os.path.exists(kwargs.get('file_path')):
---> 19             raise FileNotFoundError("Please ensure there is a file")
     20 else:
     21     if args:

FileNotFoundError: Please ensure there is a file

This is my Stereopy version:

(st) pip show stereopy
Name: stereopy
Version: 0.6.0
Summary: Spatial transcriptomic analysis in python.
Home-page: https://github.com/BGIResearch/stereopy
Author: BGIResearch
Author-email: [email protected]
License: 
Location: /mnt/nectar_volume/home/sama0023/miniconda3/envs/st/lib/python3.8/site-packages
Requires: albumentations, anndata, arboreto, bokeh, colorcet, dask, datashader, distributed, gefpy, glog, gtfparse, h5py, harmonypy, holoviews, hotspotsc, hvplot, igraph, imageio, Jinja2, joblib, KDEpy, keras, leidenalg, loompy, louvain, matplotlib, natsort, numba, numpy, opencv-python, packaging, pandas, panel, param, patsy, phenograph, pillow, protobuf, pyarrow, requests, scikit-image, scikit-learn, scipy, seaborn, setuptools, shapely, slideio, spatialpandas, squidpy, statsmodels, tables, tensorflow, tensorflow-io-gcs-filesystem, tifffile, torch, torchvision, tqdm, typing-extensions, umap-learn, urllib3, xarray
Required-by: 

This is my file structure:

sama0023@xxx:~/STOMICS$ tree
.
├── requirements.txt
├── Stomics_data
│   └── E16.5_E2S3.MOSTA.h5ad
└── STOMICS.ipynb

1 directory, 3 files

Please help!

Running data.tl.find_marker_genes(cluster_res_key='phenograph', method='t_test', use_highly_genes=False, use_raw=True) resulted in a ZeroDivisionError

[2023-02-28 11:28:00][Stereo][3139][47732363878080][st_pipeline][35][INFO]: start to run find_marker_genes...
[2023-02-28 11:28:00][Stereo][3139][47732363878080][tool_base][117][INFO]: read group information, grouping by group column.
[2023-02-28 11:28:00][Stereo][3139][47732363878080][tool_base][155][INFO]: start to run...
Find marker gene:  64%|██████████████████████████████████████████████▍                         | 67/104 [00:15<00:08,  4.37it/s]
---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
Cell In[6], line 1
----> 1 data.tl.find_marker_genes(cluster_res_key='phenograph', method='t_test', use_highly_genes=False, use_raw=True)

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/core/st_pipeline.py:37, in logit.<locals>.wrapped(*args, **kwargs)
     35 logger.info('start to run {}...'.format(func.__name__))
     36 tk = tc.start()
---> 37 res = func(*args, **kwargs)
     38 logger.info('{} end, consume time {:.4f}s.'.format(func.__name__, tc.get_time_consumed(key=tk, restart=False)))
     39 return res

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/core/st_pipeline.py:745, in StPipeline.find_marker_genes(self, cluster_res_key, method, case_groups, control_groups, corr_method, use_raw, use_highly_genes, hvg_res_key, res_key, output)
    743 data = self.raw if use_raw else self.data
    744 data = self.subset_by_hvg(hvg_res_key, use_raw=use_raw, inplace=False) if use_highly_genes else data
--> 745 tool = FindMarker(data=data, groups=self.result[cluster_res_key], method=method, case_groups=case_groups,
    746                   control_groups=control_groups, corr_method=corr_method, raw_data=self.raw)
    747 self.result[res_key] = tool.result
    748 if output is not None:

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/tools/find_markers.py:63, in FindMarker.__init__(self, data, groups, method, case_groups, control_groups, corr_method, tie_term, raw_data)
     61 self.tie_term = tie_term
     62 self.raw_data = raw_data
---> 63 self.fit()

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/core/tool_base.py:156, in ToolBase.fit_log.<locals>.wrapper(*args, **kwargs)
    153 @functools.wraps(func)
    154 def wrapper(*args, **kwargs):
    155     logger.info('start to run...')
--> 156     func(*args, **kwargs)
    157     logger.info('end to run.')

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/tools/find_markers.py:159, in FindMarker.fit(self)
    157 # self.logger.info('end selelct group')
    158 if self.method == 't_test':
--> 159     result = statistics.ttest(g_data, other_data, self.corr_method)
    160 elif self.method == 'logreg':
    161     if logres_score is None:

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/algorithm/statistics.py:76, in ttest(group, other_group, corr_method)
     75 def ttest(group, other_group, corr_method=None):
---> 76     mean_group, var_group = get_mean_var(group)
     77     mean_rest, var_rest = get_mean_var(other_group)
     78     with np.errstate(invalid="ignore"):

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/functools.py:875, in singledispatch.<locals>.wrapper(*args, **kw)
    871 if not args:
    872     raise TypeError(f'{funcname} requires at least '
    873                     '1 positional argument')
--> 875 return dispatch(args[0].__class__)(*args, **kw)

File /stornext/HPCScratch/home/wang.ch/conda_dir/envs/rapids-22.12/lib/python3.8/site-packages/stereo/utils/hvg_utils.py:41, in _(X, axis)
     39     var = mean_sq - mean ** 2
     40 # enforce R convention (unbiased estimator) for variance
---> 41 var *= X.shape[axis] / (X.shape[axis] - 1)
     42 return mean, var

ZeroDivisionError: division by zero

When I pip install stereopy using pytthon 3.8.10 there are no problems. However, I run into an error trying to do this with python 3.9.5:

pip install stereopy

...
  Attempting uninstall: setuptools
    Found existing installation: setuptools 56.0.0
    Uninstalling setuptools-56.0.0:
      Successfully uninstalled setuptools-56.0.0
    Running setup.py install for pynndescent ... error
    ERROR: Command errored out with exit status 1:
     command: /home/mf/.pyenv/versions/3.9.5/bin/python3.9 -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-hkvk21ac/pynndescent_580104e55fcd428a8187c7566ef5b0a0/setup.py'"'"'; __file__='"'"'/tmp/pip-install-hkvk21ac/pynndescent_580104e55fcd428a8187c7566ef5b0a0/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-nsj8ft48/install-record.txt --single-version-externally-managed --compile --install-headers /home/mf/.pyenv/versions/3.9.5/include/python3.9/pynndescent
         cwd: /tmp/pip-install-hkvk21ac/pynndescent_580104e55fcd428a8187c7566ef5b0a0/
    Complete output (11 lines):
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/home/mf/.pyenv/versions/3.9.5/lib/python3.9/site-packages/setuptools/__init__.py", line 18, in <module>
        from setuptools.dist import Distribution, Feature
      File "/home/mf/.pyenv/versions/3.9.5/lib/python3.9/site-packages/setuptools/dist.py", line 30, in <module>
        from setuptools.depends import Require
      File "/home/mf/.pyenv/versions/3.9.5/lib/python3.9/site-packages/setuptools/depends.py", line 7, in <module>
        from .py33compat import Bytecode
      File "/home/mf/.pyenv/versions/3.9.5/lib/python3.9/site-packages/setuptools/py33compat.py", line 55, in <module>
        unescape = getattr(html, 'unescape', html_parser.HTMLParser().unescape)
    AttributeError: 'HTMLParser' object has no attribute 'unescape'
    ----------------------------------------
ERROR: Command errored out with exit status 1: /home/mf/.pyenv/versions/3.9.5/bin/python3.9 -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-hkvk21ac/pynndescent_580104e55fcd428a8187c7566ef5b0a0/setup.py'"'"'; __file__='"'"'/tmp/pip-install-hkvk21ac/pynndescent_580104e55fcd428a8187c7566ef5b0a0/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-nsj8ft48/install-record.txt --single-version-externally-managed --compile --install-headers /home/mf/.pyenv/versions/3.9.5/include/python3.9/pynndescent Check the logs for full command output.

related problem seems to be: coursera-dl/coursera-dl#778

thanks
Mark

Hi,
Sorry to trouble you!
I have some quesitions with Cell Correction. I used the following codes to get the "SS200000314TL_D1.raw.adjusted.cellbin.gef".Then, I used the "Quick Start (Cell Bin)", but I got few cell number.I don't know why.
###########1.Cell Correction
from stereo.tools.cell_correct import cell_correct
bgef_path = "02.count/SS200000314TL_D1.raw.gef"
mask_path = "03.register/SS200000314TL_D1_regist.tif"
out_dir = "8.analysis/cell_correct_result_1"
only_save_result = False
fast = True
data = cell_correct(out_dir=out_dir,
bgef_path=bgef_path,
mask_path=mask_path,
process_count=10,
only_save_result=only_save_result,
fast=fast)

#########2.Quick Start (Cell Bin)
import warnings
warnings.filterwarnings('ignore')
import stereo as st

read the GEF file information

data_path = ['8.analysis/cell_correct_result_1/SS200000314TL_D1.raw.adjusted.cellbin.gef']
st.io.read_gef_info(data_path)

[2023-02-12 20:46:53][Stereo][149731][139721301030720][reader][762][INFO]: This is GEF file which contains cell bin infomation.
[2023-02-12 20:46:53][Stereo][149731][139721301030720][reader][763][INFO]: bin_type: cell_bins
[2023-02-12 20:46:53][Stereo][149731][139721301030720][reader][769][INFO]: Number of cells: 87
[2023-02-12 20:46:53][Stereo][149731][139721301030720][reader][772][INFO]: Number of gene: 26735
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][775][INFO]: Resolution: 500
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][778][INFO]: offsetX: 3
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][781][INFO]: offsetY: 0
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][784][INFO]: Average number of genes: 1.390804648399353
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][787][INFO]: Maximum number of genes: 28
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][790][INFO]: Average expression: 523.9310302734375
[2023-02-12 20:46:54][Stereo][149731][139721301030720][reader][793][INFO]: Maximum expression: 45450
{'cell_num': 87, 'gene_num': 26735, 'resolution': 500, 'offsetX': 3, 'offsetY': 0, 'averageGeneCount': 1.3908046, 'maxGeneCount': 28, 'averageExpCount': 523.931, 'maxExpCount': 45450}

When I used the GEM to do Cell Correcting, there was an error: bin 1 matrix: min_x=3 len_x=65883 min_y=0 len_y=740227421 matrix_len=48768403177743
python3: /workitems/geftools/main_bgef.cpp:231: void gem2gef(BgefOptions*): Assertion `dnb_matrix.pmatrix_us' failed.
Aborted (core dumped)

from stereo.tools.cell_correct import cell_correct
gem_path = "041.cellcut/SS200000314TL_D1.cellbin.gem"
mask_path = "03.register/SS200000314TL_D1_regist.tif"
out_dir = "8.analysis/cell_correct_result_gem_fast"
only_save_result = False
fast = True
data = cell_correct(out_dir=out_dir,
gem_path=gem_path,
mask_path=mask_path,
process_count=10,
only_save_result=only_save_result,
fast=fast)

Dear authors,

I am trying to install stereopy using the pip install stereopy command.
Unfortunately, I am facing the following error: " FileNotFoundError: [Errno 2] No such file or directory: 'requirements.txt' "

Could you please help me to solve this issue?

Best regards,
Davide Maspero

a group funcs of reading different data with seq format.

• read stereo data
• read 10x data
• read txt
• read h5ad

Following the example code, I am wondering if it is possible to add a scale bar to the cluter scatter visualisation. Many thanks.

• filter

• filter bins by total_count, n_genes_by_count, mt_gene_pt and bins_list.

• filter genes by gene count and genes_list.

• filter bins by position.

• normalize

• total normalize

• quantile normalize

• z-score normalize

• sc_transform

• recipes seruat

• qc

• total count

• n_gene_by_count

• mt_gene_pt

Hello, Stereopy team：

How can I visualize single gene like seurat SpatialFeaturePlot?

Sincerely

aaa

I followed the example and ran the code on jupyter, but I did not get the Interactive scatter, How can I solve it? thanks.

Dear authors,
I am having difficulty installing the stereopy package.

When I run:
pip install stereopy==0.2.4
I get the error:
ERROR: Could not find a version that satisfies the requirement gefpy>=0.1.1 (from stereopy) (from versions: none)
ERROR: No matching distribution found for gefpy>=0.1.1

When I run:
pip install stereopy
I get the error:
FileNotFoundError: [Errno 2] No such file or directory: 'requirements.txt'

And it seems the package has heavy dependency, so it is hard to directly build it.

Could you please help me in understanding the problem and in getting around it?

Kind regards,
Arinze.

你好，我按照教程代码运行交互式截取感兴趣区域，但是界面没有显示。

%matplotlib inline

import warnings
warnings.filterwarnings('ignore')
import stereo as st
import  os  
os.chdir('C:/Users/llmt/Desktop/jupyter  notebook')
path = 'data/demo/SS200000135TL_D1.tissue.gef'
data = st.io.read_gef(path, bin_size=40)
data.tl.cal_qc()
ins = data.plt.interact_spatial_scatter(width=500, height=500, poly_select=False)
ins.show()

Hi,

I have tried to run the Quick Start (Square Bin). But it keeps reporting errors on the following line:

fig = data.plt.umap(gene_names=['Atpif1', 'Tmsb4x'], res_key='umap')

The error message is shown below:

I used the /home/Jianning/Stereoseq_Demo_Data/SS200000135TL_D1.tissue.gef file to run the script. I don't know why it can't return the image that was shown in the example. I would appreciate it if you would like to kindly help me with it.

With thanks,
Jianning

Hi, I have run into errors for both cell segmentation methods. I have included the output. The tif input image is from ImageQC and did pass.

Hi everyone,

I'm attempting to run stereopy with python=3.9.5 and python=3.8 in a separate conda environment. Every installment displays a successful message. However, I failed with messages in python such as

'ImportError: Could not import 'Markup' from 'jinja2' (./miniconda3/lib/python3.9/site-packages/jinja2/_init_.py))'
'ImportError: cannot import name 'Markup' from 'jinja2' (./miniconda3/envs/Stereopy_env/lib/python3.8/site-packages/jinja2/_init_.py)'

Someone stated that it can only be used with Python 3.8 or Python 3.7.
#59

However, python3.9 is also supported in another post.
#11

Could you please provide me with detailed information on a successful installment as well as a test case?

Thank you in advance!