* 겪고 있는 문제 상황을 최대한 자세하게 작성해주세요.

* 문제 해결을 위해 어떤 시도를 해보았는지 구체적으로 함께 알려주세요.

이러한 에러가 반복적으로 떠서 chat gpt에게 질문도 해보았으나,

전혀 해결되지 않습니다.

scanpy라는 라이브러리 사용해서 분석하고 있는데,

혹시 해결 방법 알고 계시면 해결 부탁드립니다 ㅠㅠ

# %%

# Core scverse libraries

import scanpy as sc

import anndata as ad

import numpy as np




# Data retrieval

import pooch




# %%

sc.settings.set_figure_params(dpi=50, facecolor="white")




# %%

EXAMPLE_DATA = pooch.create(

    path=pooch.os_cache("scverse_tutorials"),

    base_url="doi:10.6084/m9.figshare.22716739.v1/",

)

EXAMPLE_DATA.load_registry_from_doi()




# %%

samples = {

    "s1d1": "s1d1_filtered_feature_bc_matrix.h5",

    "s1d3": "s1d3_filtered_feature_bc_matrix.h5",

}

adatas = {}




for sample_id, filename in samples.items():

    path = EXAMPLE_DATA.fetch(filename)

    sample_adata = sc.read_10x_h5(path)

    sample_adata.var_names_make_unique()

    adatas[sample_id] = sample_adata




adata = ad.concat(adatas, label="sample")

adata.obs_names_make_unique()




# %%

# mitochondrial genes, "MT-" for human, "Mt-" for mouse

adata.var["mt"] = adata.var_names.str.startswith("MT-")

# ribosomal genes

adata.var["ribo"] = adata.var_names.str.startswith(("RPS", "RPL"))

# hemoglobin genes

adata.var["hb"] = adata.var_names.str.contains("^HB[^(P)]")




# %%

sc.pp.calculate_qc_metrics(

    adata, qc_vars=["mt", "ribo", "hb"], inplace=True, log1p=True

)




# %%

sc.pl.violin(

    adata,

    ["n_genes_by_counts", "total_counts", "pct_counts_mt"],

    jitter=0.4,

    multi_panel=True,

)




# %%

sc.pl.scatter(adata, "total_counts", "n_genes_by_counts", color="pct_counts_mt")




# %%

sc.pp.filter_cells(adata, min_genes=100)

sc.pp.filter_genes(adata, min_cells=3)




# %%

sc.pp.scrublet(adata, batch_key="sample")




# %%

# Saving count data

adata.layers["counts"] = adata.X.copy()




# %%

# Normalizing to median total counts

sc.pp.normalize_total(adata)

# Logarithmize the data

sc.pp.log1p(adata)




# %%

sc.pp.highly_variable_genes(adata, n_top_genes=2000, batch_key="sample")




# %%

sc.pl.highly_variable_genes(adata)




# %%

sc.tl.pca(adata)




# %%

sc.pl.pca_variance_ratio(adata, n_pcs=50, log=True)




# %%

sc.pl.pca(

    adata,

    color=["sample", "sample", "pct_counts_mt", "pct_counts_mt"],

    dimensions=[(0, 1), (2, 3), (0, 1), (2, 3)],

    ncols=2,

    size=2,

)




# %%

sc.pp.neighbors(adata)




# %%

sc.tl.umap(adata)




# %%

sc.pl.umap(

    adata,

    color="sample",

    # Setting a smaller point size to get prevent overlap

    size=2,

)




# %%

random_state = np.random.randint(0, high=2 ** 32 - 2, dtype=np.int64)




# %%

import numpy as np




# Example where high is corrected to fit within int32 bounds

random_number = np.random.randint(low=0, high=2**31, size=1)







# %%

import numpy as np




low = 0

high = 2**31 - 1  # Maximum value for a 32-bit signed integer

rand_int = np.random.randint(low, high)







# %%

import numpy as np




low = 0

high = 2**31 - 1  # Maximum value for a 32-bit signed integer

rand_int = np.random.randint(low, high)







# %%

import random




low = 0

high = 10**10  # Example of a larger range

rand_int = random.randint(low, high)







# %%

import numpy as np




def safe_randint(low, high):

    if not (-2**31 <= high < 2**31):

        raise ValueError("The value of 'high' is out of bounds for int32")

    return np.random.randint(low, high)




low = 0

high = 2**31 - 1  # Example high value within bounds




try:

    rand_int = safe_randint(low, high)

    print(f"Random integer: {rand_int}")

except ValueError as e:

    print(e)







# %%

sc.tl.leiden(adata, flavor="igraph", n_iterations=2)

Exception ignored in: <class 'ValueError'>

Traceback (most recent call last):

File "numpy\\random\\mtrand.pyx", line 780, in numpy.random.mtrand.RandomState.randint

File "numpy\\random\\_bounded_integers.pyx", line 2881, in numpy.random._bounded_integers._rand_int32

ValueError: high is out of bounds for int32