The Kernel crashed when I run tfi.scan

[Zhangruiqi111]

When I run this command : tfi.scan(fpr=0.02,motifs=None, verbose=True)
Error reported as follows ： The Kernel crashed while executing code in the current cell or a previous cell.
So I do it in batches ，100 rows are processed at a time ，
`import math
peaks = pd.read_csv("cicero_output/processed_peak_file.csv", index_col=0)
peaks = peaks[2000:3000]
df_results = []
batch_size = 100
num_batches = math.ceil(len(peaks)/100)

def process_batch(batch_peaks):
tfi = ma.TFinfo(peak_data_frame=batch_peaks, ref_genome=ref_genome, genomes_dir=None)
tfi.scan(fpr=0.02, motifs=None, verbose=True)
tfi.reset_filtering()
tfi.filter_motifs_by_score(threshold=10)
tfi.make_TFinfo_dataframe_and_dictionary(verbose=True)
return tfi.to_dataframe()

for batch_index in range(num_batches):
start_index = batch_index * batch_size
end_index = min((batch_index + 1) * batch_size, len(peaks))
batch_peaks = peaks.iloc[start_index:end_index].copy()
df = process_batch(batch_peaks)
df_results.append(df)`

But an error is still reported ：
The Kernel crashed while executing code in the current cell or a previous cell.
I installed gimmemotifs with conda first and then celloracle with pip , But it didn't work.
So I think there is something wrong with the data :(

[baoa2ta]

Were able to solve this issue? I am having the same problem

[NN0412]

Hi I am having the issue where python keeps killing the process when running tfi.scan(fpr=0.02, motifs=None, verbose=True).have you solved your problem yet? At this step, my Python kernel always crashes, and it always gets stuck at 0% of the process. I tried changing gimmemotifs to version 0.14.4, but it still doesn't work. I'm not sure if it's because my gimmemotifs library was installed using pip instead of conda.

[wangxuann1995]

Use conda install gimmemotifs before pip install celloracle. Install specific version 0.17.2 gimmemotifs

[NN0412]

在 pip install celloracle 之前使用 conda install gimmemotifs。安装特定版本 0.17.2 gimmemotifs

yes.Last week, I already solved the problem using a method similar to yours. You were right. Thank you very much.