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Hello folks! I'm using kilosort3 on neuropixel 1.0 data in spikeinterface: This error occurs when I export waveforms to phy:
Warning: empty units have been removed when being exported to Phy write_binary_recording with n_jobs 1 chunk_size 3125000 write_binary_recording: 100%|############################################################| 2/2 [00:00<00:00, 17.85it/s] --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Input In [29], in <module> 1 start_time = time.time() ----> 2 export_to_phy(we_KS3, output_folder='_phy_KS3', 3 progress_bar=True, total_memory='100M') 4 print("--- _phy_KS3 took %s seconds ---" % (time.time() - start_time)) File ~\anaconda3\envs\siphy_env\lib\site-packages\spikeinterface\exporters\to_phy.py:161, in export_to_phy(waveform_extractor, output_folder, compute_pc_features, compute_amplitudes, sparsity_dict, copy_binary, max_channels_per_template, remove_if_exists, peak_sign, template_mode, dtype, verbose, **job_kwargs) 158 templates.append(template_full) 159 templates_ind.append(inds_full) --> 161 template_similarity = compute_template_similarity(waveform_extractor, method='cosine_similarity') 163 np.save(str(output_folder / 'templates.npy'), templates) 164 np.save(str(output_folder / 'template_ind.npy'), templates_ind) File ~\anaconda3\envs\siphy_env\lib\site-packages\spikeinterface\toolkit\postprocessing\template_similarity.py:37, in compute_template_similarity(waveform_extractor, waveform_extractor_other, method) 35 else: 36 templates_other_flat = None ---> 37 similarity = sklearn.metrics.pairwise.cosine_similarity(templates_flat, templates_other_flat) 38 # elif method == '': 39 else: 40 raise ValueError(f'compute_template_similarity(method {method}) not exists') File ~\anaconda3\envs\siphy_env\lib\site-packages\sklearn\metrics\pairwise.py:1251, in cosine_similarity(X, Y, dense_output) 1217 """Compute cosine similarity between samples in X and Y. 1218 1219 Cosine similarity, or the cosine kernel, computes similarity as the (...) 1247 kernel matrix : ndarray of shape (n_samples_X, n_samples_Y) 1248 """ 1249 # to avoid recursive import -> 1251 X, Y = check_pairwise_arrays(X, Y) 1253 X_normalized = normalize(X, copy=True) 1254 if X is Y: File ~\anaconda3\envs\siphy_env\lib\site-packages\sklearn\metrics\pairwise.py:147, in check_pairwise_arrays(X, Y, precomputed, dtype, accept_sparse, force_all_finite, copy) 144 dtype = dtype_float 146 if Y is X or Y is None: --> 147 X = Y = check_array( 148 X, 149 accept_sparse=accept_sparse, 150 dtype=dtype, 151 copy=copy, 152 force_all_finite=force_all_finite, 153 estimator=estimator, 154 ) 155 else: 156 X = check_array( 157 X, 158 accept_sparse=accept_sparse, (...) 162 estimator=estimator, 163 ) File ~\anaconda3\envs\siphy_env\lib\site-packages\sklearn\utils\validation.py:800, in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator) 794 raise ValueError( 795 "Found array with dim %d. %s expected <= 2." 796 % (array.ndim, estimator_name) 797 ) 799 if force_all_finite: --> 800 _assert_all_finite(array, allow_nan=force_all_finite == "allow-nan") 802 if ensure_min_samples > 0: 803 n_samples = _num_samples(array) File ~\anaconda3\envs\siphy_env\lib\site-packages\sklearn\utils\validation.py:114, in _assert_all_finite(X, allow_nan, msg_dtype) 107 if ( 108 allow_nan 109 and np.isinf(X).any() 110 or not allow_nan 111 and not np.isfinite(X).all() 112 ): 113 type_err = "infinity" if allow_nan else "NaN, infinity" --> 114 raise ValueError( 115 msg_err.format( 116 type_err, msg_dtype if msg_dtype is not None else X.dtype 117 ) 118 ) 119 # for object dtype data, we only check for NaNs (GH-13254) 120 elif X.dtype == np.dtype("object") and not allow_nan: ValueError: Input contains NaN, infinity or a value too large for dtype('float32').
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Hello folks! I'm using kilosort3 on neuropixel 1.0 data in spikeinterface: This error occurs when I export waveforms to phy:
The text was updated successfully, but these errors were encountered: