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running pfire-integration-test with python3.6 on testdata/brain_2d
`
/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/core/_asarray.py:136: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return array(a, dtype, copy=False, order=order, subok=True)
Traceback (most recent call last):
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/bin/pfire-integration-test", line 11, in
load_entry_point('pfire-benchmarking==0.1', 'console_scripts', 'pfire-integration-test')()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/main.py", line 41, in main
testsuite.run_tests()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/testdespatcher.py", line 99, in run_tests
test.generate_report()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/cross_validate.py", line 84, in generate_report
cmpname="ShIRT")
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 106, in compare_image_results
mi_pfire = calculate_proficiency(fixed_path, pfire_path)
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 88, in calculate_proficiency
res = calculate_mutual_information(alpha_data, beta_data, return_hist=True)
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 55, in calculate_mutual_information
bins=bin_edges, density=True)
File "<array_function internals>", line 6, in histogram2d
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/lib/twodim_base.py", line 713, in histogram2d
hist, edges = histogramdd([x, y], bins, range, normed, weights, density)
File "<array_function internals>", line 6, in histogramdd
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/lib/histograms.py", line 1031, in histogramdd
'The dimension of bins must be equal to the dimension of the '
ValueError: The dimension of bins must be equal to the dimension of the sample x.
`
The text was updated successfully, but these errors were encountered:
running pfire-integration-test with python3.6 on testdata/brain_2d
`
/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/core/_asarray.py:136: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return array(a, dtype, copy=False, order=order, subok=True)
Traceback (most recent call last):
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/bin/pfire-integration-test", line 11, in
load_entry_point('pfire-benchmarking==0.1', 'console_scripts', 'pfire-integration-test')()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/main.py", line 41, in main
testsuite.run_tests()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/testdespatcher.py", line 99, in run_tests
test.generate_report()
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/cross_validate.py", line 84, in generate_report
cmpname="ShIRT")
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 106, in compare_image_results
mi_pfire = calculate_proficiency(fixed_path, pfire_path)
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 88, in calculate_proficiency
res = calculate_mutual_information(alpha_data, beta_data, return_hist=True)
File "/home/tartarini/deleteme/pFIRE/benchmarking/pfire_benchmarking/analysis_routines.py", line 55, in calculate_mutual_information
bins=bin_edges, density=True)
File "<array_function internals>", line 6, in histogram2d
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/lib/twodim_base.py", line 713, in histogram2d
hist, edges = histogramdd([x, y], bins, range, normed, weights, density)
File "<array_function internals>", line 6, in histogramdd
File "/home/tartarini/deleteme/pFIRE/benchmarking/venv-py36/lib64/python3.6/site-packages/numpy/lib/histograms.py", line 1031, in histogramdd
'The dimension of bins must be equal to the dimension of the '
ValueError: The dimension of bins must be equal to the dimension of the sample x.
`
The text was updated successfully, but these errors were encountered: