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I ran memory profiler on our examples to track down memory consuming functions. I thought that I'd share the results here if someone else wants to look at it. The examples listed here have a peak consumption of over 1 GiB.
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datasets/plot_brainstorm_data.py(MRG: Better memory usage (#2) #2977) -
datasets/plot_spm_faces_dataset.py(MRG: Better memory usage (#2) #2977) -
decoding/plot_decoding_spatio_temporal_source.py(MRG: Better memory usage (#2) #2977) -
decoding/plot_decoding_time_generalization.py(MRG: Better memory usage (#2) #2977) -
inverse/plot_covariance_whitening_dspm.py(MRG: Better memory usage (#2) #2977) -
inverse/plot_tf_lcmv.py(MRG: Better memory usage (#2) #2977) -
visualization/plot_meg_eeg_fields_3d.py(MRG: Better memory usage (#2) #2977) -
forward/plot_source_space_morphing.py(MRG: Less memory #2972) -
preprocessing/plot_resample.py(MRG: Less memory #2972) -
simulation/plot_simulate_raw_data.py(MRG: Less memory #2972) -
stats/plot_linear_regression_raw.py(MRG: Less memory #2972) -
time_frequency/plot_compute_raw_data_spectrum.py(MRG: Less memory #2972) -
time_frequency/plot_epochs_spectra.py(MRG: Less memory #2972)