Reads filtration change seq length + RF model update #5
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shacharmo
requested changes
Sep 30, 2020
IgOmeProfiling_pipeline.py
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| @@ -42,7 +42,7 @@ def run_pipeline(fastq_path, barcode2samplename_path, samplename2biologicalcondi | |||
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| module_parameters = [fastq_path, first_phase_output_path, first_phase_logs_path, | |||
| barcode2samplename_path, left_construct, right_construct, | |||
| max_mismatches_allowed, min_sequencing_quality, first_phase_done_path, | |||
| max_mismatches_allowed, min_sequencing_quality, minimal_length_required,first_phase_done_path, | |||
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Mismatch with the definition in read_filtration/module_wrapper.py.
You define that as a named parameter (starts with --) and pass it here as positional parameter.
Also the order is incorrect/doesn't match, you are passing minimal length as done path.
To summarize, this change is wrong and doesn't work
model_fitting/random_forest.py
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| def get_hyperparameters_grid(seed): | ||
| # Number of trees in random forest | ||
| n_estimators = [int(x) for x in np.linspace(start=100, stop=2000, num=20)] |
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Set parameters using command arguments, parameters shouldn't be hardcoded.
This remark should be applied to entire file, not just this line
model_fitting/random_forest.py
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| for i in range(num_of_configurations_to_sample): | ||
| configuration = {} | ||
| for key in hyperparameters_grid: | ||
| configuration[key] = np.random.choice(hyperparameters_grid[key], size=1)[0] |
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It this seeded? Would we get same results every experiment run?
model_fitting/random_forest.py
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| data.drop(['sample_name', 'label'], axis=1, inplace=True) | ||
| # a matrix of the actual feature values | ||
| X_train = data[train_rows_mask].values | ||
| X_test = data[test_rows_mask].values |
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There is no usage in (modified) code - not X_test and not Y_test
Tool all data rf
Rf parallel
Validation files
…s/IgomeProfiling into change_place_stop_machines
change the place of file AWS stop machines from tools to auxiliaries
fix the script by the new requests
change the path of the wsl tutorial
Order of sort motifs bc
Connect positive motifs to pipeline
Flag num sample build cluster
add new script for summary reads in one csv file
Join samples to groups
The motif samples were by sort_by_num_samples, sort_by_unique_memebers, sort_by_cluster_size now its sort_by_num_samples, sort_by_cluster_size , sort_by_unique_memebers when unique members goes from low to high
changed the order of the samples
fixed bug of biological condition type value
Fix unite motifs
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