xtra¶

Module: `xtra`¶

Unused functions.

Authors:

Arno Klein, 2015 (arno@sagebase.org) http://binarybottle.com

Functions¶

mhealthx.xtra.arff_to_csv(arff_file, output_csv_file=None)¶

Convert an arff file to a row.

Column headers include lines that start with '@attribute ‘, include ‘numeric’, and whose intervening string is not exception_string. The function raises an error if the number of resulting columns does not equal the number of numeric values.

Example input: arff output from openSMILE’s SMILExtract command

Adapted some formatting from: http://biggyani.blogspot.com/2014/08/ converting-back-and-forth-between-weka.html

arff_file : string: arff file (full path)
output_csv_file : string or None: output table file (full path)

row_data : Pandas Series: output table data
output_csv_file : string or None: output table file (full path)

>>> from mhealthx.xtra import arff_to_csv
>>> arff_file = '/Users/arno/csv/test1.csv'
>>> output_csv_file = None #'test.csv'
>>> row_data, output_csv_file = arff_to_csv(arff_file, output_csv_file)

mhealthx.xtra.concatenate_tables_horizontally(tables, output_csv_file=None)¶

Horizontally concatenate multiple table files or pandas DataFrames that have the same number of rows and store as a csv table.

If any one of the members of the tables list is itself a list, call concatenate_tables_vertically() on this list.

tables : list of strings or pandas DataFrames: each component table has the same number of rows
output_csv_file : string or None: output table file (full path)

table_data : Pandas DataFrame: output table data
output_csv_file : string or None: output table file (full path)

>>> import pandas as pd
>>> from mhealthx.xtra import concatenate_tables_horizontally
>>> df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
>>>                     'B': ['B0', 'B1', 'B2', 'B3'],
>>>                     'C': ['C0', 'C1', 'C2', 'C3']},
>>>                    index=[0, 1, 2, 3])
>>> df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
>>>                     'B': ['B4', 'B5', 'B6', 'B7'],
>>>                     'C': ['C4', 'C5', 'C6', 'C7']},
>>>                     index=[0, 1, 2, 3])
>>> tables = [df1, df2]
>>> output_csv_file = None #'./test.csv'
>>> table_data, output_csv_file = concatenate_tables_horizontally(tables, output_csv_file)

mhealthx.xtra.concatenate_tables_vertically(tables, output_csv_file=None)¶

Vertically concatenate multiple table files or pandas DataFrames with the same column names and store as a csv table.

tables : list of table files or pandas DataFrames: each table or dataframe has the same column names
output_csv_file : string or None: output table file (full path)

table_data : Pandas DataFrame: output table data
output_csv_file : string or None: output table file (full path)

>>> import pandas as pd
>>> from mhealthx.xtra import concatenate_tables_vertically
>>> df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
>>>                     'B': ['B0', 'B1', 'B2', 'B3'],
>>>                     'C': ['C0', 'C1', 'C2', 'C3']},
>>>                    index=[0, 1, 2, 3])
>>> df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
>>>                     'B': ['B4', 'B5', 'B6', 'B7'],
>>>                     'C': ['C4', 'C5', 'C6', 'C7']},
>>>                     index=[0, 1, 2, 3])
>>> tables = [df1, df2]
>>> tables = ['/Users/arno/csv/table1.csv', '/Users/arno/csv/table2.csv']
>>> output_csv_file = None #'./test.csv'
>>> table_data, output_csv_file = concatenate_tables_vertically(tables, output_csv_file)

mhealthx.xtra.concatenate_two_tables_horizontally(table1, table2, output_csv_file=None)¶

Horizontally concatenate two table files or pandas DataFrames that have the same number of rows and store as a csv table.

If either of the tables is itself a list, concatenate_two_tables_horizontally() will call concatenate_tables_vertically() on this list.

table1 : string or pandas DataFrame table2 : string or pandas DataFrame

same number of rows as table1

output_csv_file : string or None: output table file (full path)

table_data : Pandas DataFrame: output table data
output_csv_file : string or None: output table file (full path)

>>> import pandas as pd
>>> from mhealthx.xtra import concatenate_two_tables_horizontally
>>> table1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
>>>                     'B': ['B0', 'B1', 'B2', 'B3'],
>>>                     'C': ['C0', 'C1', 'C2', 'C3']},
>>>                    index=[0, 1, 2, 3])
>>> table2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
>>>                     'B': ['B4', 'B5', 'B6', 'B7'],
>>>                     'C': ['C4', 'C5', 'C6', 'C7']},
>>>                     index=[0, 1, 2, 3])
>>> output_csv_file = None #'./test.csv'
>>> table_data, output_csv_file = concatenate_two_tables_horizontally(table1, table2, output_csv_file)

mhealthx.xtra.copy_synapse_table(synapse_table_id, synapse_project_id, table_name='', remove_columns=[], username='', password='')¶

Copy Synapse table to another Synapse project.

synapse_table_id : string: Synapse ID for table to copy
synapse_project_id : string: copy table to project with this Synapse ID
table_name : string: schema name of table
remove_columns : list of strings: column headers for columns to be removed
username : string: Synapse username (only needed once on a given machine)
password : string: Synapse password (only needed once on a given machine)

table_data : Pandas DataFrame: Synapse table contents
table_name : string: schema name of table
synapse_project_id : string: Synapse ID for project within which table is to be written

>>> from mhealthx.xtra import copy_synapse_table
>>> synapse_table_id = 'syn4590865'
>>> synapse_project_id = 'syn4899451'
>>> table_name = 'Copy of ' + synapse_table_id
>>> remove_columns = ['audio_audio.m4a', 'audio_countdown.m4a']
>>> username = ''
>>> password = ''
>>> table_data, table_name, synapse_project_id = copy_synapse_table(synapse_table_id, synapse_project_id, table_name, remove_columns, username, password)

mhealthx.xtra.feature_file_to_synapse_table(feature_file, raw_feature_file, source_file_id, provenance_activity_id, command, command_line, synapse_table_id, username='', password='')¶

Upload files and file handle IDs to Synapse.

feature_file : string: path to file to upload to Synapse
raw_feature_file : string: path to file to upload to Synapse
source_file_id : string: Synapse file handle ID to source file used to generate features
provenance_activity_id : string: Synapse provenance activity ID
command : string: name of command run to generate raw feature file
command_line : string: full command line run to generate raw feature file
synapse_table_id : string: Synapse table ID for table to store file handle IDs, etc.
username : string: Synapse username (only needed once on a given machine)
password : string: Synapse password (only needed once on a given machine)

>>> from mhealthx.xtra import feature_file_to_synapse_table
>>> feature_file = '/Users/arno/Local/wav/test1.wav'
>>> raw_feature_file = '/Users/arno/Local/wav/test1.wav'
>>> source_file_id = ''
>>> provenance_activity_id = ''
>>> command_line = 'SMILExtract -C blah -I blah -O blah'
>>> synapse_table_id = 'syn4899451'
>>> username = ''
>>> password = ''
>>> feature_file_to_synapse_table(feature_file, raw_feature_file, source_file_id, provenance_activity_id, command_line, synapse_table_id, username, password)

mhealthx.xtra.rename_file(old_file, new_filename='', new_path='', file_append='', create_file=False)¶

Rename (and optionally copy) a file / path / file_append.

old_file : string: old file name (full path)
new_filename : string: new file name (not the full path)
new_path : string: replacement path
file_append : string: append to file names
create_file : Boolean: copy file (or just create a string)?

new_filepath : string: new file name (full path, if remove_path not set)

>>> from mhealthx.utils import rename_file
>>> old_file = '/homedir/wav/test1.wav'
>>> new_filename = ''
>>> new_path = '.'
>>> file_append = '.csv'
>>> create_file = True
>>> new_filepath = rename_file(old_file, new_filename, new_path, file_append, create_file)

mhealthx.xtra.write_synapse_table(table_data, synapse_project_id, table_name='', username='', password='')¶

Write data to a Synapse table.

table_data : Pandas DataFrame: Synapse table contents
synapse_project_id : string: Synapse ID for project within which table is to be written
table_name : string: schema name of table
username : string: Synapse username (only needed once on a given machine)
password : string: Synapse password (only needed once on a given machine)

>>> from mhealthx.xio import read_files_from_synapse_row
>>> from mhealthx.xtra import write_synapse_table
>>> synapse_table = 'syn4590865'
>>> row =
>>> column_name = ''
>>> out_path = '.'
>>> username = ''
>>> password = ''
>>> table_data, files = read_files_from_synapse_row(synapse_table, row, column_name, out_path, username, password)
>>> synapse_project_id = 'syn4899451'
>>> table_name = 'Contents of ' + synapse_table
>>> write_synapse_table(table_data, synapse_project_id, table_name, username, password)

xtra¶

Module: xtra¶

Functions¶

Module: `xtra`¶