def get_CGM_data(dir_path): '''Extract raw data from the file.''' lst = dir_list_gen(dir_path, 'TAB') #for kn in range(len(lst)): out = [] with open(lst[0], 'rb') as f: reader = csv.reader(f, delimiter='\t') for row in reader: out.append(row) out = [[row[i] for row in out] for i in range(len(out[0]))] timestamps, values, device_name, device_id = \ CGM_data_extraction(out) return numpy.vstack((numpy.array(timestamps), numpy.array(values))), \ device_name, device_id
def get_CGM_data(dir_path): '''Extract raw data from the file.''' lst = dir_list_gen(dir_path,'TAB') #for kn in range(len(lst)): out = [] with open(lst[0],'rb') as f: reader = csv.reader(f, delimiter='\t') for row in reader: out.append(row) out = [[row[i] for row in out] for i in range(len(out[0]))] timestamps, values, device_name, device_id = \ CGM_data_extraction(out) return numpy.vstack((numpy.array(timestamps), numpy.array(values))), \ device_name, device_id
def get_BG_data(dir_path): '''Extract raw data from the file.''' lst = dir_list_gen(dir_path,'CSV') #for kn in range(len(lst)): out = [] with open(lst[0],'rb') as f: reader = csv.reader(f, delimiter=';') for row in reader: out.append(row) print 'get_BG_data:', len(out[0]) out = [[row[i] for row in out] for i in range(len(out[0]))] timestamps, bolus, basal, bg, carbs, pen_doses = \ BG_data_extraction(out) print 'length of timestamps:', len(timestamps) print 'length of bolus:', len(bolus) return numpy.vstack((numpy.array(timestamps), numpy.array(bolus))), \ numpy.vstack((numpy.array(timestamps), numpy.array(basal))), \ numpy.vstack((numpy.array(timestamps), numpy.array(bg))), \ numpy.vstack((numpy.array(timestamps), numpy.array(carbs))), \ numpy.vstack((numpy.array(timestamps), numpy.array(pen_doses))) \
def import_module_xls(dir_path): '''Reads in data from an xls spreadsheet and returns the relavent data in lists.''' # Initialise return values bolusdates = [] bolustimes = [] bolusdata = [] basaldates = [] basaltimes = [] basaldata = [] basaladju = [] basaladjl = [] bgdates = [] bgtimes = [] bgdata = [] carbsdata = [] eventsdates = [] eventstimes = [] eventsdata = [] # find the relavent files lst = dir_list_gen(dir_path, 'xls') for legr in lst: book = xlrd.open_workbook(legr) sheet_list = book.sheets() for pages in range(len(sheet_list)): page = book.sheet_by_index(pages) n_cols = page.ncols n_rows = page.nrows temp_sheet = [] if n_cols > 0 and n_rows > 0: for col in range(n_cols): # generate a list of lists to represent the row and column data. temp_sheet.append( page.col_values(col, start_rowx=0, end_rowx=n_rows)) loc_bolus = index(temp_sheet[0], 'Bolus') loc_basal = index(temp_sheet[0], 'Basal') loc_bg = index(temp_sheet[0], 'Evaluated results') loc_events = index(temp_sheet[0], 'Events') # find out which sets of data are on the current sheet. section_list = [loc_bolus, loc_basal, loc_bg, loc_events] section_names = ['Bolus', 'Basal', 'BG', 'Events'] index_dict = dict(zip(section_list, section_names)) revindex_dict = dict(zip(section_names, section_list)) name = sorted_dict_values(index_dict) name_dict = dict(zip(name, [0, 1, 2, 3])) revname_dict = dict(zip([0, 1, 2, 3], name)) if loc_bolus != None: bolusdates, bolustimes, bolusdata = xls_get_bolus( temp_sheet, bolusdates, bolustimes, bolusdata, page, loc_bolus, name_dict, revindex_dict, revname_dict, n_cols) if loc_basal != None: basaldates, basaltimes, basaldata, basaladju, basaladjl = \ xls_get_basal( temp_sheet, basaldates, basaltimes, basaldata, basaladju, basaladjl, page, loc_basal, name_dict, revindex_dict, revname_dict, n_cols) if loc_bg != None: bgdates, bgtimes, bgdata, carbsdata = xls_get_bg( temp_sheet, bgdates, bgtimes, bgdata, carbsdata, page, loc_bg, name_dict, revindex_dict, revname_dict, n_cols) if loc_events != None: eventsdates, eventstimes, eventsdata = xls_get_events( temp_sheet, eventsdates, eventstimes, eventsdata, page, loc_events, name_dict, revindex_dict, \ revname_dict, n_cols) bolusstream = xls_condition_input(bolusdates, bolustimes, bolusdata) basalstream = xls_condition_input(basaldates, basaltimes, basaldata) basaladjustream = xls_condition_input(basaldates, basaltimes, basaladju) basaladjlstream = xls_condition_input(basaldates, basaltimes, basaladjl) bgstream = xls_condition_input(bgdates, bgtimes, bgdata) print 'Carbsdata', type(carbsdata), type(carbsdata[0]) print carbsdata carbstream = xls_condition_input(bgdates, bgtimes, carbsdata) eventstream = xls_condition_input(eventsdates, eventstimes, eventsdata, noconv=True) return bolusstream, basalstream, basaladjustream, basaladjlstream, \ bgstream, carbstream, eventstream
def import_module_xls(dir_path): '''Reads in data from an xls spreadsheet and returns the relavent data in lists.''' # Initialise return values bolusdates = [] bolustimes = [] bolusdata = [] basaldates = [] basaltimes = [] basaldata = [] basaladju = [] basaladjl = [] bgdates = [] bgtimes = [] bgdata = [] carbsdata = [] eventsdates = [] eventstimes = [] eventsdata = [] # find the relavent files lst = dir_list_gen(dir_path,'xls') for legr in lst: book = xlrd.open_workbook(legr) sheet_list = book.sheets() for pages in range(len(sheet_list)): page = book.sheet_by_index(pages) n_cols = page.ncols n_rows = page.nrows temp_sheet = [] if n_cols > 0 and n_rows > 0: for col in range(n_cols): # generate a list of lists to represent the row and column data. temp_sheet.append( page.col_values(col, start_rowx=0, end_rowx=n_rows)) loc_bolus = index(temp_sheet[0],'Bolus') loc_basal = index(temp_sheet[0],'Basal') loc_bg = index(temp_sheet[0],'Evaluated results') loc_events = index(temp_sheet[0],'Events') # find out which sets of data are on the current sheet. section_list = [loc_bolus, loc_basal, loc_bg, loc_events] section_names = ['Bolus', 'Basal', 'BG', 'Events'] index_dict = dict(zip(section_list, section_names)) revindex_dict = dict(zip(section_names, section_list)) name = sorted_dict_values(index_dict) name_dict = dict(zip(name, [0, 1, 2, 3])) revname_dict = dict(zip([0, 1, 2, 3], name)) if loc_bolus != None: bolusdates, bolustimes, bolusdata = xls_get_bolus( temp_sheet, bolusdates, bolustimes, bolusdata, page, loc_bolus, name_dict, revindex_dict, revname_dict, n_cols) if loc_basal != None: basaldates, basaltimes, basaldata, basaladju, basaladjl = \ xls_get_basal( temp_sheet, basaldates, basaltimes, basaldata, basaladju, basaladjl, page, loc_basal, name_dict, revindex_dict, revname_dict, n_cols) if loc_bg != None: bgdates, bgtimes, bgdata, carbsdata = xls_get_bg( temp_sheet, bgdates, bgtimes, bgdata, carbsdata, page, loc_bg, name_dict, revindex_dict, revname_dict, n_cols) if loc_events != None: eventsdates, eventstimes, eventsdata = xls_get_events( temp_sheet, eventsdates, eventstimes, eventsdata, page, loc_events, name_dict, revindex_dict, \ revname_dict, n_cols) bolusstream = xls_condition_input(bolusdates, bolustimes, bolusdata) basalstream = xls_condition_input(basaldates, basaltimes, basaldata) basaladjustream = xls_condition_input(basaldates, basaltimes, basaladju) basaladjlstream = xls_condition_input(basaldates, basaltimes, basaladjl) bgstream = xls_condition_input(bgdates, bgtimes, bgdata) print 'Carbsdata',type(carbsdata),type(carbsdata[0]) print carbsdata carbstream = xls_condition_input(bgdates, bgtimes, carbsdata) eventstream = xls_condition_input(eventsdates, eventstimes, eventsdata, noconv = True) return bolusstream, basalstream, basaladjustream, basaladjlstream, \ bgstream, carbstream, eventstream