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
