def data_process(participant_list=[], data_dir=[]):
output_fields = ['task', 'trial', 'rotation_angle_deg', 'target_angle_deg']
output_rows = []
for i in range(0, len(data_dir)):
output_fields.append(participant_list[i])
pc = 0
for j in range(0, len(data_dir[i])):
for k in range(0, len(data_dir[i][j])):
# fields = []
rows = []
input_row = []
with open(data_dir[i][j][k], "rb") as csvfile:
csv_reader = csv.reader(csvfile)
# fields = csv_reader.next()
# print ("\nField names are:" + ','.join(field for field in fields))
for row in csv_reader:
rows.append(row)
for row in rows[1:]:
if i == 0:
if float(
exp.get_dist([0, 0], [
float(row[15:16][0]),
float(row[16:17][0])
])) / float(
exp.get_dist([0, 0], [
float(row[11:12][0]),
float(row[12:13][0])
])) >= float(1) / float(3):
input_row.append(row[1:2][0])
input_row.append(row[3:4][0])
input_row.append(row[5:6][0])
input_row.append(row[6:7][0])
cursor_deviation = degrees(
exp.cart2pol([
float(row[15:16][0]),
float(row[16:17][0])
])[1]) - float(row[6:7][0])
input_row.append(cursor_deviation)
break
if i > 0:
if float(
exp.get_dist([0, 0], [
float(row[15:16][0]),
float(row[16:17][0])
])) / float(
exp.get_dist([0, 0], [
float(row[11:12][0]),
float(row[12:13][0])
])) >= float(1) / float(3):
cursor_deviation = degrees(
exp.cart2pol([
float(row[15:16][0]),
float(row[16:17][0])
])[1]) - float(row[6:7][0])
output_rows[pc].append(cursor_deviation)
pc = pc + 1
break
if i == 0:
output_rows.append(input_row)
return [output_fields, output_rows]
def data_process(participant_list=[], data_dir=[], cfg={}):
output_fields = ['task', 'trial', 'rotation_angle_deg', 'target_angle_deg']
output_rows = []
for i in range(0, len(data_dir)): # does this loop over participants?
output_fields.append(participant_list[i]) # seems like it does
pc = 0
for j in range(0, len(data_dir[i])
): # does this loop over files in the data directory?
for k in range(0, len(data_dir[i][j])):
# fields = []
rows = []
input_row = []
with open(data_dir[i][j][k], "rb") as csvfile:
csv_reader = csv.reader(
csvfile
) # why not read in the COMPLETE file as a pandas data frame?
# fields = csv_reader.next()
# print ("\nField names are:" + ','.join(field for field in fields))
for row in csv_reader:
rows.append(row)
for row in rows[1:]:
if i == 0:
if float(
exp.get_dist([0, 0], [
float(row[15:16][0]),
float(row[16:17][0])
])
) / float(
exp.get_dist([0, 0], [
float(row[11:12][0]),
float(row[12:13][0])
])
) >= float(
1
) / float(
3
): # why use column indices instead of column names? names are more robust to future situations where we add or re-order columns
input_row.append(row[1:2][0]) # task?
input_row.append(row[3:4][0]) # trial?
input_row.append(
row[5:6][0]) # rotation_angle_deg?
input_row.append(row[6:7][0]) # target_angle_deg?
cursor_deviation = degrees(
exp.cart2pol([
float(row[15:16][0]),
float(row[16:17][0])
])[1]) - float(row[6:7][0])
input_row.append(cursor_deviation)
break
if i > 0:
if float(
exp.get_dist([0, 0], [
float(row[15:16][0]),
float(row[16:17][0])
])) / float(
exp.get_dist([0, 0], [
float(row[11:12][0]),
float(row[12:13][0])
])) >= float(1) / float(3):
cursor_deviation = degrees(
exp.cart2pol([
float(row[15:16][0]),
float(row[16:17][0])
])[1]) - float(row[6:7][0])
output_rows[pc].append(cursor_deviation)
pc = pc + 1
break
if i == 0:
output_rows.append(input_row)
return [output_fields, output_rows
] # why not return a data frame where this is integrated?
