def file_check(filename):
filebase = filename
filename = filebase + ".txt."
#read in the first line.
with open(filename, 'r') as f:
line1 = f.readline().strip()
new_format = False
old_format = False
#"name" is characteristic of the new format.
if "Name" in line1:
new_format = True
old_format = False
elif "Name" not in line1:
new_format = False
old_format = True
if old_format == True:
nanonightly.convert_to_new(filename)
filename = filebase + "_KSV_NIMA_Format.txt"
skip = 1
return old_format, new_format
filename = filebase +".txt."
with open(filename, 'r') as f:
line1 = f.readline().strip()
new_format = False
old_format = False
if "Name" in line1:
new_format = True
old_format = False
elif "Name" not in line1:
new_format = False
old_format = True
if old_format == True:
nanonightly.convert_to_new(filename)
filename = filebase + "_KSV_NIMA_Format.txt"
skip = 1
# We then use this to do our data analysis.
t, Bpos, Bspd, A, Mma, P1, P2 = nanonightly.loadtxt(filename, unpack = True, usecols = [0,1,2,3,4,5,6], skiprows=44)
t_smooth, A_smooth = nanonightly.smooth_data(t, A, new_array_len = len(t), window_size = size, poly_order = order)
t_smooth, P1_smooth = nanonightly.smooth_data(t, P1, new_array_len = len(t), window_size = size, poly_order = order)
t_smooth, P2_smooth = nanonightly.smooth_data(t, P2, new_array_len = len(t), window_size = size, poly_order = order)
t_smooth, Bpos_smooth = nanonightly.smooth_data(t, Bpos, new_array_len = len(t), window_size = size, poly_order = order)
t_smooth, Bspd_smooth = nanonightly.smooth_data(t, Bspd, new_array_len = len(t), window_size = size, poly_order = order)
t_smooth, Mma_smooth = nanonightly.smooth_data(t, Mma, new_array_len = len(t), window_size = size, poly_order = order)
#t, Bpos, Bspd, A, Mma, P1, P2 = loadtxt(filename, unpack = True, usecols = [0,1,2,3,4,5,6], skiprows=44)
