def filter_rupture(fitfile, meas_pars, test=False):
m = meas_pars
# laptop or work PC
folder = "C:\\Users\\tbrouwer\\Desktop\\Data\\"
bool = os.path.isdir(folder)
if bool == False:
folder = "C:\\Users\\brouw\\Desktop\\Data\\"
# open data
file_location = folder + str(fitfile[:6]) + "\\"
file_name = str(fitfile[7:15]) + ".dat"
bead = fitfile[16:-4]
# read logfile
log_name = str(fitfile[7:15]) + ".log"
f = open(file_location + log_name, 'r')
log = f.readlines()[:]
f.close()
m['beads'] = func.get_num(log[9])
framerate = func.get_num(log[5])
# because of this annoying bug in the LabVIEW program, offset bead no. by 2
bead = int(bead)
# bead = str(bead + 2)
bead = str(bead)
# title
title = fitfile[:-4]
# read DataFrame
df = pd.read_csv(file_location + file_name, sep="\t")
time = np.array(df['Time (s)'])
amplitude = np.array(df['Amp' + str(bead) + ' (a.u.)'])
X = np.array(df['X' + str(bead) + ' (um)'])
Y = np.array(df['Y' + str(bead) + ' (um)'])
Z = np.array(df['Z' + str(bead) + ' (um)'])
m['X0_um'] = np.mean(X[np.logical_not(np.isnan(X))])
m['Y0_um'] = np.mean(Y[np.logical_not(np.isnan(Y))])
m['Z0_um'] = np.mean(Z[np.logical_not(np.isnan(Z))])
m['amp'] = np.mean(amplitude[np.logical_not(np.isnan(amplitude))])
m['points_exp'] = int(time[-1]*framerate)
# does the tether rupture?
rupt, peak_index, mask = func.rupture(time, amplitude, mask=True)
if rupt:
magnet = np.array(df['Stepper shift (mm)'])
force = func.calc_force(magnet)
f_rupt = force[peak_index]
m['f_rupt_pN'] = f_rupt
if test:
return rupt, mask, Z
else:
return rupt, mask
def open_data(n, measurements, data_path):
# open data
sub = measurements[n]
file_location = data_path + str(sub[0]) + "\\"
file_name = "data_" + str(sub[1])
file_extension = ".dat"
file_all = file_location + file_name + file_extension
# title - extract date of the measurements
title = int(func.get_num(file_location))
# headers
f = open(file_all, 'r')
headers_lines = f.readlines()[0]
f.close()
headers = headers_lines.split('\t')
# data
f = open(file_all, 'r')
data_lines = f.readlines()[1:]
f.close()
# number of beads
file_name = "data_" + str(sub[1])
file_extension = ".log"
file_all = file_location + file_name + file_extension
# find "number of beads" column
f = open(file_all, 'r')
beads = f.readlines()[9]
f.close()
beads = int(func.get_num(beads))
# calculate force from magnet position
magnet = []
time = []
force = []
for n, x in enumerate(data_lines):
magnet.append(float(x.split()[headers.index('Stepper shift (mm)')]))
time.append(float(x.split()[headers.index('Time (s)')]))
magnet = np.array(magnet)
for i in magnet:
force.append(func.calc_force(i))
# calculating the first derivative of magnet to discriminate in pull/release-curve
dx = np.diff(time)
dy = np.diff(magnet)
diff_magnet = np.array(np.divide(dy, dx))
return time, force, beads, diff_magnet, headers, data_lines, title, file_name
def read_analyze_DNA(measurement, pars):
# import parameters
try:
p = pars
except:
print('Error: no parameters')
return
# constants from Parameters
L_bp = p['L_bp'] # contour length (bp)
S_pN = p['S_pN'] # stretch modulus (pN)
P_nm = p['P_nm'] # persistence length (nm)
# working on laptop or work PC?
folder = "C:\\Users\\tbrouwer\\Desktop\\Data\\"
bool = os.path.isdir(folder)
if bool == False:
folder = "C:\\Users\\brouw\\Desktop\\Data\\"
# open data
sub = measurement
file_location = folder + str(sub[0]) + "\\"
file_name = "data_" + str(sub[1])
file_extension = ".dat"
file_all = file_location + file_name + file_extension
bead = int(sub[2])
# title
title = int(func.get_num(file_location))
# read DataFrame
df = pd.read_csv(file_all, sep="\t")
magnet = np.array(df['Stepper shift (mm)'])
time = np.array(df['Time (s)'])
force = func.calc_force(magnet)
Z = np.array(df['Z' + str(bead) + ' (um)'])
# number of beads
file_log = file_location + file_name + ".log"
f = open(file_log, 'r')
beads = f.readlines()[9]
f.close()
beads = int(func.get_num(beads))
drift = []
for i in range(beads):
z_drift = np.array(df['Z' + str(i) + ' (um)'])
amplitude_drift = np.array(df['Amp' + str(i) + ' (a.u.)'])
# does the tether rupture?
rupt = rupture(time, amplitude_drift)
if rupt == False:
drift.append(func.drift_self(z_drift, time))
drift_med = float(np.median(drift))
Z = Z - (drift_med / 1000) * time
# calculating the first derivative of magnet
dx = np.diff(time)
dy = np.diff(magnet)
diff_magnet = np.append([0], np.divide(dy,
dx)) # add a zero as first element
# split in pull & release
factor = max(diff_magnet / 1000)
# f_pull = force[diff_magnet > factor]
# f_release = force[diff_magnet < factor]
# z_pull = Z[diff_magnet > factor]
# z_release = Z[diff_magnet < factor]
# 1st pull
# f_pull = force[np.where((diff_magnet > factor) & (time < 25))]
# f_release = force[np.where((diff_magnet < factor) & (time < 25))]
# z_pull = Z[np.where((diff_magnet > factor) & (time < 25))]
# z_release = Z[np.where((diff_magnet < factor) & (time < 25))]
# 2nd pull
f_pull = force[np.where((diff_magnet > factor) & (time > 25))]
f_release = force[np.where((diff_magnet < factor) & (time > 25))]
z_pull = Z[np.where((diff_magnet > factor) & (time > 25))]
z_release = Z[np.where((diff_magnet < factor) & (time > 25))]
# select high-force data
select_f = f_pull[np.where((f_pull > 14) & (f_pull < 16))]
select_z = z_pull[np.where((f_pull > 14) & (f_pull < 16))]
# fit the WLC in fashion (x,y) - only fit offset, fix everything else
popt, pcov = curve_fit(
lambda f, z0: func.WLC_fit(f, P_nm, L_bp * 0.34, S_pN, z0),
select_f,
select_z,
p0=1)
z_fit = popt[0]
# subtract fitted offset from data
z_pull -= z_fit
z_release -= z_fit
select_z -= z_fit
title = str(title) + '_' + str(sub[1]) + '_' + str(sub[2]) + '_' + str(
sub[3])
return f_pull, z_pull, f_release, z_release, title
def read_analyze(measurement, pars, data_path):
try:
p = pars
except:
print('Error: no parameters')
return
global_drift = True
# constants from parameters
L_bp = p['L_bp'] # contour length (bp)
S_pN = p['S_pN'] # stretch modulus (pN)
P_nm = p['P_nm'] # persistence length (nm)
# open data
file_location = data_path
file_name = "data_" + str(measurement[1])
file_extension = ".dat"
file_all = file_location + file_name + file_extension
bead = int(measurement[2])
# title
title = int(func.get_num(file_location))
# read DataFrame
df = pd.read_csv(file_all, sep="\t")
magnet = np.array(df['Stepper shift (mm)'])
time = np.array(df['Time (s)'])
force = func.calc_force(magnet)
Z = np.array(df['Z' + str(bead) + ' (um)'])
# number of beads
file_log = file_location + file_name + ".log"
f = open(file_log, 'r')
try:
beads = f.readlines()[9]
except:
headers = list(df)
# get number of beads
beads = headers[len(headers) - 1]
f.close()
try:
beads = int(func.get_num(beads))
except:
beads = func.get_int(beads)
drift = []
for i in range(beads):
z_drift = np.array(df['Z' + str(i) + ' (um)'])
try:
amplitude_drift = np.array(df['Amp' + str(i) + ' (a.u.)'])
except:
amplitude_drift = np.array(df['Amp a.u.'])
# does the tether rupture?
rupt, _ = func.rupture(time, amplitude_drift)
if rupt == False:
drift.append(func.drift_self(z_drift, time))
if not drift:
p['drift'] = 'uncorrected'
drift_med = 0
else:
drift_med = float(np.median(drift))
Z = Z - (drift_med / 1000) * time
p['drift'] = str(round(drift_med, 3)) + " nm/s (global drift)"
# calculating the first derivative of magnet
dx = np.diff(time)
dy = np.diff(magnet)
diff_magnet = np.append([0], np.divide(dy, dx)) # add a zero as first element
# split in pull & release
factor = max(diff_magnet / 1000)
time_pull = time[diff_magnet < factor]
f_pull = force[diff_magnet < factor]
f_release = force[diff_magnet > factor]
z_pull = Z[diff_magnet < factor]
z_release = Z[diff_magnet > factor]
# select high-force data
select_f = f_pull[np.where((f_pull > 50) & (f_pull < 55) & (time_pull > 60) & (time_pull < 140))]
select_z = z_pull[np.where((f_pull > 50) & (f_pull < 55) & (time_pull > 60) & (time_pull < 140))]
if select_f.size != 0:
# fit the WLC in fashion (x,y) - only fit offset, fix everything else
popt, pcov = curve_fit(lambda f, z0: func.WLC_fit(f, P_nm, L_bp * 0.34, S_pN, z0), select_f, select_z, p0=1)
z_fit = popt[0]
# subtract fitted offset from data
z_pull -= z_fit
z_release -= z_fit
select_z -= z_fit
else:
z_fit = 0
title = str(title) + '_' + str(measurement[1]) + '_' + str(measurement[2]) + '_' + str(measurement[3])
return f_pull, z_pull, f_release, z_release, title, drift_med, z_fit
for file in fitfiles:
# read DataFrame
df = pd.read_csv(folder + file, sep="\t")
force = np.array(df['F (pN)'])
time = np.array(df['t (s)'])
A = 59.5
C = 0.01
L = 1.4
magnet = -np.log(force / A - C / A) * L
recalc_force = func.calc_force(magnet)
df['F (pN)'] = recalc_force
df.to_csv(recalc_folder + file[:-4] + "_rec.fit", sep='\t')
# rename logfiles + save
logfiles = []
os.chdir(folder)
for file in glob.glob("*.log"):
logfiles.append(file)
for file in logfiles:
old_name = folder + file