],
[
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\august_2020\2020_08_21_alginate2%_NIH_xposition_1\inlet\inlet_2\*_result.txt",
],
[
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\august_2020\2020_08_21_alginate2%_NIH_xposition_1\inlet\inlet_3\*_result.txt",
],
]
pos = "inlet"
axes = []
for j in range(3):
data_list = []
config_list = []
for pressure in [1, 2, 3]:
data1, config1 = load_all_data(files[j], pressure=pressure)
data_list.append(data1)
config_list.append(config1)
data = pd.concat(data_list)
config = config_list[0]
p = fitStiffness(data, config)
if 0:
fits = get_bootstrap_fit(data, config, 100)
np.save(__file__[:-3] + f"_fits{j}.npy", fits)
else:
fits = np.load(__file__[:-3] + f"_fits{j}.npy")
print("fits", fits.shape)
p2 = np.std(fits, axis=0)
for i in config_list:
import numpy as np
from scipy import stats
import pylustrator
pylustrator.start()
numbers = []
for row, name in enumerate(["inlet", "middle", "outlet"]):
for index, pressure in enumerate([1, 2, 3]):
ax = plt.subplot(3, 3, 3 * row + index + 1)
#data, config = load_all_data(r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data" +
# r"\microscope4\2020_july\2020_07_21_alginate2%_dmem_NIH_time_2\[0-9]\*_result.txt", pressure=pressure)
data, config = load_all_data([
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\{name}\[0-9]\*_result.txt",
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\{name}\[0-9]\*_result.txt",
],
pressure=pressure)
x, y = np.array(data.stress), np.array(np.abs(data.angle))
plotDensityScatter(x, y)
plotBinnedData(x, y, np.arange(0, 300, 50))
numbers.append(len(data.rp))
print("numbers", numbers)
#plt.legend()
#% start: automatic generated code from pylustrator
plt.figure(1).ax_dict = {ax.get_label(): ax for ax in plt.figure(1).axes}
import matplotlib as mpl
import tqdm
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from scipy.stats import gaussian_kde
import glob
import pylustrator
pylustrator.start()
data1, config1 = load_all_data([
# r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_13_alginate2%_sync_k562_diff_xpositions\end_[0-9]series\*_result.txt"
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\inlet\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\[0-9]\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_10_alginate2%_K562_0%FCS_time\2\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\07_07_2020_alginate2%_K562_0%FCS_time\2\*_result.txt",
# r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_may\2020_05_22_alginateDMEM2%\[0-9]\*_result.txt",
], pressure=1)
data2, config2 = load_all_data([
# r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_13_alginate2%_sync_k562_diff_xpositions\end_[0-9]series\*_result.txt"
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\inlet\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\[0-9]\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_10_alginate2%_K562_0%FCS_time\2\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\07_07_2020_alginate2%_K562_0%FCS_time\2\*_result.txt",
import numpy as np
from scipy import stats
import pylustrator
pylustrator.start()
if 1:
numbers = []
for index, pressure in enumerate([0.5, 1, 1.5]):
ax = plt.subplot(1, 3, index+1)
#data, config = load_all_data(r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data" +
# r"\microscope4\2020_july\2020_07_21_alginate2%_dmem_NIH_time_2\[0-9]\*_result.txt", pressure=pressure)
data, config = load_all_data([
rf"\\131.188.117.96\biophysDS\meroles\2020.05.27_THP1_RPMI_2pc_Ag\THP1_27_05_2020_2replicate\*\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_10_alginate2%_K562_0%FCS_time\*\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\07_07_2020_alginate2%_K562_0%FCS_time\*\*_result.txt",
], pressure=pressure)
plotDensityScatter(data.rp, data.area)
plotBinnedData(data.rp, data.area, [0, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250])
#plt.hist(data.area, bins=100, density=True, alpha=0.8)
numbers.append(len(data.rp))
#kde = stats.gaussian_kde(np.hstack((data.rp, -data.rp)))
#xx = np.linspace(-110, 110, 1000)
#plt.plot(xx, kde(xx), "--k", lw=0.8)
print("numbers", numbers)
all_plots_same_limits()
# and fits a stress stiffening equation to the data
# The results such as maximum flow speed, cell mechanical parameters, etc. are stored in
# the file 'all_data.txt' located at the same directory as this script
"""
from scripts.helper_functions import load_all_data, fitStiffness
from scripts.helper_functions import plotStressStrain, plotStressStrainFit
import numpy as np
import matplotlib.pyplot as plt
import pylustrator
pylustrator.start()
data3, config3 = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_30_alginate2%_NIH3T3_blebbistatin\inlet\[0-9]\*_result.txt"
], pressure=3)
data3b, config3b = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_30_alginate2%_NIH3T3_DMSO\inlet\[0-9]\*_result.txt",
], pressure=3)
fitStiffness(data3, config3)
fitStiffness(data3b, config3b)
plt.subplot(121)
plotStressStrain(data3b, config3b)
plotStressStrainFit(data3b, config3b)
plt.title("DMSO")
plt.text(0.5, 0.5, f"k = {config3b['fit']['p'][0]:3.0f} Pa\n$\\alpha$ = {config3b['fit']['p'][1]:2.2f}")
""" THP1 """
fit_data = []
pressures = np.sort(np.unique(get_pressures(rf"\\131.188.117.96\biophysDS\meroles\2020.05.27_THP1_RPMI_2pc_Ag\THP1_27_05_2020_2replicate\2\*_result.txt")))
pressures = pressures[2:]
# iterate over all times
for index, pressure in enumerate(pressures):
f = []
time = 2
# iterate over the different experiment paths
for path in [
rf"\\131.188.117.96\biophysDS\meroles\2020.05.27_THP1_RPMI_2pc_Ag\THP1_27_05_2020_2replicate\2\*_result.txt",
]:
# get the data and the fit parameters
data, config = load_all_data(path, pressure=pressure)
f.append([config["fit"]["p"][0], config["fit"]["p"][1], config["fit"]["p"][0] * config["fit"]["p"][1]])
fit_data.append(f)
fit_data = np.array(fit_data)
# plot the fit data in the three different plots
for i in range(3):
plt.subplot(1, 3, i+1)
print("i", np.mean(fit_data[:, :, i], axis=1))
plt.errorbar(pressures, np.mean(fit_data[:, :, i], axis=1),
np.std(fit_data[:, :, i], axis=1) / np.sqrt(fit_data[:, :, i].shape[1]), capsize=3,
label="THP1",
)
import numpy as np
from scipy import stats
import pylustrator
pylustrator.start()
if 1:
numbers = []
for index, pressure in enumerate([1, 2, 3]):
ax = plt.subplot(1, 3, index + 1)
#data, config = load_all_data(r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data" +
# r"\microscope4\2020_july\2020_07_21_alginate2%_dmem_NIH_time_2\[0-9]\*_result.txt", pressure=pressure)
data, config = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_21_alginate2%_dmem_NIH_time_2\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_may\2020_05_22_alginateDMEM2%\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_27_alginate2%_dmem_NIH_time_1\[0-9]\*_result.txt",
],
pressure=pressure)
plt.hist(data.rp,
bins=np.linspace(-100, 100, 20),
density=True,
alpha=0.8)
numbers.append(len(data.rp))
kde = stats.gaussian_kde(np.hstack((data.rp, -data.rp)))
xx = np.linspace(-110, 110, 1000)
plt.plot(xx, kde(xx), "--k", lw=0.8)
print("numbers", numbers)
from scripts.helper_functions import storeEvaluationResults, load_all_data
import numpy as np
import tqdm
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from scipy.stats import gaussian_kde
import glob
import pylustrator
pylustrator.start()
data1, config1 = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\inlet\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\[0-9]\*_result.txt",
],
pressure=1)
data2, config2 = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\inlet\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\[0-9]\*_result.txt",
],
pressure=2)
data3, config3 = load_all_data([
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_2\inlet\[0-9]\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\[0-9]\*_result.txt",
],
pressure=3)
