], [ 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)