def getXY(pressure):
data, config = load_all_data(
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_16_alginate2%_NIH_tanktreading\1\*_result.txt",
pressure=pressure)
x = np.abs(data.rp) * 1e-6
y = data.velocity * 1e-3
return removeNan(x, y)
def getXY(pressure):
data, config = load_all_data([
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_16_alginate2%_NIH_tanktreading\1\*_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\1\*_result.txt",
], pressure=pressure)
x, y = data.rp*1e-6, data.velocity*1e-3
i = ~np.isnan(x) & ~np.isnan(y)
x = x[i]
y = y[i]
return x, y, data
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from deformationcytometer.evaluation.helper_functions import plotDensityScatter, load_all_data
import numpy as np
import pylustrator
pylustrator.start()
for index, pressure in enumerate([1]):
ax = plt.subplot(1, 3, index + 1)
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.subplot(1, 2, 1)
plotDensityScatter(data.rp, data.angle)
plt.subplot(1, 2, 2)
plotDensityScatter(data.rp, np.sqrt(data.area / np.pi))
#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
plt.figure(1).set_size_inches(12.000000 / 2.54, 4.370000 / 2.54, forward=True)
plt.figure(1).axes[0].set_position([0.118367, 0.241321, 0.356764, 0.716233])
plt.figure(1).axes[0].set_xlim(-90.0, 90.0)
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from deformationcytometer.evaluation.helper_functions import load_all_data, plotDensityScatter, plotBinnedData
import numpy as np
from scipy import stats
import pylustrator
pylustrator.start()
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\inlet\[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\inlet\[0-9]\*_result.txt",
],
pressure=3)
def curve(x, x0, a):
return 1 / 2 * 1 / (1 + (x / x0)**a)
omega_weissenberg = curve(np.abs(data.vel_grad),
(1 / data.tau) * 3, data.delta) * np.abs(
data.vel_grad) # * np.pi*2
plt.plot(data.omega, omega_weissenberg, "o")
plt.savefig(__file__[:-3] + ".png", dpi=300)
plt.savefig(__file__[:-3] + ".pdf")
plt.show()
"""
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from deformationcytometer.includes.includes import getInputFile, getConfig, getData
#refetchTimestamps,
from deformationcytometer.evaluation.helper_functions import getVelocity, filterCells, correctCenter, getStressStrain, fitStiffness
from deformationcytometer.evaluation.helper_functions import initPlotSettings, plotVelocityProfile, plotStressStrain, plotMessurementStatus
from deformationcytometer.evaluation.helper_functions import storeEvaluationResults
from deformationcytometer.evaluation.helper_functions import load_all_data
""" loading data """
# get the results file (by config parameter or user input dialog)
datafile = getInputFile(filetype=[("txt file", '*_result.txt')])
# load the data and the config
data, config = load_all_data(datafile)
fitStiffness(data, config)
""" plotting data """
initPlotSettings()
# add multipage plotting
pp = PdfPages(datafile[:-11] + '.pdf')
# generate the velocity profile plot
plotVelocityProfile(data, config)
pp.savefig()
plt.cla()
plt.axvline(0.7, linestyle="dashed", lw=0.8, color="k")
plt.xlabel("relative radius")
plt.ylabel("speed (µm/s)")
break
#m, t = getCenterLine(data_x, data_y)
#cr = np.corrcoef(data_y, m * np.array(data_x))
#r2 = np.corrcoef(data_y, m * np.array(data_x))[0, 1] ** 2
#return m, r2
# load the data and the config
data, config = load_all_data(
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_16_alginate2%_NIH_tanktreading\1\*_result.txt"
)
data = data[np.abs(data.velocity - data.velocity_fitted) < 1.5]
plt.subplot(241)
plot_velocity_fit(data)
#plt.legend(title="pressure (bar)")
plt.subplot(242)
plot_velocity_fit_dot(data)
plt.subplot(243)
plot_viscisity(data)
plt.subplot(244)
data, config = load_all_data_new(
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_16_alginate2%_NIH_tanktreading\1\*_result.txt"
config = {"channel_length_m": 5.8e-2, "channel_width_m": 186e-6}
x, y = getFitXY(config, np.mean(pressure), p)
return x, y
def histplot(x):
x = np.array(x)
from scipy import stats
kde = stats.gaussian_kde(x)
xx = np.linspace(np.min(x), np.max(x), 1000)
plt.hist(x, bins=50, density=True)
plt.plot(xx, kde(xx))
if 0:
data, config = load_all_data([
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\september_2020\2020_09_16_alginate2%_NIH_tanktreading\1\*_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\1\*_result.txt",
])
data = data.dropna()
#data0 = data
data2 = data
if 1:
import pandas as pd
data2 = pd.read_csv("../figures/panel3_tanktreading/output_rotation_NIH.csv")
data2["velocity"] = data2.v
data2["long_axis"] = data2.a
data2["short_axis"] = data2.b
data2["angle"] = data2.beta
data = data2
p = apply_velocity_fit(data)
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\evaluation\diff % alginate\2020_10_30_alginate2.0%_dmem_NIH_3T3\*\*_result.txt",
]
alg15 = [
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\evaluation\diff % alginate\2020_07_30_alginate1.5%_dmem_NIH_3T3\*\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\evaluation\diff % alginate\2020_10_14_alginate1.5%_dmem_NIH_3T3\*\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\evaluation\diff % alginate\2020_10_14_alginate1.5%_dmem_NIH_3T3_2\*\*_result.txt",
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\evaluation\diff % alginate\2020_10_28_alginate1.5%_dmem_NIH_3T3\*\*_result.txt",
]
if 0:
plt.subplot(2, 3, 1, label="cells")
# iterate over all times
for index, path in enumerate([THP1, K562, NIH3T3]):
# get the data and the fit parameters
data, config = load_all_data(path, pressure=2)
plot_joint_density(np.log10(data.k_cell), data.alpha_cell, label=["THP1", "K562", "NIH3T3"][index])
plt.xlim(1, 3)
plt.ylim(0, 1)
plt.legend(fontsize=8)
plt.subplot(2, 3, 2, label="pressure")
# iterate over all times
for pressure in [1, 2, 3]:
# get the data and the fit parameters
data, config = load_all_data(NIH3T3, pressure=pressure)
plot_joint_density(np.log10(data.k_cell), data.alpha_cell, color=pylustrator.lab_colormap.LabColormap(["C2", "C3"], 3)(pressure-1), label=f"{pressure} bar")
plt.xlim(1, 3)
)):
folder = Path(folder)
name = str(folder.name)
drugs[name] = str(folder) + "\*\*_result.txt"
N = len(drugs)
cols = int(np.sqrt(N))
rows = int(np.ceil(N / cols))
ax_k = []
ax_a = []
# iterate over all times
for index, name in enumerate(drugs.keys()):
plt.figure(1)
# get the data and the fit parameters
data, config = load_all_data(drugs[name])
print(index, name, len(data), np.sum(~np.isnan(data.k_cell)))
ax_k.append(plt.subplot(rows, cols * 2, index * 2 + 1))
plt.title(name)
plot_density_hist(np.log10(data.k_cell))
stat_k = get_mode_stats(data.k_cell)
plt.xlim(1, 4)
plt.xticks(np.arange(5))
plt.grid()
ax_a.append(plt.subplot(rows, cols * 2, index * 2 + 1 + 1))
plot_density_hist(data.alpha_cell, color="C1")
stat_alpha = get_mode_stats(data.alpha_cell)
rows = int(np.ceil(N / cols))
import matplotlib as mpl
mpl.rc("figure.subplot", top=0.95, hspace=0.35, left=0.2,
right=0.95) # defaults top=0.88, hspace=0.2, left=0.125, right=0.9
mpl.rc("figure", figsize=[3.0, 4.8]) # default 6.4, 4.8
ax_k = []
ax_a = []
ax_Gp1 = []
ax_Gp2 = []
# iterate over all times
for index, name in enumerate(experiment.keys()):
print(experiment[name])
try:
data, config = load_all_data(
experiment[name], pressure=3
) #set pressure to 0.5,1,2,3 or what was measured. for all pressures together, delete ", pressure=x"
except (FileNotFoundError, ValueError):
continue
data = data[~np.isnan(data.tt)]
print(index, name, len(data), np.sum(~np.isnan(data.w_k_cell)),
np.sum(~np.isnan(data.k_cell)))
row_title = ""
if "/" in name:
row_title, name = name.split("/", 1)
row_title += "\n"
if index >= cols:
name = ""
plt.figure(1) #histogram of alpha and k
""" THP1 """
fit_data = []
x = []
# iterate over all times
for index, time in enumerate(range(1, 7, 1)):
f = []
# iterate over the different experiment paths
for path in [
rf"\\131.188.117.96\biophysDS\meroles\2020.07.07.Control.sync\Control2\T{time * 10}\*_result.txt",
rf"\\131.188.117.96\biophysDS\meroles\2020.06.26-Control\Control2\T{time * 10}\*_result.txt",
rf"\\131.188.117.96\biophysDS\meroles\2020.06.26-Control\Control1\T{time * 10}\*_result.txt",
rf"\\131.188.117.96\biophysDS\meroles\2020.07.09_control_sync_hepes\Control3\T{time * 10}\*_result.txt",
]:
# get the data and the fit parameters
data, config = load_all_data(path, repetition=2)
f.append([
config["fit"]["p"][0], config["fit"]["p"][1],
config["fit"]["p"][0] * config["fit"]["p"][1]
])
x.append(time * 10)
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)
plt.errorbar(
x,
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\december_2020\2020_12_14_NIH3T3_drugs\Nocodazole\[2-9]\*_result.txt",
"Paclitaxel":
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\december_2020\2020_12_14_NIH3T3_drugs\Paclitaxel\[2-9]\*_result.txt",
"Y27632":
r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\december_2020\2020_12_14_NIH3T3_drugs\Y27632\[2-9]\*_result.txt",
}
drugs = drugs_jan
ax_k = []
ax_a = []
# iterate over all times
for index, name in enumerate(drugs.keys()):
print(index, name)
# get the data and the fit parameters
data, config = load_all_data(drugs[name], pressure=3)
ax_k.append(plt.subplot(4, 3, index + 1))
def curve(x, x0, a):
return 1 / 2 * 1 / (1 + (x / x0)**a)
omega_weissenberg = curve(np.abs(data.vel_grad),
(1 / data.tau) * 3, data.delta) * np.abs(
data.vel_grad) # * np.pi*2
plt.title(name)
plt.plot(data.omega, omega_weissenberg, "o", ms=1)
plt.xlabel("omega")
plt.ylabel("omega_weissenberg")
# full path of the output file
out_put_file = r"/home/user/Desktop/out.pdf"
# list of base folders to analyze. Each folder must contain subfolders "1", "2" .. for different experiments.
base_folders = [
r"/home/user/Desktop/biophysDS/emirzahossein/microfluidic cell rhemeter data/microscope_1/october_2020/2020_10_14_alginate1.5%_NIH",
#r"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_29_aslginate2%_NIH_diff_x_position_3\inlet\\"
]
base_folders_ = [
os.path.join(b, os.path.join("[0-9]", "*_result.txt"))
for b in base_folders
]
print(base_folders_)
# reading all data, with out splitting for the pressure
data_all, config_all = load_all_data(base_folders_, pressure=None)
# reading the data for each pressure individually. This is needed to later plot stress-strain curves
# for each pressure separately
data1, config1 = load_all_data(base_folders_, pressure=1)
data2, config2 = load_all_data(base_folders_, pressure=2)
data3, config3 = load_all_data(base_folders_, pressure=3)
""" evaluating data"""
# fit with all pressures combined
p = fitStiffness(data_all, config_all)
config1["fit"] = config_all["fit"]
config2["fit"] = config_all["fit"]
config3["fit"] = config_all["fit"]
""" plotting data """
initPlotSettings()
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from deformationcytometer.evaluation.helper_functions import plotDensityScatter, plotStressStrainFit, load_all_data, all_plots_same_limits
import pylustrator
pylustrator.start()
rows = 3
cols = 5
for index, time in enumerate(range(1, 6, 1)):
plt.subplot(rows, cols, index + 1)
data, config = load_all_data(
[
rf"\\131.188.117.96\biophysDS\meroles\2020.07.07.Control.sync\Control2\T{time*10}\*_result.txt",
# rf"\\131.188.117.96\biophysDS\meroles\2020.06.26\Control2\T{time*10}\*_result.txt",
# rf"\\131.188.117.96\biophysDS\meroles\2020.06.26\Control1\T{time*10}\*_result.txt",
# rf"\\131.188.117.96\biophysDS\meroles\2020.07.09_control_sync_hepes\Control3\T{time*10}\*_result.txt",
],
repetition=2)
plotDensityScatter(data.stress, data.strain)
plotStressStrainFit(data, config)
for index, time in enumerate(range(2, 11, 2)):
plt.subplot(rows, cols, cols + index + 1)
data, config = load_all_data(
[
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\2020_07_10_alginate2%_K562_0%FCS_time\{time}\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\2020_july\07_07_2020_alginate2%_rpmi_no_fcs_time\{time}\*_result.txt",
],
repetition=2)
# iterate over all times
#pressures = np.sort(np.unique(get_pressures(rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\october_2020\2020_10_16_alginate2%_THP1_overtime\2\*_result.txt")))
pressures = np.sort(np.unique(get_pressures(rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\Mar THP1\2\*_result.txt")))
pressures = pressures[2:]
print(pressures)
for index, pressure in enumerate(pressures):
f = []
# iterate over the different experiment paths
for path in [
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope_1\october_2020\2020_10_15_alginate2%_THP1_overtime\**\*_result.txt",
rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\Mar THP1\2\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\Mar THP1\Control1\**\*_result.txt",
# rf"\\131.188.117.96\biophysDS\emirzahossein\microfluidic cell rhemeter data\microscope4\Mar THP1\Control2\**\*_result.txt",
]:
# get the data and the fit parameters
data, config = load_all_data(path, pressure=pressure)
f.append([np.mean(data.alpha_cell), np.nanmedian(data.k_cell)])
#f.append([np.mean(data.alpha_cell), np.mean(np.log10(data.k_cell))])
fit_data.append(f)
fit_data = np.array(fit_data)
# plot the fit data in the two different plots
for i in range(2):
plt.subplot(1, 2, i+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",
)
