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Commit 01bc68fd authored by Felix Reichel's avatar Felix Reichel :beers:
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Add new fit functions to the shape analysis

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figure_plots/20220218_new_shape_analysis_test.ipynb
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%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import os import os
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import seaborn as sns import seaborn as sns
from scipy.optimize import curve_fit from scipy.optimize import curve_fit
import warnings import warnings
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')
``` ```
%% Cell type:code id: tags:
``` python
# folder to save all panels for figure 2
# savefolder = r"plots\fig2"
# file containing the data for the controls
results_ctrl_file = r"data\shape_analysis\histograms_HealthyControl_deformed_undeformed.txt"
```
%% Cell type:code id: tags:
``` python
def logistic_growth(x, A, x_0, k):
'''The logistic growth fct'''
return A/(1+np.exp(-k*(x-x_0)))
def logistic_growth_simple(x, x_0, k):
'''A simplified logistic growth fct'''
return 1/(1+np.exp(-k*(x-x_0)))
def hyperbola(x, a):
'''Hyperbolic function with growth rate a and limit 1 with
root at f(0)=0: f(x) = a/(x-a) + 1
'''
return a/(x-a) + 1
def exponential_inverted(x, a):
return 1 - np.exp(-a*x)
```
%% Cell type:code id: tags:
``` python
results_ctrl = np.loadtxt(results_ctrl_file)
v_min = 0.
v_max = 3.
v_ctrl = results_ctrl[:,0]
probs_ctrl = results_ctrl[:,3]
probs_ctrl_err = results_ctrl[:,4]
# fit_bounds=(0, [1, np.inf, np.inf])
ind_vmax = v_ctrl <= v_max
v_ctrl = v_ctrl[ind_vmax]
probs_ctrl = probs_ctrl[ind_vmax]
probs_ctrl_err = probs_ctrl_err[ind_vmax]
popt_ctrl, pcov_ctrl = curve_fit(logistic_growth_simple, v_ctrl, probs_ctrl,
sigma = probs_ctrl_err, absolute_sigma=False,
# bounds = fit_bounds
)
popt_ctrl_exp, pcov_ctrl_exp = curve_fit(exponential_inverted, v_ctrl, probs_ctrl,
sigma = probs_ctrl_err, absolute_sigma=False,
# p0=-15,
# bounds = fit_bounds
)
v_plot = np.linspace(v_min, v_max, 100)
with sns.axes_style("darkgrid"):
plt.figure(0,(5,3.5))
plt.errorbar(v_ctrl, probs_ctrl, probs_ctrl_err, color='k', marker='.', alpha=.5, label='CTRL', lw=2, zorder=1)
plt.plot(v_plot, logistic_growth_simple(v_plot, *popt_ctrl), 'r-', alpha=1, lw=2, zorder=100)
plt.plot(v_plot, exponential_inverted(v_plot, *popt_ctrl_exp), c='C0', alpha=1, lw=2, zorder=100)
plt.axhline(1, c='C0', ls='--', lw=1.5)
plt.vlines(0.5, -0.1, 0.5, ls='--', color='orange', lw=1.5)
plt.xlim(0,3)
plt.ylim(0,1.05)
plt.xlabel("Cell velocity [mm/s]")
plt.ylabel("Probability")
plt.title("Probability for deformed cell", fontsize=12)
plt.legend(loc='lower right')
plt.tight_layout()
# savename = "fig2A_explain_LogGrowth_FitValues"
# savepath = os.path.join(savefolder,savename)
# plt.savefig(savepath+".pdf", dpi=900, format='pdf')
```
%% Output
%% Cell type:code id: tags:
``` python
popt_ctrl_exp
```
%% Output
array([2.03423702])
%% Cell type:code id: tags:
``` python
```
......
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