import numpy as np
import matplotlib.pyplot as pl
import pandas as pd


from style import  *
from helper import *

import os
from scipy.optimize import curve_fit

path_data_repo = "../data_supplementary"

fig, ax = pl.subplots(nrows=1, ncols=2, figsize = (3.5 * 1.61,3),dpi = 300)
axs = ax.flatten()


data = pd.read_csv(join(path_data_repo, f"Sim_DC_shapiro_curve.csv"))

vel = data["velocity"]  # in mm/s
mu = data["mu"] # in Hz


ax[0].errorbar(vel, mu, **get_style(RPTU_COLORS['petrol']), label=r"$x_\mathrm{m}=0$")
ax[0].set_xlabel(f"Velocity [mm/s]")
ax[0].set_ylabel(fr"$\Delta \mu$/$h$ [Hz]")
ax[0].legend()

#############################

freq_list=["60","90","120"]
colorlist = [RPTU_COLORS['himbeere'],RPTU_COLORS["mango"],RPTU_COLORS["nacht"]]


for i,f in enumerate(freq_list):

    data = pd.read_csv(join(path_data_repo, f"Sim_AC_shapiro_curve_f_{f}Hz.csv"))

    # data = np.asarray(data)
    # print(data.shape)
    # df = pd.DataFrame(data, columns=["current",
    #                                  "mu"])  # time in ms , barrier _pos in barrier position in lattice discretization length
    # df.to_csv(join(path_data_repo, f"Sim_AC_shapiro_curve_f_{f}Hz.csv"))

    current = data["current"]  # in mm/s
    mu = data["mu"]  # in Hz

    ax[1].errorbar(current, mu, **get_style(colorlist[i],ls="--"), label = fr"{f} Hz")

ax[1].set_xlabel(r"$I/I_\mathrm{c}$")
ax[1].set_ylabel(fr"$\Delta \mu$/$h$ [Hz]")
ax[1].legend()
pl.tight_layout()

pl.show()