#! /Usr/bin/python3

import scipy.optimize as opt
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import VisTools.plotting as vt

plt.ioff()
plt.style.use('bmh')
fig, axarr = plt.subplots(2,1,figsize=(11.88, 8.4))
data = pd.read_csv("./" + __file__[:-3].split("_")[1] + ".csv", comment="#")

fits = np.array([])
errs = np.array([])
colors = np.array([])

data['Dv'] = data['v_pit48/v'] - data['v_set/v']
data['Dvk'] = data['v_keith/v'] - data['v_set/v']
print(data)
# fit to abs dist
linfnc = lambda x,m,c: x*m+c

p = axarr[0].errorbar(
    data[data.cycles == 0]['v_set/v'],
    data[data.cycles == 0]['Dvk'],
    label="relative Error of ADC, keith",
    fmt='.'
)

pfinal, pcov = opt.curve_fit(
    linfnc,
    data[data.cycles == 0]['v_set/v'],
    data[data.cycles == 0]['Dvk'],
    p0=(.1,2.6),
    sigma=[.5 for e in range(data[data.cycles == 0]['Dv'].size)]
)

axarr[0].plot(
    data[data.cycles == 0]['v_set/v'],
    data[data.cycles == 0]['v_set/v']*pfinal[0]+pfinal[1],
    label="fitted, keith",
    color = p[0].get_color()
)
for i in range(8):
    p = axarr[0].errorbar(
        data[data.cycles == i]['v_set/v'],
        data[data.cycles == i]['Dv'],
        yerr=data[data.cycles == i]['dv_pit48/v'],
        label="relative Error of ADC, scaler: "+str(i),
        fmt='.'
    )

    pfinal, pcov = opt.curve_fit(
        linfnc,
        data[data.cycles == i]['v_set/v'],
        data[data.cycles == i]['Dv'],
        p0=(.1,2.6),
        sigma=[.5 for e in range(data[data.cycles == i]['Dv'].size)]
    )

    axarr[0].plot(
        data[data.cycles == i]['v_set/v'],
        data[data.cycles == i]['v_set/v']*pfinal[0]+pfinal[1],
        label="fitted, scaler: "+str(i),
        color = p[0].get_color()
    )

    fits = np.append(fits, pfinal[0])
    errs = np.append(errs, np.sqrt(pcov[0][0]))
    colors = np.append(colors, p[0].get_color() )

#vt.annotate_val(plt, pfinal[0], np.sqrt(pcov[0][0]), name="V48[2]", data_pos=(44, 3))

print(fits)
for i in range(8):
    axarr[1].errorbar(
        i,
        fits[i],
        yerr = errs[i],
        fmt='.',
        c = colors[i]
    )

axarr[0].set_xlabel('V$_{set}$/V')
axarr[0].set_title("PowerIt ADC Calibration: dependency on measurement cycles")
axarr[0].set_ylabel('$\Delta$V$_{IN}$ / V')

axarr[1].set_xlabel('sampleTicks scaler')
axarr[1].set_ylabel('$\Delta(\Delta$V$_{IN})$')

plt.tight_layout()
plt.savefig("./" + __file__[:-3].split("_")[1] + ".eps", format='eps', dpi=1000)