#!/usr/bin/env python

from time import sleep
from collections import deque
import numpy as np
from zoetrope import aniplot as plt
from scipy.stats.stats import pearsonr
from bstrd import BS, bsstream
plt.blit = False
plt.style.use('ggplot')

wav = np.linspace(409.914, 672.792, num=2048)

def unpumpedshots(pulseids, *arrays):
    unpumped_shots = (pulseids%2 == 0)
    return [a[unpumped_shots] for a in arrays]


def pumpedshots(pulseids, *arrays):
    pumped_shots = (pulseids%2 == 1)
    return [a[pumped_shots] for a in arrays]

chname_specsig = "SARES11-SPEC125-M2.projection_signal"
chname_specback = "SARES11-SPEC125-M2.projection_background"
chname_i0 = "SLAAR11-LSCP1-FNS:CH5:VAL_GET"
#chname_events = "SAR-CVME-TIFALL4:EvtSet"
chname_pids = "SATCB01-RLLE-STA:MASTER-EVRPULSEID"

# create channel
ch_spec1  = BS(chname_specsig)
ch_back1 = BS(chname_specback)
ch_i0 = BS(chname_i0)
ch_pids = BS(chname_pids)

n = 200
sigs1 = np.empty((n, 2048))
backs1 = np.empty((n, 2048))
i0s = np.empty(n)
pids = np.empty(n)

# create the empty plot
pd = plt.plot([0])

# some plot settings
plt.fig.set_figheight(6)
plt.fig.set_figwidth(7)

for counter, data in zip(plt.show(), bsstream):
    print(counter)

    for i in range(n):
        sigs1[i] = ch_spec1.get()
        backs1[i] = ch_back1.get()
        i0s[i] = ch_i0.get()
        pids[i] = int(ch_pids.get())
        next(bsstream) # this gets the next set of data

    pumpi0s, pumpsigs, pumpbacks = pumpedshots(pids, i0s, sigs1, backs1)
    unpumpi0s, unpumpsigs, unpumpbacks = unpumpedshots(pids, i0s, sigs1, backs1)

    diffa = np.mean((pumpsigs - pumpbacks), axis=0) / np.mean((unpumpsigs - unpumpbacks), axis=0)

    plt.tight_layout()
    plt.clf()
    plt.xlim(450, 650)
    plt.ylim(-0.05, 0.05)
    plt.plot(wav, -np.log10(diffa))
    plt.show()
    
bsstream.close()