import numpy as np
import matplotlib.pyplot as plt
import Cluster
import Fit

output_data_path = '/Users/marialauraperez/Desktop/'
input_data_path = '/Volumes/TOSHIBA EXT/XRF_20190723_22C/raw/'
sources = ['CaXRF', 'AgXRF', 'Am241XRF_1']
names_hists = ['Ca XRF', 'Ag XRF', 'Am241']
names = [['Ca', 'Cu'], ['Ag'], ['Sn', 'Gd']]
colors_hists = ['lightcoral', 'yellowgreen', 'dodgerblue']
colors_peaks = [['maroon', 'red'], ['olive'], ['navy', 'blueviolet']]
maximum = 70
numbins = 70
maxrows = 100000


def load_parameter_matrices(suffix, path_to_data):
    # suffix: of the data
    # path_to_data: where txt matrices are
    parameter_matrices = []
    names = ['A', 'B', 'C', 'T']
    for i in range(len(names)):
        if i is 0:
            parameter_matrices.append(Cluster.remove_dead_pixels(np.genfromtxt(
                path_to_data + names[i] + suffix)))
        else:
            parameter_matrices.append(np.genfromtxt(path_to_data + names[i] + suffix))
    return parameter_matrices


def histos_and_peaks(matrices, calibration_type, minargs, maxargs):
    # clusters, may calibrate, gives histograms and returns info of histogram
    # maximum: in histogram
    # maxrows: number of events to import
    # calibration_type: string, non calibrated, test pulse or default
    # if calibrate is false, everything is done with ToT values
    mus = list()
    x1 = np.linspace(0, maximum, 500)
    plt.figure()
    plt.title('Test spectra with Si-TPX3 (' + calibration_type + ')', fontweight='bold')
    for i in range(len(sources)):
        source = sources[i]
        print('Processing '+names_hists[i]+' data...')
        data = np.genfromtxt(input_data_path+source+'.t3pa', skip_header=1, delimiter='\t', unpack=True,
                             max_rows=maxrows)
        indexes = np.ndarray.astype(data[1, :], int)
        ToA_vals = data[2, :]
        ToT_vals = data[3, :]
        x_vals, y_vals = np.unravel_index(indexes, [256, 256])
        if calibration_type is 'NonCalibrated':
            energies = ToT_vals
        else:
            energies = Cluster.calibrate(matrices, x_vals, y_vals, ToT_vals)

        clusters = Cluster.db_cluster(x_vals, y_vals, ToA_vals, energies, eps=1.99, scale=[1.0, 1.0, 100.])
        x_cvals, y_cvals, t_cvals, e_cvals = Cluster.get_clustered_energies(clusters)
        del data
        del energies
        del clusters
        n, bins, patches = plt.hist(e_cvals, bins=numbins, range=[0, maximum], histtype='step',
                                    label=names_hists[i] + ' data', color=colors_hists[i])
        bins2 = np.zeros(len(bins)-1)
        for w in range(len(bins)-1):
            bins2[w] = (bins[w+1] + bins[w])/2
        # ('+str(len(x_cvals))+' clusters)
        for j in range(len(names[i])):
            name = names[i][j]
            print('Fitting '+name+' peak...')
            minarg = minargs[i][j]
            maxarg = maxargs[i][j]
            gauss = Fit.FitGauss().fit(x=bins2[minarg:maxarg], y=n[minarg:maxarg])
            y1 = Fit.gauss(x1, gauss[0])
            mu = gauss[0][1]
            mus.append(mu)
            plt.plot(x1, y1, label=name + r' fit ($\mu$ = ' + str(np.round(mu, 3)) + ')', color=colors_peaks[i][j],
                     linestyle='--')
    plt.xlim(0, maximum)
    if calibration_type is 'NonCalibrated':
        plt.xlabel('ToT value')
    else:
        plt.xlabel('Energy [keV]')
    plt.ylabel('Total counts')
    plt.legend(fontsize='small')
    plt.savefig(output_data_path+calibration_type+'_Histos+Peaks.png')
    return mus


matpath = '/Users/marialauraperez/Desktop/param_mats/'
#param_mats_default = load_parameter_matrices('_SiTPX3.txt', matpath)
#param_mats_stp = load_parameter_matrices('_SourceTestPulse.txt', matpath)
#param_mats_tp = load_parameter_matrices('_TestPulse22deg.txt', matpath)
param_mats_noam = load_parameter_matrices('_STP_NoAm.txt', matpath)

#mus_def = histos_and_peaks(param_mats_default, 'Default', [[0,  6], [12], [15, 35]], [[6,  11], [35], [35, 47]])
#mus_stp = histos_and_peaks(param_mats_stp, 'STP', [[0,  6], [12], [15, 35]], [[6,  11], [35], [35, 47]])
#mus_tp = histos_and_peaks(param_mats_tp, 'Test Pulses', [[0,  5], [12], [15, 30]], [[5, 10], [35], [30, 38]])
mus_noam = histos_and_peaks(param_mats_noam, 'STP (No Am)', [[0,  6], [12], [15, 35]], [[6,  11], [35], [35, 47]])

#print(mus_def)
#print(mus_stp)
#print(mus_tp)
print(mus_noam)