import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.basemap import Basemap


def data_read(file):
    with open(file, 'r') as f:
        data = f.readlines()

    row_header = int(data[0].split(',')[1].strip())
    row_variable = int(data[0].split(',')[5].strip())
    row_column = int(data[0].split(',')[6].strip())

    var = data[row_header - row_variable:row_header]
    data = [tuple(s.replace('\n', '').strip() for s in row.split(',')) for row in data[row_header:-1]]

    dtype = []
    for row in var:
        row = [s.replace("'", '').strip() for s in row.split(',')]
        num = int(row[2])
        type_s = 'float' if num > 0 else 'string'
        for k in range(num):
            name_s = row[0] + ('_{:d}'.format(k + 1) if num > 1 else '')
            dtype.append((name_s, type_s))

    assert len(dtype) == row_column

    data = np.array(data, dtype=dtype)

    return dtype, data


def orbit():
    _, data = data_read('assets/orbit.csv')
    lat, lon = data['Latitude'], data['Longitude'] - 180

    m = Basemap()
    m.drawcoastlines()
    m.fillcontinents(color='white', lake_color='lightskyblue')
    m.drawmapboundary(fill_color='skyblue')
    m.scatter(lon, lat, s=1)
    plt.savefig('docs/orbit.png', bbox_inches='tight')


def GCR(M=1):
    _, data = data_read('assets/CREME86-M{:d}.csv'.format(M))
    E = data['Energy']
    proton_i, proton_d = data['IFlux_1'], data['DFlux_1']
    alpha_i, alpha_d = data['IFlux_2'], data['DFlux_2']

    fig, ax1 = plt.subplots(1, 1)
    ax1.plot(E, proton_i, label=r'$p$')
    ax1.plot(E, alpha_i, label=r'$\alpha$')
    ax1.set_yscale('log')
    ax1.set_ylabel(r'$Integrated\ Flux\ (\mathrm{m^{-2}sr^{-1}s^{-1}})$')
    ax1.legend(loc="upper left")

    ax2 = ax1.twinx()
    ax2.plot(E, proton_d, linestyle=':', label=r'$p$')
    ax2.plot(E, alpha_d, linestyle=':', label=r'$\alpha$')
    ax2.set_yscale('log')
    ax2.set_ylabel(r'$Differential\ Flux\ (\mathrm{m^{-2}sr^{-1}s^{-1}MeV^{-1}})$')
    ax2.legend(loc="upper right")

    ax1.set_xlabel(r'$Energy\ (\mathrm{MeV})$')
    ax1.set_xlim(1, 1e5)
    plt.title('Average spectra - M = {:d}'.format(M))
    plt.xscale('log')
    plt.savefig('docs/spectra-M{:d}'.format(M))

GCR()
GCR(3)