# pack_str_list = []
# import matplotlib.pyplot as plt
# import matplotlib.ticker as ticker
from map_packages_colors_all import *

def plot_abs_data_n_arr(n_arr, data, pack_str):
    if len(n_arr) > len(data):
        plt.plot(n_arr[0:len(data)], data, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    elif len(n_arr) < len(data):
        plt.plot(n_arr, data[0:len(n_arr)], linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    else:
        plt.plot(n_arr, data, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)

def plot_comp_data_n_arr(n_arr, data_1, data_2, pack_str):
    ratio_arr = []
    if len(data_1) == len(data_2):
        for i, elem in enumerate(data_1):
            ratio_arr.append(elem/float(data_2[i]))
    elif len(data_1) > len(data_2):
        for i, elem in enumerate(data_2):
            ratio_arr.append(data_1[i]/float(elem))
        # plt.plot(n_arr[0:len(data_2)], ratio_arr, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    elif len(data_2) > len(data_1):
        for i, elem in enumerate(data_1):
            ratio_arr.append(elem/data_2[i])
        # plt.plot(n_arr[0:len(data_1)], ratio_arr, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    # print(ratio_arr)
    if len(n_arr) > len(ratio_arr):
        plt.plot(n_arr[0:len(ratio_arr)], ratio_arr, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    elif len(n_arr) < len(ratio_arr):
        plt.plot(n_arr, ratio_arr[0:len(n_arr)], linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)
    else:
        plt.plot(n_arr, ratio_arr, linestyle='-', marker=symbol_dict[pack_str], label=label_dict[pack_str], color=color_dict[pack_str], markersize=5)


def gen_settings(fig, ax, xlabel_str, ylabel_str, log_x_on, log_y_on, xlim_on, xlim_low, xlim_upp, ylim_on, ylim_low, ylim_upp, leg_loc, fn):

    ax.tick_params(direction='in', which='both', bottom=True, top=True, left=True, right=True)
    # ax.xaxis.set_major_locator(MaxNLocator(integer=True))
    ax.xaxis.set_major_locator(ticker.AutoLocator())
    ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
    ax.yaxis.set_major_locator(ticker.AutoLocator())
    ax.yaxis.set_minor_locator(ticker.AutoMinorLocator())

    if log_x_on:
        ax.set_xscale('log')
    if log_y_on:
        ax.set_yscale('log')
    if xlim_on == True:
        plt.xlim([xlim_low, xlim_upp])
    if ylim_on == True:
        plt.ylim([ylim_low, ylim_upp])
    # plt.xlabel(r"N (system size)")
    # plt.ylabel(r"Time ($t_{package}$)")
    plt.xlabel(xlabel_str)
    plt.ylabel(ylabel_str)
    if leg_loc== "out":
        ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), prop={'size': 8})

    elif leg_loc == None:
        ax.legend(loc=0)

    plt.tight_layout()
    fig.set_dpi(100)
    if fn == None:
        pass
    else:
        plt.savefig(fn)
    plt.show()
    # plt.savefig("perf_heisenberg_pure_evolution_single_thread_wallclock_absolute.pdf")
    # plt.savefig("perf_heisenberg_pure_evolution_single_thread_wallclock_relative_line.svg", format="svg", dpi=1200)
    # plt.show()