#!/usr/bin/python

import os
import sys
import glob
import pickle
import numpy as np
import matplotlib.pyplot as plt


def blocking_display_signal_map(
    data_vector: np.ndarray,
    fp: str,
    vmin: float = -80.0,
    vmax: float = -40.0
):
    '''
    '''
    plt.scatter(data_vector[:, 3], data_vector[:, 4], s=50, c=data_vector[:, 2])
    # plt.xlim()
    # plt.ylim()
    plt.colorbar()
    plt.xlabel('loc x (m)')
    plt.ylabel('loc y (m)')
    # plt.show()
    plt.draw()
    plt.savefig(fp, dpi=50)
    # plt.pause(0.1)
    # q = input("press Enter to continue... type q to quit: ")
    # if q == 'q':
    #     sys.exit()
    plt.close()


if len(sys.argv) < 3:
    print('Usage: {} pickle_fp outputfolder'.format(sys.argv[0]))
    sys.exit(0)

pickle_fp = sys.argv[1]
outputfolder = sys.argv[2]
if not os.path.isdir(outputfolder):
    try:
        os.makedirs(outputfolder)
    except BaseException:
        raise

############################
# load
############################
all_data = pickle.load(open(pickle_fp, 'rb'))

for data in all_data:
    num_of_entries = len(data['measurements'])
    filename = (
        "{}_{}_{}_{}_{}_{}_{}entries.png"
        .format(data['country_code'], data['radio'], data['mcc'], data['mnc'], data['area'], data['cell'], num_of_entries)
    )
    blocking_display_signal_map(data['measurements'], "{}/{}".format(outputfolder, filename))