#!/usr/bin/env python3
import sys
sys.path.append('../')
from LoLIM import utilities
import numpy as np
import pandas as pd
from stokesIO import read_polarization_data
from stokes import stokes_plotter
timeID = "D20190424T210306.154Z"
utilities.default_processed_data_loc = "/home/student4/Marten/processed_files"
rd = read_polarization_data(timeID)
pulseID = 1477200
data = rd.read_PE(pulseID)
data = data.values
stokes_plot = stokes_plotter(plot=['polarization_ellipse'])
stokes_plot.plot_polarization_ellipse(data, errors=True)
stokes_plot.showPlots()
if __name__ == "__main__":
#station_names = natural_sort(station_timing_offsets.keys())
data_folder = processed_data_folder + "/polarization_data/Lightning Phenomena/K changes"
pName = "KC13" #phenomena name
Zlimit = 50 #max zenith angle for which antenna model should hold!
δlimit = 0.8 #lower limit for the degree of polarization (pulses below this limit are observed to have large errorbars due to local interference or pulses are mixed together in time)
with open(data_folder + '/' + "source_info_{}.json".format(pName),
'r') as f:
source_info = json.load(f)
with open(data_folder + '/' + "pulseIDs_{}.pkl".format(pName), 'rb') as f:
pulseIDs = pickle.load(f)
rd = read_polarization_data(timeID,
alt_loc=data_folder + '/' +
"{}_data".format(pName))
sv = save_acceleration_vector(timeID,
fname="a_vectors_{}".format(pName),
alt_loc=data_folder + '/' +
"{}_data".format(pName))
pbar = tqdm(pulseIDs,
ascii=True,
unit_scale=True,
dynamic_ncols=True,
position=0)
for pulseID in pbar:
pbar.set_description("Processing pulse {}".format(pulseID))
"""
sort station names according to zenith angle (Z) and impose a Z requirement
"""
for i in range(sort_indices.size):
print("{} : {} deg".format(station_names[i],Z[i]))
"""
#
Zlimit = 50
station_names = [station_names[i] for i in np.where(Z<=Zlimit)[0]]
with open(data_folder + "/pulseIDs_" + pName + ".pkl", 'rb') as f:
pulseIDs = pickle.load(f)
rd = read_polarization_data(timeID, alt_loc="polarization_data/Lightning Phenomena/K changes/" + pName + "_data")
for pulseID in pulseIDs:
if pulseID == 1481534:
τ = np.array([])
τ_err = np.array([])
r = np.empty((0,3))
df = rd.read_PE(pulseID)
if df.empty:
continue
#max_stations = 3
#station_select = 21
#i = 0