py3DCORE_h4c_basic/plottingroutine.py at master · helioforecast/py3DCORE_h4c_basic · GitHub

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import numpy as np
import matplotlib.pyplot as plt
import pickle as p

import datetime as datetime
from datetime import timedelta
import seaborn as sns
import pandas as pd
import os

import multiprocessing
#import copy as cp

import py3dcore_h4c as py3dcore_h4c

import py3dcore_h4c.fluxplot as fp

import warnings
warnings.filterwarnings('ignore')

plt.switch_backend('agg')

import logging

logging.basicConfig(level=logging.INFO)
logging.getLogger("heliosat.spice").setLevel("WARNING")
logging.getLogger("heliosat.spacecraft").setLevel("WARNING")
logging.getLogger("sunpy").setLevel("WARNING")
logging.getLogger("py3dcore_h4c.fluxplot").setLevel("WARNING")


## setting the times for py3dcore_h4c

t_launch = datetime.datetime(2022, 9, 5, 18, 45, tzinfo=datetime.timezone.utc) # launch time assumed at CME impact at PSP at 14.72 Rs

t_s = datetime.datetime(2022, 9, 7, 8, tzinfo=datetime.timezone.utc)
t_e = datetime.datetime(2022, 9, 8, 3, tzinfo=datetime.timezone.utc)

start = t_s + datetime.timedelta(hours=1)

t_fit = [
        datetime.datetime(2022, 9, 7, 9, tzinfo=datetime.timezone.utc),
        datetime.datetime(2022, 9, 7, 15, tzinfo=datetime.timezone.utc),
        datetime.datetime(2022, 9, 7, 20, tzinfo=datetime.timezone.utc),
        datetime.datetime(2022, 9, 8, 2, tzinfo=datetime.timezone.utc)
     ]

#t_fit = fp.equal_t_creator(start = start, n = 4, delta = 6)

#####2022 Sep 5: 3 solar radii at 17 UT (COR2 & LASCO FoV appearance)
# 2022 Sep 5: 15 solar radii at 18:45 UT (PSP)


## loading the pickle files

path = 'output/solo06092022_heeq_1024_restrP_3/'

filepath = fp.loadpickle(path, number = -1)


# checking if the directory demo_folder2
# exist or not.

if not os.path.isdir(filepath[:-7] + 'movie_3d/'):
    os.makedirs(filepath[:-7] + 'movie_3d/')

if not os.path.isdir(filepath[:-7] + 'movie_3d_multiview/'):
    os.makedirs(filepath[:-7] + 'movie_3d_multiview/')

# plot fullinsitu image

fp.fullinsitu(observer='solo', t_fit=t_fit, start=t_s, end=t_e, filepath=filepath,
              custom_data='solo_2022sep.p', best=False, ensemble=True, mean=True,
              save_fig=True, legend=True, fixed=None)

# plot scatterplot

fp.scatterparams(filepath)

# plot full3d

tm1 =  t_launch + datetime.timedelta(days=1.7)

fp.full3d(spacecraftlist=['solo', 'psp'], planetlist =['Earth'],t = tm1, filepath = filepath)

def make_frame(k):
    tm0 = datetime.datetime(2022, 9, 5, 19)
    t = tm0 + k*datetime.timedelta(hours=1)

    fig = fp.full3d(spacecraftlist=['solo', 'psp'], planetlist =['Earth'],
              t = t, filepath = filepath, save_fig = False)
    frmstr = '%05i' % (k)
    plt.savefig(filepath[:-7] + 'movie_3d/'+frmstr+'.jpg',dpi=200)
    return fig

#for i in range(100):
#    fig = make_frame(i)
#    plt.clf()

inn=[i for i in range(100)]


mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame, inn[0:20])
mpool.close()
mpool.join()

print('done 1/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame, inn[20:40])
mpool.close()
mpool.join()

print('done 2/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame, inn[40:60])
mpool.close()
mpool.join()

print('done 3/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame, inn[40:80])
mpool.close()
mpool.join()

print('done 4/4')

os.system('ffmpeg -r 25 -i '+filepath[:-7]+'movie_3d/%05d.jpg -b 5000k -r 25 '+filepath[:-7]+'movie_3d/full_3d_movie.mp4 -y -loglevel quiet')


#measurement times
#tm0 =  t_launch + datetime.timedelta(days=1.5)
tm0 =  datetime.datetime(2022, 9, 7, 1)
tm1 =  t_launch + datetime.timedelta(days=1.7)
tm2 =  t_launch + datetime.timedelta(days=3.5)

fig = fp.full3d_multiview(t_launch = t_launch, filepath=filepath)

def make_frame2(k):
    tm0 = datetime.datetime(2022, 9, 5, 19)
    t = tm0 + k*datetime.timedelta(hours=1)
    frametime = k

    fig = fp.full3d_multiview_movie(t_launch = tm0, t = t, filepath=filepath,
                                    frametime=k)
    frmstr = '%05i' % (k)
    plt.savefig(filepath[:-7] + 'movie_3d_multiview/'+frmstr+'.jpg',dpi=200)
    return fig

inn=[i for i in range(100)]


mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame2, inn[0:20])
mpool.close()
mpool.join()

print('done 1/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame2, inn[20:40])
mpool.close()
mpool.join()

print('done 2/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame2, inn[40:60])
mpool.close()
mpool.join()

print('done 3/4')

mpool = multiprocessing.Pool(processes=5)
mpool.map(make_frame2, inn[40:80])
mpool.close()
mpool.join()

print('done 4/4')

os.system('ffmpeg -r 25 -i '+filepath[:-7]+'movie_3d_multiview/%05d.jpg -b 5000k -r 25 '+filepath[:-7]+'movie_3d/full_3d_multiview_movie.mp4 -y -loglevel quiet')