from parameters import Param
import matplotlib.pyplot as plt
from utils import make_gif, make_plot
from time import time
from pathlib import Path
import sys
PATH = sys.argv[1] if len(sys.argv) == 2 else str(Path(__file__).parent.absolute())[:-3]+'imgs/'
NAME = 'huge'
fst = Param(
CLUSTERS = 12**2,
CLUST_SIDE_LEN = 7,
DAYS = 100,
INFECTION_TIME = 20,
DEATH_RATE = 0.4,
INFECT_RATE = 0.3,
MIGRATIONS_PER_DAY = 100,
FEAR_RATE = 0.4,
HEALTHCARE_CAPACITY = 2500
)
start = time()
cumulative, active, healed, dead, migrations, real_mig = run_simulation(fst, PATH)
print('time elapsed:', time() - start, flush=True)
make_gif(PATH, NAME)
# plt.plot(range(len(migrations)), migrations, label='migrations', color='blue')
plt.plot(range(len(real_mig)), real_mig, label='migrations', color='blue', ls=':')
from parameters import Param
import rgdf
import matplotlib.pyplot as plt
import time
import glob
import schwimmbad
import numpy as np
from netCDF4 import Dataset
import iotools
import datetime
plt.ion()
# load the paragridded parameters
param = Param()
param.dirgigabin = "/ccc/store/cont003/gch0401/gch0401/GIGATL1_1h_tides/BIN_1h_JG"
param.dirgrid = "/ccc/scratch/cont003/ra4735/gulaj/GIGATL1/INIT_N100_100_100/GRD3"
param.dirgrid = "/ccc/scratch/cont003/gen12051/groullet/giga/GRD"
# setup readers
rgdf.setup_predefine_readers(param)
# list of tiles in region 7
reg7 = [t for t, r in param.subdmap.items() if r == 7]
def get_alldates(datadir, subd):
""" return the dates converted into dat file"""
files = glob.glob(f"{datadir}/{subd:02}/*.dat")
"""
Tools to manage the RGDF database
"""
from parameters import Param
import rgdf
import glob
param = Param()
def get_whatisdone(param, subd):
""" return the list of dates that are completed in region subd
"""
pattern = f"{param.dirgigabin}/{subd:02}/giga_*_{subd:02}.dat"
files = glob.glob(pattern)
dates = [f.split("/")[-1].split("_")[1] for f in files]
return dates
def scan_all(param):
dates = {}
for subd in range(1, 14):
dates[subd] = get_whatisdone(param, subd)
return dates
import os
import sys
import tensorflow as tf
from parameters import Param
from src.model.model import Net
# Obtain parameters
args = Param()
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
def main(_):
Net_model = Net
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=1.0)
config = tf.ConfigProto(gpu_options=gpu_options)
config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
model = Net_model(sess, args)
if __name__ == '__main__':
tf.app.run()
from parameters import Param import giga_subdomains as gs import datetime as dt import dates import ncconvert import migration param = Param() # Region 1 (Gulf Stream separation): 78W-68W, 30N-40N; dom = ((-78, 30), (-68, 40)) # Region 2 (Gulf Stream extension): 54W-44W, 30N-40N dom = ((-54, 30), (-44, 40)) domain = gs.LLTR2domain(*dom) tiles = gs.find_tiles_inside(param, domain) subds = [param.subdmap[t] for t in tiles] print(set(subds)) # Pour les périodes: # # Aug., Sep. and Oct. 2008 # Feb., Mar. and Apr. 2009 d0 = dt.datetime(2008, 8, 1, 0) d1 = dt.datetime(2008, 11, 1, 0) d0 = dt.datetime(2009, 2, 1, 0) d1 = dt.datetime(2009, 5, 1, 0) hisdates = dates.daterange(d0, d1, dates.day)