def call_make_map(animation, kelpType, plot_type, experiments, polygons):
startdate = '01022018'
enddate = '02022018'
experiment = 1
paths = "results/Bekkelaget_microplast_drift_01022018_to_28022018_sinkspeed_0.01_experiment_1.nc" #"results/MarMine_molusc_opendrift_"+str(startdate)+"_to_"+str(enddate)+"_novertical.nc"
confobj = confm.bekkelaget_conf()
make_map(confobj,
paths,
kelpType,
plot_type,
experiment=experiments,
polygons=polygons)
outfile=confobj.outputFilename,
export_variables=[
'sea_floor_depth_below_sea_level', 'z', 'terminal_velocity'
])
if __name__ == "__main__":
start_time = time.time()
experiments = [0,
1] # Used as index other places so have to run from 0---N
years = [2019]
for experiment in experiments:
confobj = confm.bekkelaget_conf(experiment)
for year in years:
confobj.startdate = datetime(year, 7, 1, 12, 0, 0)
confobj.enddate = datetime(year, 7, 7, 12, 0, 0)
logging.debug("Running experiment for period {} to {}".format(
confobj.startdate.year, confobj.enddate))
for confobj.select_sinking_velocity in confobj.sinkingvelocities:
confobj.experiment = experiment
createOutputFilenames(confobj)
logging.debug(
"Result files will be stored as:\nnetCDF=> {}".format(
confobj.outputFilename))
createAndRunSimulation(confobj)
from pprint import pprint
from netCDF4 import Dataset, date2num, num2date
from scipy.ndimage.filters import gaussian_filter
import matplotlib
import os
import config_bekkelaget as confm
import probability_distribution_map_v2 as pb
import time
o = PelagicPlanktonDrift(loglevel=0) # Set loglevel to 0 for debug information
#######################
# Preparing readers
#######################
confobj = confm.bekkelaget_conf()
base = 'results'
baseout = 'figures'
hexagon = False
startdate = '01062015'
enddate = '30122015'
experiment = 1
start_time = time.time()
experiments = [1]
years = [2018]
for year in years:
confobj.startdate = datetime(year, 2, 5, 0, 0, 0)