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run-producer_calibration.py
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run-producer_calibration.py
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#!/usr/bin/python
# -*- coding: UTF-8
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/. */
# Authors:
# Michael Berg-Mohnicke <[email protected]>
#
# Maintainers:
# Currently maintained by the authors.
#
# This file has been created at the Institute of
# Landscape Systems Analysis at the ZALF.
# Copyright (C: Leibniz Centre for Agricultural Landscape Research (ZALF)
from datetime import datetime
import capnp
from collections import defaultdict
import copy
import csv
from datetime import date, timedelta
import json
import math
import numpy as np
import os
from pathlib import Path
from pyproj import CRS, Transformer
import sqlite3
import sqlite3 as cas_sq3
import sys
import time
import zmq
import geopandas as gpd
import rasterio
from rasterio.transform import from_origin
from rasterio import features
import monica_io3
import soil_io3
import monica_run_lib
import shared
PATH_TO_REPO = Path(os.path.realpath(__file__)).parent
PATH_TO_MAS_INFRASTRUCTURE_REPO = PATH_TO_REPO / "../mas-infrastructure"
PATH_TO_PYTHON_CODE = PATH_TO_MAS_INFRASTRUCTURE_REPO / "src/python"
if str(PATH_TO_PYTHON_CODE) not in sys.path:
sys.path.insert(1, str(PATH_TO_PYTHON_CODE))
from pkgs.common import common
from pkgs.model import monica_io3
PATH_TO_CAPNP_SCHEMAS = (PATH_TO_MAS_INFRASTRUCTURE_REPO / "capnproto_schemas").resolve()
abs_imports = [str(PATH_TO_CAPNP_SCHEMAS)]
fbp_capnp = capnp.load(str(PATH_TO_CAPNP_SCHEMAS / "fbp.capnp"), imports=abs_imports)
PATHS = {
# adjust the local path to your environmen
"ow-local-remote": {
# "include-file-base-path": "/home/berg/GitHub/monica-parameters/", # path to monica-parameters
"path-to-climate-dir": "/beegfs/common/data/climate/",
# mounted path to archive or hard drive with climate data
"monica-path-to-climate-dir": "/monica_data/climate-data/",
# mounted path to archive accessable by monica executable
"path-to-data-dir": "./data/", # mounted path to archive or hard drive with data
},
"mbm-local-remote": {
# "include-file-base-path": "/home/berg/GitHub/monica-parameters/", # path to monica-parameters
"path-to-climate-dir": "/run/user/1000/gvfs/sftp:host=login01.cluster.zalf.de,user=rpm/beegfs/common/data/climate/",
# mounted path to archive or hard drive with climate data
"monica-path-to-climate-dir": "/monica_data/climate-data/",
# mounted path to archive accessable by monica executable
"path-to-data-dir": "./data/", # mounted path to archive or hard drive with data
},
"mbm-local-local": {
# "include-file-base-path": "/home/berg/GitHub/monica-parameters/", # path to monica-parameters
"path-to-climate-dir": "/run/user/1000/gvfs/sftp:host=login01.cluster.zalf.de,user=rpm/beegfs/common/data/climate/",
# mounted path to archive or hard drive with climate data
"monica-path-to-climate-dir": "/run/user/1000/gvfs/sftp:host=login01.cluster.zalf.de,user=rpm/beegfs/common/data/climate/",
# mounted path to archive accessable by monica executable
"path-to-data-dir": "./data/", # mounted path to archive or hard drive with data
},
"hpc-local-remote": {
# "path-to-climate-dir": "/beegfs/common/data/soil/global_soil_dataset_for_earth_system_modeling/",
# mounted path to archive or hard drive with climate data
"path-to-climate-dir": "/beegfs/common/data/climate/", # mounted path to archive or hard drive with climate data
"monica-path-to-climate-dir": "/monica_data/climate-data/",
# mounted path to archive accessable by monica executable
"path-to-data-dir": "./data/", # mounted path to archive or hard drive with data
},
}
DATA_SOIL_DB = "germany/buek200.sqlite"
DATA_GRID_HEIGHT = "germany/dem_1000_25832_etrs89-utm32n.asc"
DATA_GRID_SLOPE = "germany/slope_1000_25832_etrs89-utm32n.asc"
DATA_GRID_LAND_USE = "germany/landuse_1000_31469_gk5.asc"
DATA_GRID_SOIL = "germany/buek200_1000_25832_etrs89-utm32n.asc"
DATA_GRID_SOIL_OW = "germany/buek200_1000_25832_etrs89-utm32n_OW.asc"
DATA_GRID_CROPS = "germany/OWgermany-crop-ww_1000_25832_etrs89-utm32n.asc" # Added as a cropmap for winter wheat OW
# ORIGINAL DATA_GRID_SOIL = "germany/buek200_1000_25832_etrs89-utm32n.asc"
# DATA_GRID_CROPS = "germany/crops-all2017-2019_1000_25832_etrs89-utm32n.asc"
# DATA_GRID_CROPS = "germany/dwd-stations-pheno_1000_25832_etrs89-utm32n.asc"
# DATA_GRID_CROPS = "germany/germany-complete_1000_25832_etrs89-utm32n.asc"
TEMPLATE_PATH_LATLON = "{path_to_climate_dir}/latlon-to-rowcol.json"
# Additional data for masking the regions
NUTS3_REGIONS = "data/germany/NUTS_RG_03M_25832.shp"
TEMPLATE_PATH_HARVEST = "{path_to_data_dir}/projects/monica-germany/ILR_SEED_HARVEST_doys_{crop_id}.csv"
gdf = gpd.read_file(NUTS3_REGIONS)
def run_producer(server={"server": None, "port": None}):
context = zmq.Context()
socket = context.socket(zmq.PUSH) # pylint: disable=no-member
# config_and_no_data_socket = context.socket(zmq.PUSH)
config = {
"mode": "mbm-local-remote",
"server-port": server["port"] if server["port"] else "6666",
"server": server["server"] if server["server"] else "login01.cluster.zalf.de",
"start-row": "0",
"end-row": "-1",
"path_to_dem_grid": "",
"sim.json": "sim_calibration.json",
"crop.json": "crop_calibration.json",
"site.json": "site.json",
"setups-file": "sim_setups_calibration_OW.csv",
"run-setups": "[1]",
"reader_sr": None,
"path_to_out": "out/",
"only_nuts3_region_ids": "[]", # "[10]",
}
common.update_config(config, sys.argv, print_config=True, allow_new_keys=False)
path_to_out_file = config["path_to_out"] + "/producer.out"
if not os.path.exists(config["path_to_out"]):
try:
os.makedirs(config["path_to_out"])
except OSError:
print("run-calibration-producer.py: Couldn't create dir:", config["path_to_out"], "!")
with open(path_to_out_file, "a") as _:
_.write(f"config: {config}\n")
with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
_.write(f"{datetime.now()} start producer in producer\n")
nuts3_region_ids = json.loads(config["only_nuts3_region_ids"])
# select paths
paths = PATHS[config["mode"]]
# open soil db connection
soil_db_con = sqlite3.connect(paths["path-to-data-dir"] + DATA_SOIL_DB)
# soil_db_con = cas_sq3.connect(paths["path-to-data-dir"] + DATA_SOIL_DB) #CAS.
# connect to monica proxy (if local, it will try to connect to a locally started monica)
socket.connect("tcp://" + config["server"] + ":" + str(config["server-port"]))
# read setup from csv file
setups = monica_run_lib.read_sim_setups(config["setups-file"])
run_setups = json.loads(config["run-setups"])
print("read sim setups: ", config["setups-file"])
with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
_.write(f"{datetime.now()} setup read\n")
# transforms geospatial coordinates from one coordinate reference system to another
# transform wgs84 into gk5
soil_crs_to_x_transformers = {}
wgs84_crs = CRS.from_epsg(4326)
utm32_crs = CRS.from_epsg(25832)
# transformers[wgs84] = Transformer.from_crs(wgs84_crs, gk5_crs, always_xy=True)
ilr_seed_harvest_data = defaultdict(
lambda: {"interpolate": None, "data": defaultdict(dict), "is-winter-crop": None})
# Load grids
## note numpy is able to load from a compressed file, ending with .gz or .bz2
# soil data
path_to_soil_grid = paths["path-to-data-dir"] + DATA_GRID_SOIL
soil_epsg_code = int(path_to_soil_grid.split("/")[-1].split("_")[2])
soil_crs = CRS.from_epsg(soil_epsg_code)
if wgs84_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[wgs84_crs] = Transformer.from_crs(soil_crs, wgs84_crs)
soil_metadata, _ = monica_run_lib.read_header(path_to_soil_grid)
soil_grid = np.loadtxt(path_to_soil_grid, dtype=int, skiprows=6)
print("read: ", path_to_soil_grid)
# height data for germany
path_to_dem_grid = paths["path-to-data-dir"] + DATA_GRID_HEIGHT
dem_epsg_code = int(path_to_dem_grid.split("/")[-1].split("_")[2])
dem_crs = CRS.from_epsg(dem_epsg_code)
if dem_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[dem_crs] = Transformer.from_crs(soil_crs, dem_crs)
dem_metadata, _ = monica_run_lib.read_header(path_to_dem_grid)
dem_grid = np.loadtxt(path_to_dem_grid, dtype=float, skiprows=6)
dem_interpolate = monica_run_lib.create_ascii_grid_interpolator(dem_grid, dem_metadata)
print("read: ", path_to_dem_grid)
# slope data
path_to_slope_grid = paths["path-to-data-dir"] + DATA_GRID_SLOPE
slope_epsg_code = int(path_to_slope_grid.split("/")[-1].split("_")[2])
slope_crs = CRS.from_epsg(slope_epsg_code)
if slope_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[slope_crs] = Transformer.from_crs(soil_crs, slope_crs)
slope_metadata, _ = monica_run_lib.read_header(path_to_slope_grid)
slope_grid = np.loadtxt(path_to_slope_grid, dtype=float, skiprows=6)
slope_interpolate = monica_run_lib.create_ascii_grid_interpolator(slope_grid, slope_metadata)
print("read: ", path_to_slope_grid)
# nuts3_regions
path_to_nuts3_regions_grid = paths["path-to-data-dir"] + "germany/nuts3-regions_1000_25832_etrs89-utm32n.asc"
nuts3_regions_epsg_code = int(path_to_nuts3_regions_grid.split("/")[-1].split("_")[2])
nuts3_regions_crs = CRS.from_epsg(nuts3_regions_epsg_code)
if nuts3_regions_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[nuts3_regions_crs] = Transformer.from_crs(soil_crs, nuts3_regions_crs)
nuts3_regions_metadata, _ = monica_run_lib.read_header(path_to_nuts3_regions_grid)
nuts3_regions_grid = np.loadtxt(path_to_nuts3_regions_grid, dtype=float, skiprows=6)
nuts3_regions_interpolate = monica_run_lib.create_ascii_grid_interpolator(nuts3_regions_grid, nuts3_regions_metadata)
print("read: ", path_to_nuts3_regions_grid)
# land use data
path_to_landuse_grid = paths["path-to-data-dir"] + DATA_GRID_LAND_USE
landuse_epsg_code = int(path_to_landuse_grid.split("/")[-1].split("_")[2])
landuse_crs = CRS.from_epsg(landuse_epsg_code)
if landuse_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[landuse_crs] = Transformer.from_crs(soil_crs, landuse_crs)
landuse_meta, _ = monica_run_lib.read_header(path_to_landuse_grid)
landuse_grid = np.loadtxt(path_to_landuse_grid, dtype=int, skiprows=6)
landuse_interpolate = monica_run_lib.create_ascii_grid_interpolator(landuse_grid, landuse_meta)
print("read: ", path_to_landuse_grid)
# crop mask data
path_to_crop_grid = paths["path-to-data-dir"] + DATA_GRID_CROPS
crop_epsg_code = int(path_to_crop_grid.split("/")[-1].split("_")[2])
crop_crs = CRS.from_epsg(crop_epsg_code)
if crop_crs not in soil_crs_to_x_transformers:
soil_crs_to_x_transformers[crop_crs] = Transformer.from_crs(soil_crs, crop_crs)
crop_meta, _ = monica_run_lib.read_header(path_to_crop_grid)
crop_grid = np.loadtxt(path_to_crop_grid, dtype=int, skiprows=6)
crop_interpolate = monica_run_lib.create_ascii_grid_interpolator(crop_grid, crop_meta)
print("read: ", path_to_crop_grid)
with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
_.write(f"{datetime.now()} grids load producer\n\n")
# Create the function for the mask. This function will later use the additional column in a setup file!
def create_mask_from_shapefile(NUTS3_REGIONS, region_name, path_to_soil_grid):
regions_df = gpd.read_file(NUTS3_REGIONS)
region = regions_df[regions_df["NUTS_NAME"] == region_name]
# This is needed to read the transformation data correctly from the file. With the original opening it does not work
with rasterio.open(path_to_soil_grid) as dataset:
soil_grid = dataset.read(1)
transform = dataset.transform
rows, cols = soil_grid.shape
mask = rasterio.features.geometry_mask([region.geometry.values[0]], out_shape=(rows, cols), transform=transform,
invert=True)
return mask
if len(run_setups) > 1 and run_setups[0] not in setups:
return
else:
setup_id = run_setups[0]
conman = common.ConnectionManager()
reader = conman.try_connect(config["reader_sr"], cast_as=fbp_capnp.Channel.Reader, retry_secs=1)
if reader:
sent_env_count = 0
while True:
msg = reader.read().wait()
# check for end of data from in port
if msg.which() == "done":
break
with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
_.write(f"{datetime.now()} connected\n")
env_template = None
start_setup_time = None
try:
in_ip = msg.value.as_struct(fbp_capnp.IP)
s: str = in_ip.content.as_text()
params = json.loads(s) # keys: MaxAssimilationRate, AssimilateReallocation, RootPenetrationRate
if "only_nuts3_region_ids" in params:
nuts3_region_ids = params["only_nuts3_region_ids"]
del params["only_nuts3_region_ids"]
start_setup_time = time.perf_counter()
setup = setups[setup_id]
crop_id = setup["crop-id"]
#region_name = setup["region_name"]
## extract crop_id from crop-id name that has possible an extenstion
crop_id_short = crop_id.split('_')[0]
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} setup started producer\n")
#if region_name and len(region_name) > 0:
# Create the soil mask for the specific region
#path_to_soil_grid_ow = paths["path-to-data-dir"] + DATA_GRID_SOIL_OW
#mask = create_mask_from_shapefile(NUTS3_REGIONS, region_name, path_to_soil_grid_ow)
# Apply the soil mask to the soil grid
#soil_grid_copy = soil_grid.copy()
#soil_grid[mask == False] = -8888
#soil_grid[soil_grid_copy == -9999] = -9999
# add crop id from setup file
try:
# read seed/harvest dates for each crop_id
path_harvest = TEMPLATE_PATH_HARVEST.format(path_to_data_dir=paths["path-to-data-dir"],
crop_id=crop_id_short)
print("created seed harvest gk5 interpolator and read data: ", path_harvest)
monica_run_lib.create_seed_harvest_geoGrid_interpolator_and_read_data(path_harvest, wgs84_crs, utm32_crs,
ilr_seed_harvest_data)
except IOError:
path_harvest = TEMPLATE_PATH_HARVEST.format(path_to_data_dir=paths["path-to-data-dir"],
crop_id=crop_id_short)
print("Couldn't read file:", path_harvest)
continue
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} crop added producer\n")
cdict = {}
# path to latlon-to-rowcol.json
# path = TEMPLATE_PATH_LATLON.format(path_to_climate_dir=paths["path-to-climate-dir"] + setup["climate_path_to_latlon_file"] + "/")
path = TEMPLATE_PATH_LATLON.format(
path_to_climate_dir=paths["path-to-climate-dir"] + setup["climate_path_to_latlon_file"] + "/")
climate_data_interpolator = monica_run_lib.create_climate_geoGrid_interpolator_from_json_file(path, wgs84_crs,
soil_crs, cdict)
print("created climate_data to gk5 interpolator: ", path)
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} climate data read producer\n")
# read template sim.json
with open(setup.get("sim.json", config["sim.json"])) as _:
sim_json = json.load(_)
# change start and end date according to setup
if setup["start_date"]:
sim_json["climate.csv-options"]["start-date"] = str(setup["start_date"])
if setup["end_date"]:
sim_json["climate.csv-options"]["end-date"] = str(setup["end_date"])
# sim_json["include-file-base-path"] = paths["include-file-base-path"]
# read template site.json
with open(setup.get("site.json", config["site.json"])) as _:
site_json = json.load(_)
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} read site and sim json producer\n\n")
#site_json["EnvironmentParameters"]["rcp"] = scenario
# read template crop.json
with open(setup.get("crop.json", config["crop.json"])) as _:
crop_json = json.load(_)
crop_json["cropRotation"][2] = crop_id
real_crop_id = None
# set value of calibration params
for ws in crop_json["cropRotationTemplates"][crop_id][0]["worksteps"]:
if "Sowing" in ws["type"]:
real_crop_id = ws["crop"][2]
if real_crop_id:
ps = crop_json["crops"][real_crop_id]["cropParams"]
for pname, pval in params.items():
if pname == "DaylengthRequirement":
ps["cultivar"][pname][1] = pval
ps["cultivar"][pname][2] = pval
ps["cultivar"][pname][3] = pval
elif pname == "SpecificLeafArea":
ps["cultivar"][pname][0] *= pval
ps["cultivar"][pname][1] *= pval
ps["cultivar"][pname][2] *= pval
ps["cultivar"][pname][3] *= pval
ps["cultivar"][pname][4] *= pval
ps["cultivar"][pname][5] *= pval
elif pname == "BaseDaylength":
ps["cultivar"][pname][2] = pval
ps["cultivar"][pname][3] = pval
else:
pname_arr = pname.split("_")
i = None
if len(pname_arr) == 2:
pname = pname_arr[0]
i = int(pname_arr[1])
if pname in ps["species"]:
if i:
if len(ps["species"][pname]) < i:
ps["species"][pname][i] = pval
else:
ps["species"][pname] = pval
elif pname in ps["cultivar"]:
if i:
if len(ps["cultivar"][pname]) > i:
ps["cultivar"][pname][i] = pval
else:
ps["cultivar"][pname] = pval
else:
print("Error couldn't find sowing workstep in crop.json")
exit(1)
crop_json["CropParameters"]["__enable_vernalisation_factor_fix__"] = setup[
"use_vernalisation_fix"] if "use_vernalisation_fix" in setup else False
# create environment template from json templates
env_template = monica_io3.create_env_json_from_json_config({
"crop": crop_json,
"site": site_json,
"sim": sim_json,
"climate": ""
})
scols = int(soil_metadata["ncols"])
srows = int(soil_metadata["nrows"])
scellsize = int(soil_metadata["cellsize"])
xllcorner = int(soil_metadata["xllcorner"])
yllcorner = int(soil_metadata["yllcorner"])
nodata_value = int(soil_metadata["nodata_value"])
# unknown_soil_ids = set()
soil_id_cache = {}
print("All Rows x Cols: " + str(srows) + "x" + str(scols))
for srow in range(0, srows):
print(srow, end=", ")
if srow < int(config["start-row"]):
continue
elif int(config["end-row"]) > 0 and srow > int(config["end-row"]):
break
for scol in range(0, scols):
soil_id = int(soil_grid[srow, scol])
if soil_id == nodata_value:
continue
# get coordinate of clostest climate element of real soil-cell
sh = yllcorner + (scellsize / 2) + (srows - srow - 1) * scellsize
sr = xllcorner + (scellsize / 2) + scol * scellsize
# inter = crow/ccol encoded into integer
crow, ccol = climate_data_interpolator(sr, sh)
crop_grid_id = int(crop_grid[srow, scol])
# print(crop_grid_id)
if crop_grid_id != 1 or soil_id == -8888:
continue
tcoords = {}
if nuts3_regions_crs not in tcoords:
tcoords[nuts3_regions_crs] = soil_crs_to_x_transformers[nuts3_regions_crs].transform(sr, sh)
n3r, n3h = tcoords[nuts3_regions_crs]
nuts3_region_id = int(nuts3_regions_interpolate(n3r, n3h))
if not nuts3_region_id or (len(nuts3_region_ids) > 0 and nuts3_region_id not in nuts3_region_ids):
continue
if soil_id in soil_id_cache:
soil_profile = soil_id_cache[soil_id]
else:
soil_profile = soil_io3.soil_parameters(soil_db_con, soil_id)
soil_id_cache[soil_id] = soil_profile
if not soil_profile or len(soil_profile) == 0:
continue
worksteps = env_template["cropRotation"][0]["worksteps"]
sowing_ws = next(filter(lambda ws: ws["type"][-6:] == "Sowing", worksteps))
harvest_ws = next(filter(lambda ws: ws["type"][-7:] == "Harvest", worksteps))
ilr_interpolate = ilr_seed_harvest_data[crop_id_short]["interpolate"]
seed_harvest_cs = ilr_interpolate(sr, sh) if ilr_interpolate else None
# set external seed/harvest dates
if seed_harvest_cs:
seed_harvest_data = ilr_seed_harvest_data[crop_id_short]["data"][seed_harvest_cs]
if seed_harvest_data:
is_winter_crop = ilr_seed_harvest_data[crop_id_short]["is-winter-crop"]
if setup[
"sowing-date"] == "fixed": # fixed indicates that regionally fixed sowing dates will be used
sowing_date = seed_harvest_data["sowing-date"]
elif setup[
"sowing-date"] == "auto": # auto indicates that automatic sowng dates will be used that vary between regions
sowing_date = seed_harvest_data["latest-sowing-date"]
elif setup[
"sowing-date"] == "fixed1": # fixed1 indicates that a fixed sowing date will be used that is the same for entire germany
sowing_date = sowing_ws["date"]
sds = [int(x) for x in sowing_date.split("-")]
sd = date(2001, sds[1], sds[2])
sdoy = sd.timetuple().tm_yday
if setup[
"harvest-date"] == "fixed": # fixed indicates that regionally fixed harvest dates will be used
harvest_date = seed_harvest_data["harvest-date"]
elif setup[
"harvest-date"] == "auto": # auto indicates that automatic harvest dates will be used that vary between regions
harvest_date = seed_harvest_data["latest-harvest-date"]
elif setup[
"harvest-date"] == "auto1": # fixed1 indicates that a fixed harvest date will be used that is the same for entire germany
harvest_date = harvest_ws["latest-date"]
hds = [int(x) for x in harvest_date.split("-")]
hd = date(2001, hds[1], hds[2])
hdoy = hd.timetuple().tm_yday
esds = [int(x) for x in seed_harvest_data["earliest-sowing-date"].split("-")]
esd = date(2001, esds[1], esds[2])
# sowing after harvest should probably never occur in both fixed setup!
if setup["sowing-date"] == "fixed" and setup["harvest-date"] == "fixed":
# calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy-1))
if is_winter_crop:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy - 1))
else:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=hdoy)
sowing_ws["date"] = seed_harvest_data["sowing-date"]
harvest_ws["date"] = "{:04d}-{:02d}-{:02d}".format(hds[0], calc_harvest_date.month,
calc_harvest_date.day)
elif setup["sowing-date"] == "fixed" and setup["harvest-date"] == "auto":
if is_winter_crop:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy - 1))
else:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=hdoy)
sowing_ws["date"] = seed_harvest_data["sowing-date"]
harvest_ws["latest-date"] = "{:04d}-{:02d}-{:02d}".format(hds[0], calc_harvest_date.month,
calc_harvest_date.day)
elif setup["sowing-date"] == "fixed" and setup["harvest-date"] == "auto1":
if is_winter_crop:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy - 1))
else:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=hdoy)
sowing_ws["date"] = seed_harvest_data["sowing-date"]
harvest_ws["latest-date"] = "{:04d}-{:02d}-{:02d}".format(hds[0], hds[1], hds[2])
elif setup["sowing-date"] == "auto" and setup["harvest-date"] == "fixed":
sowing_ws["earliest-date"] = seed_harvest_data["earliest-sowing-date"] if esd > date(
esd.year, 6, 20) else "{:04d}-{:02d}-{:02d}".format(sds[0], 6, 20)
calc_sowing_date = date(2000, 12, 31) + timedelta(days=max(hdoy + 1, sdoy))
sowing_ws["latest-date"] = "{:04d}-{:02d}-{:02d}".format(sds[0], calc_sowing_date.month,
calc_sowing_date.day)
harvest_ws["date"] = seed_harvest_data["harvest-date"]
elif setup["sowing-date"] == "auto" and setup["harvest-date"] == "auto":
sowing_ws["earliest-date"] = seed_harvest_data["earliest-sowing-date"] if esd > date(
esd.year, 6, 20) else "{:04d}-{:02d}-{:02d}".format(sds[0], 6, 20)
if is_winter_crop:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy - 1))
else:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=hdoy)
sowing_ws["latest-date"] = seed_harvest_data["latest-sowing-date"]
harvest_ws["latest-date"] = "{:04d}-{:02d}-{:02d}".format(hds[0], calc_harvest_date.month,
calc_harvest_date.day)
elif setup["sowing-date"] == "fixed1" and setup["harvest-date"] == "fixed":
# calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy-1))
if is_winter_crop:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=min(hdoy, sdoy - 1))
else:
calc_harvest_date = date(2000, 12, 31) + timedelta(days=hdoy)
sowing_ws["date"] = sowing_date
# print(seed_harvest_data["sowing-date"])
harvest_ws["date"] = "{:04d}-{:02d}-{:02d}".format(hds[0], calc_harvest_date.month,
calc_harvest_date.day)
# check if current grid cell is used for agriculture
if setup["landcover"]:
if landuse_crs not in tcoords:
tcoords[landuse_crs] = soil_crs_to_x_transformers[landuse_crs].transform(sr, sh)
lur, luh = tcoords[landuse_crs]
landuse_id = landuse_interpolate(lur, luh)
if landuse_id not in [2, 3, 4]:
continue
if dem_crs not in tcoords:
tcoords[dem_crs] = soil_crs_to_x_transformers[dem_crs].transform(sr, sh)
demr, demh = tcoords[dem_crs]
height_nn = dem_interpolate(demr, demh)
if slope_crs not in tcoords:
tcoords[slope_crs] = soil_crs_to_x_transformers[slope_crs].transform(sr, sh)
slr, slh = tcoords[slope_crs]
slope = slope_interpolate(slr, slh)
env_template["params"]["userCropParameters"]["__enable_T_response_leaf_expansion__"] = setup[
"LeafExtensionModifier"]
# print("soil:", soil_profile)
env_template["params"]["siteParameters"]["SoilProfileParameters"] = soil_profile
# setting groundwater level
if setup["groundwater-level"]:
groundwaterlevel = 20
layer_depth = 0
for layer in soil_profile:
if layer.get("is_in_groundwater", False):
groundwaterlevel = layer_depth
# print("setting groundwaterlevel of soil_id:", str(soil_id), "to", groundwaterlevel, "m")
break
layer_depth += monica_run_lib.get_value(layer["Thickness"])
env_template["params"]["userEnvironmentParameters"]["MinGroundwaterDepthMonth"] = 3
env_template["params"]["userEnvironmentParameters"]["MinGroundwaterDepth"] = [
max(0, groundwaterlevel - 0.2), "m"]
env_template["params"]["userEnvironmentParameters"]["MaxGroundwaterDepth"] = [
groundwaterlevel + 0.2, "m"]
# setting impenetrable layer
if setup["impenetrable-layer"]:
impenetrable_layer_depth = monica_run_lib.get_value(
env_template["params"]["userEnvironmentParameters"]["LeachingDepth"])
layer_depth = 0
for layer in soil_profile:
if layer.get("is_impenetrable", False):
impenetrable_layer_depth = layer_depth
# print("setting leaching depth of soil_id:", str(soil_id), "to", impenetrable_layer_depth, "m")
break
layer_depth += monica_run_lib.get_value(layer["Thickness"])
env_template["params"]["userEnvironmentParameters"]["LeachingDepth"] = \
[impenetrable_layer_depth, "m"]
env_template["params"]["siteParameters"]["ImpenetrableLayerDepth"] = \
[impenetrable_layer_depth, "m"]
if setup["elevation"]:
env_template["params"]["siteParameters"]["heightNN"] = float(height_nn)
if setup["slope"]:
env_template["params"]["siteParameters"]["slope"] = slope / 100.0
if setup["latitude"]:
clat, _ = cdict[(crow, ccol)]
env_template["params"]["siteParameters"]["Latitude"] = clat
if setup["CO2"]:
env_template["params"]["userEnvironmentParameters"]["AtmosphericCO2"] = float(setup["CO2"])
if setup["O3"]:
env_template["params"]["userEnvironmentParameters"]["AtmosphericO3"] = float(setup["O3"])
if setup["FieldConditionModifier"]:
env_template["cropRotation"][0]["worksteps"][0]["crop"]["cropParams"]["species"][
"FieldConditionModifier"] = float(setup["FieldConditionModifier"])
if setup["StageTemperatureSum"]:
stage_ts = setup["StageTemperatureSum"].split('_')
stage_ts = [int(temp_sum) for temp_sum in stage_ts]
orig_stage_ts = env_template["cropRotation"][0]["worksteps"][0]["crop"]["cropParams"]["cultivar"]["="][
"StageTemperatureSum"][0]
if len(stage_ts) != len(orig_stage_ts):
stage_ts = orig_stage_ts
print('The provided StageTemperatureSum array is not '
'sufficiently long. Falling back to original StageTemperatureSum')
env_template["cropRotation"][0]["worksteps"][0]["crop"]["cropParams"]["cultivar"]["="][
"StageTemperatureSum"][0] = stage_ts
env_template["params"]["simulationParameters"]["UseNMinMineralFertilisingMethod"] = setup[
"fertilization"]
env_template["params"]["simulationParameters"]["UseAutomaticIrrigation"] = setup["irrigation"]
env_template["params"]["simulationParameters"]["NitrogenResponseOn"] = setup["NitrogenResponseOn"]
env_template["params"]["simulationParameters"]["WaterDeficitResponseOn"] = setup[
"WaterDeficitResponseOn"]
env_template["params"]["simulationParameters"]["EmergenceMoistureControlOn"] = setup[
"EmergenceMoistureControlOn"]
env_template["params"]["simulationParameters"]["EmergenceFloodingControlOn"] = setup[
"EmergenceFloodingControlOn"]
env_template["csvViaHeaderOptions"] = sim_json["climate.csv-options"]
env_template["pathToClimateCSV"] = \
paths["monica-path-to-climate-dir"] + \
f"dwd/csvs/germany_ubn_1901-01-01_to_2022-09-30/{crow}/daily_mean_RES1_C{ccol}R{crow}.csv.gz"
print("pathToClimateCSV:", env_template["pathToClimateCSV"])
env_template["customId"] = {
"setup_id": setup_id,
"srow": srow, "scol": scol,
"crow": int(crow), "ccol": int(ccol),
"soil_id": soil_id,
"env_id": sent_env_count+1,
"nodata": False,
"nuts3_region_id": nuts3_region_id,
}
sent_env_count += 1
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} Sending jobs out (producer)\n")
socket.send_json(env_template)
print("sent env ", sent_env_count, " customId: ", env_template["customId"])
#with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
# _.write(f"{datetime.now()} Ended jobs (producer)\n")
# END OF THE "FOR" LOOP
except Exception as e:
with open(path_to_out_file, "a") as _:
_.write(f"raised exception: {e}\n")
print("Exception raised:", e)
raise e
with open(config["path_to_out"] + "/spot_setup.out", "a") as _:
_.write(f"{datetime.now()} Sending final last message (producer) \n")
# send a last message will be just forwarded by monica to signify last
if env_template:
env_template["pathToClimateCSV"] = ""
env_template["customId"] = {
"no_of_sent_envs": sent_env_count,
"nodata": True
}
socket.send_json(env_template)
stop_setup_time = time.perf_counter()
print("\nSetup ", setup_id, ":", sent_env_count, " envs took ", (stop_setup_time - start_setup_time),
" seconds")
sent_env_count = 0
if __name__ == "__main__":
run_producer()