02-run-fv-kmj.py

import os
from dotenv import load_dotenv
import numpy as np
import pandas as pd
import altair as alt
from io import StringIO
import xarray as xr
from sklearn.metrics import roc_auc_score
from xbootstrap import block_bootstrap
import xskillscore as xs


from dask.distributed import Client
from vthree_utils import get_threshold

from vthree_utils import BinCreateParams
from vthree_utils import run_xhist2d
from vthree_utils import run_xhist1d


load_dotenv()

# Get environment variables
#ea_input_path = os.getenv("ea_input_path")
ea_input_path='./'
sa_file = os.getenv("sa_file")
polygon_pq_uri = os.getenv("polygon_pq_uri")


# Now create the BinCreateParams object
params = BinCreateParams(
    region_id=0,
    season_str="MAM",
    lead_int=2,
    level="mod",
    region_name_dict={0: "Karamoja", 1: "Marsabit", 2: "Wajir"},
    spi_prod_name="spi3",
    data_path=ea_input_path,
    output_path=os.path.join(os.getcwd(), "output"),
    spi4_data_path="",
    obs_netcdf_file=os.path.join(ea_input_path, "kmj_obs_spi3_masked.nc"),
    fct_netcdf_file=os.path.join(ea_input_path, "kmj_rgr_seas51_spi3_masked.nc"),
    service_account_json=sa_file,
    gcs_file_url=polygon_pq_uri,
    region_filter="kmj",
)

"""
run_xhist2d(params)
run_xhist1d(params)


params.lead_int = 3
run_xhist2d(params)
run_xhist1d(params)

params.lead_int = 4
run_xhist2d(params)
run_xhist1d(params)
"""
params.season_str = "JJA"
params.sc_season_str = "jja"
params.spi_prod_name = "spi3"
# params.data_path = params.spi4_data_path
params.lead_int = 2
run_xhist2d(params)
run_xhist1d(params)


params.lead_int = 3
run_xhist2d(params)
run_xhist1d(params)

params.lead_int = 4
run_xhist2d(params)
run_xhist1d(params)