# -*- coding: utf-8 -*-
"""
Created on Mon May 27 11:45:19 2024

@author: bertoz_b
"""

import time
import pandas as pd
import dask.dataframe as dd
import dask
from dask.distributed import Client
from dask_jobqueue import SLURMCluster
import gc

from SP2XR_toolkit import (
    find_files,
    read_and_process_sp2b,
    read_csv_files_with_dask_2,
    process_sp2b_parquet,
    resample_to_dt,
    chunks,
    list_first_level_subdirs,
    process_pbp_parquet,
    get_file_dict,
)


# %% Define directories and folders

parent_directory = "/data/user/bertoz_b/SP2XR/data/NyA"
source_directory = parent_directory + "/SP2XR_files"

target_directory_pbp_parquet = parent_directory + "/SP2XR_pbp_parquet"
filter_string_pbp = "PbP"

target_directory_sp2b_parquet = parent_directory + "/SP2XR_sp2b_parquet"
filter_string_sp2b = "sp2b"

target_directory_hk_parquet = parent_directory + "/SP2XR_hk_parquet"
filter_string_hk = "hk"

meta_file_pbp = pd.read_parquet(
    "/data/user/bertoz_b/SP2XR/final_test_script_and_data/meta_files/pbp_meta.parquet",
    engine="fastparquet",
)
meta_file_hk = pd.read_parquet(
    "/data/user/bertoz_b/SP2XR/final_test_script_and_data/meta_files/hk_meta.parquet",
    engine="fastparquet",
)
meta_file_sp2b = pd.read_parquet(
    "/data/user/bertoz_b/SP2XR/final_test_script_and_data/meta_files/meta_sp2b_20240619.parquet",
    engine="pyarrow",
)

matching_files_pbp = find_files(source_directory, filter_string_pbp)
matching_files_hk = find_files(source_directory, filter_string_hk)
matching_files_sp2b = find_files(source_directory, filter_string_sp2b)[10000:50000]


# %% PBP: From csv/zip to parquet


start_time = time.time()
cluster = SLURMCluster(
    cores=64,
    processes=64,
    memory="128GB",
    walltime="05:59:00",
    job_extra_directives=["--partition=daily"],
)
cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)


i = 0
for chunk_pbp in chunks(matching_files_pbp, 100):
    print(f"chunk: {i}")

    dask.compute(
        *[
            read_csv_files_with_dask_2(
                f, meta_file_pbp, meta_file_hk, target_directory_pbp_parquet
            )
            for f in chunk_pbp
        ]
    )

    gc.collect()
    i += 1

client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))


# %% HK: From csv/zip to parquet


start_time = time.time()
cluster = SLURMCluster(
    cores=16,
    processes=16,
    memory="128GB",
    walltime="07:59:00",
    job_extra_directives=["--partition=daily"],
)
cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)

i = 0
for chunk_hk in chunks(matching_files_hk, 100):
    print(f"chunk: {i}")

    dask.compute(
        *[
            read_csv_files_with_dask_2(
                f, meta_file_pbp, meta_file_hk, target_directory_hk_parquet
            )
            for f in chunk_hk
        ]
    )

    gc.collect()
    i += 1

client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))

# %% SP2B: From csv/zip to parquet


start_time = time.time()
cluster = SLURMCluster(
    cores=64,
    processes=64,
    memory="128GB",  # 2GB/process should sufficient
    walltime="02:59:00",
    job_extra_directives=["--partition=daily"],
)
cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)

sp2b_orig = read_and_process_sp2b(
    matching_files_sp2b, target_directory_sp2b_parquet, meta_file_sp2b
)

client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))


# %%  PBP: from single particle to specified dt


# config_path = '/data/user/bertoz_b/SP2XR/data/Granada/SP2XR_files/20240612/20240612061852'
config_path = "/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_files/20200922/20200922064903"

# The level keyword has been added to control the partitioning columns of the processed pbp files,
# this level has to match the partition_on keyword in the process_pbp_parquet function below
files_pbp = get_file_dict(target_directory_pbp_parquet, "PbP", level="date")
files_hk = get_file_dict(target_directory_hk_parquet, "HK", level="date")


list_pbp = []
list_hk = []
for key in files_pbp:
    if key in files_hk:
        list_pbp.append(files_pbp[key])
        list_hk.append(files_hk[key])


start_time = time.time()

cluster = SLURMCluster(
    cores=8,
    processes=8,
    memory="128GB",
    walltime="11:59:00",
    job_extra_directives=["--partition=daily"],
)

cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)

# when at hour level the chunks can also be of 50 (hours), when level is day the chuncks should be max 25 (days)
# when using the cluster settings above (8cores, 128GB)
i = 0
for chunk_pbp, chunk_hk in zip(chunks(list_pbp, 25), chunks(list_hk, 25)):
    print(f"chunk: {i}")

    dask.compute(
        *[
            process_pbp_parquet(
                dir_path_pbp,
                dir_path_hk,
                dt=60,
                rho_eff=1800,
                BC_type="constant_effective_density",
                inc_calib_curve="polynomial",
                inc_calib_params=[0.05, 2.0470000507725255e-07],
                scatt_calib_curve="powerlaw",
                scatt_calib_params=[17.21724257, 0.16908516, -1.49431104],
                config_file_dir=config_path,
                minM=0.3,
                maxM=400,
                n_incbins=50,
                minOptD=100,
                maxOptD=500,
                n_scattbins=20,
                minTL=-10,
                maxTL=400,
                n_timelag=100,
                path_parquet="/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_pbp_processed_20250212/",
                partition_on=["date"],
                save_final_data=True,
            )
            for dir_path_pbp, dir_path_hk in zip(chunk_pbp, chunk_hk)
        ]
    )
    gc.collect()
    i += 1

client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))


# %% PBP: Resample

dir_pbp_1s = list_first_level_subdirs(
    "/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_pbp_processed_new"
)


start_time = time.time()

cluster = SLURMCluster(
    cores=8,
    processes=8,
    memory="32GB",
    walltime="00:20:00",
    job_extra_directives=["--partition=hourly"],
)

cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)


i = 0
for chunk_pbp in chunks(dir_pbp_1s, 50):
    print(f"chunk: {i}")

    dask.compute(
        *[
            resample_to_dt(
                dir_path_pbp,
                dt=60,
                path_parquet="/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_pbp_processed_new_1min/",
                save_final_data=True,
            )
            for dir_path_pbp in chunk_pbp
        ]
    )
    gc.collect()
    i += 1

client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))


# %% SP2B: Process parquet files
# This is a very old function, it might need revisiting

start_time = time.time()

cluster = SLURMCluster(
    cores=8,
    processes=8,
    memory="16GB",
    walltime="00:30:00",
    job_extra_directives=["--partition=hourly"],
)
cluster.scale(1)
client = Client(cluster)
print(client.dashboard_link)


sp2_raw_traces = dd.read_parquet(
    "/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_sp2b_parquet", calculate_divisions=True
)  # .repartition(freq='1h')

test2 = process_sp2b_parquet(
    sp2_raw_traces,
    scatt_sat_threshold=1e9,
    inc_sat_threshold=1e8,
    scatt_noise_threshold=1e4,
    end_bkgr_ch0=100,
    end_bkgr_ch1=350,
    output_path="/data/user/bertoz_b/SP2XR/data/NyA/SP2XR_sp2b_processed",
)


client.close()
cluster.close()
print("--- %s seconds ---" % (time.time() - start_time))