funcs_solver_new.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jan 16 17:44:54 2024

@author: Mino Sorribas
"""

import numpy as np
import pandas as pd
from datetime import datetime,timedelta
import itertools

def dump_mgb_binary_to_stats_npy(filebin, fileout, nt, nc, itini):
    """ Read binary file (MGB format) and dump content to .npy """
    # read from file
    #'<f4' indicates little-endian (<) float(f) 4 byte (4)
    dados = np.fromfile(filebin,'<f4').reshape(nt,nc)
    
    # filter hotstart
    dados = dados[itini:,:]
    
    # statistics
    stats_qm = np.mean(dados,axis=0)
    stats_q95 = np.quantile(dados,0.05,axis=0)
    dados_stats = np.vstack((stats_qm, stats_q95))

    # dump fo hard disk
    np.save(fileout,dados_stats)
    return None


def stats_mmap_to_dataframe(stats_mmap, list_c, list_st):
    """ Read data from memmap as dataframe

    Args:
        stats_mmap (np.memmap) :: memory map of stats binary .npy

        list_c (list) :: list of integer of selected catchments
                         such as generated by
                         .make_dict_bho_ixc()
        list_st (integer) :: rows of statistic

    Returns:
        df (pd.DataFrame) :: time-series of selected values
    """

    # adjust loc in array
    ixt_ = [i for i in list_st]
    ixc_ = [int(i-1) for i in list_c]  # mini column [1,nc] -> python [0,nc-1]

    # get selection
    idx = np.ix_(ixt_, ixc_)
    a = stats_mmap[idx]

    # make dataframe
    #times = [dstart + timedelta(days=i) for i in list_t]
    st_headers = ['qm', 'q95']
    df = pd.DataFrame(a, columns=list_c, index=st_headers)

    return df