ens_stat

#!/usr/bin/env python
import sys
import numpy as np
from ecl.summary import EclSum

# This small example illustrates how the EclSum class and numpy can be used to
# assemble basis ensemble statistics from a list of simulations. The current
# example is mainly to illustrate loading how to load summary cases, and the
# use of the EclSum.numpy_vector() to extract summary vectors - it does not
# really "do anything" with the calculated statistics.



# Input is a list of paths to simulation cases, and the return value is the
# corresponding list of EclSum instances.
def load(argv):
    case_list = []
    for case in argv:
        case_list.append( EclSum(case) )

    return case_list


# This function will take a list of EclSum instances and a summary key - e.g.
# 'FOPT' and create a 2D numpy array where each realization corresponds to one
# column. The summary vectors are evaulated - with interpolation - at every
# month. It is assumed that all summary cases cover the same temporal range.
def numpy_matrix(case_list, key):
    case0 = case_list[0]
    time_points = case0.time_range(interval="1M")

    data = np.ndarray((len(time_points), len(case_list)))
    for index,case in enumerate(case_list):
        v = case.numpy_vector(key, time_index = time_points)
        data[:,index] = v
    return data


def stats(case_list, key):
    data = numpy_matrix(case_list, key)

    mean = np.mean(data, axis=1)
    std = np.std(data, axis=1)

    try:
        p10 = np.quantile(data, 0.10, axis=1)
        p90 = np.quantile(data, 0.90, axis=1)
    except AttributeError:
        print("Sorry - current numpy version:{} does not have the quantile function - upgrade to 1.15.".format(np.version.full_version))



def main(argv):
    case_list = load(argv)
    stats(case_list, "FOPT")

# Typical usage:
#
# ens_stat simulations/CASE*.SMSPEC

if __name__ == "__main__":
    main(sys.argv[1:])