Source code for oasislmf.pytools.lec.data

import numba as nb
import numpy as np

from oasislmf.pytools.common.data import oasis_float, oasis_int

# Output flags

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AGG_FULL_UNCERTAINTY = 0


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AGG_WHEATSHEAF = 1


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AGG_SAMPLE_MEAN = 2


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AGG_WHEATSHEAF_MEAN = 3


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OCC_FULL_UNCERTAINTY = 4


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OCC_WHEATSHEAF = 5


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OCC_SAMPLE_MEAN = 6


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OCC_WHEATSHEAF_MEAN = 7


# EPCalcs

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MEANDR = 1


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FULL = 2


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PERSAMPLEMEAN = 3


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MEANSAMPLE = 4


# EPTypes

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OEP = 1


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OEPTVAR = 2


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AEP = 3


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AEPTVAR = 4



# Outloss mean and sample dtype, summary_id, period_no (and sidx) obtained from index

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OUTLOSS_DTYPE = np.dtype([
    ("row_used", np.bool_),
    ("agg_out_loss", oasis_float),
    ("max_out_loss", oasis_float),
])



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EPT_output = [
    ('SummaryId', oasis_int, '%d'),
    ('EPCalc', oasis_int, '%d'),
    ('EPType', oasis_int, '%d'),
    ('ReturnPeriod', oasis_float, '%.6f'),
    ('Loss', oasis_float, '%.6f'),
]



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PSEPT_output = [
    ('SummaryId', oasis_int, '%d'),
    ('SampleId', oasis_int, '%d'),
    ('EPType', oasis_int, '%d'),
    ('ReturnPeriod', oasis_float, '%.6f'),
    ('Loss', oasis_float, '%.6f'),
]



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EPT_headers = [c[0] for c in EPT_output]


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PSEPT_headers = [c[0] for c in PSEPT_output]


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EPT_dtype = np.dtype([(c[0], c[1]) for c in EPT_output])


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PSEPT_dtype = np.dtype([(c[0], c[1]) for c in PSEPT_output])


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EPT_fmt = ','.join([c[2] for c in EPT_output])


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PSEPT_fmt = ','.join([c[2] for c in PSEPT_output])



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LOSSVEC2MAP_dtype = np.dtype([
    ("summary_id", oasis_int),
    ("period_no", np.int32),
    ("period_weighting", np.float64),
    ("value", oasis_float),
])



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WHEATKEYITEMS_dtype = np.dtype([
    ("summary_id", oasis_int),
    ("sidx", oasis_int),
    ("period_no", np.int32),
    ("period_weighting", np.float64),
    ("value", oasis_float),
])



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MEANMAP_dtype = np.dtype([
    ("retperiod", np.float64),
    ("mean", np.float64),
    ("count", np.int32),
])


# For Dict of summary_id (oasis_int) to nb_Tail_valtype

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TAIL_valtype = np.dtype([
    ("retperiod", np.float64),
    ("tvar", oasis_float),
])


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NB_TAIL_valtype = nb.types.Array(nb.from_dtype(TAIL_valtype), 1, "C")