Source code for oasislmf.pytools.gulmc.common

import numba as nb
import numpy as np

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

# gul stream type
# probably need to set this dynamically depending on the stream type

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gul_header = np.int32(1 | 2 << 24).tobytes()



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Item = nb.from_dtype(np.dtype([('item_id', np.int32),
                               ('coverage_id', np.int32),
                               ('areaperil_id', areaperil_int),
                               ('vulnerability_id', np.int32),
                               ('group_id', np.int32)
                               ]))



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ItemAdjustment = nb.from_dtype(np.dtype([('item_id', np.int32),
                                         ('intensity_adjustment', np.int32),
                                         ('return_period', np.int32)
                                         ]))



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items_data_type = nb.from_dtype(np.dtype([('item_id', np.int32),
                                          ('damagecdf_i', np.int32),
                                          ('rng_index', np.int32)
                                          ]))



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items_MC_data_type = nb.from_dtype(np.dtype([('item_id', np.int32),
                                             ('item_idx', np.int32),
                                             ('hazcdf_i', np.int32),
                                             ('rng_index', np.int32),
                                             ('hazard_rng_index', np.int32),
                                             ('intensity_adjustment', np.int32),
                                             ('return_period', np.int32)
                                             ]))



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VulnCdfLookup = nb.from_dtype(np.dtype([('start', np.int32),
                                        ('length', np.int32)]))




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coverage_type = nb.from_dtype(np.dtype([('tiv', np.float64),
                                        ('max_items', np.int32),
                                        ('start_items', np.int32),
                                        ('cur_items', np.int32)
                                        ]))



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NP_BASE_ARRAY_SIZE = 8




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ITEM_MAP_KEY_TYPE = nb.types.Tuple((nb.from_dtype(areaperil_int), nb.types.int32))

# ITEM_MAP_VALUE_TYPE = nb.types.UniTuple(nb.types.int32, 1)

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ITEM_MAP_VALUE_TYPE = nb.types.int64


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AREAPERIL_TO_EFF_VULN_KEY_TYPE = nb.types.Tuple((nb.from_dtype(areaperil_int), nb.types.int64))


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AREAPERIL_TO_EFF_VULN_VALUE_TYPE = nb.types.UniTuple(nb.types.int32, 2)


# compute the relative size of oasis_float and areaperil_int vs int32

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oasis_float_to_int32_size = oasis_float.itemsize // np.int32().itemsize


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areaperil_int_to_int32_size = areaperil_int.itemsize // np.int32().itemsize



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haz_cdf_type = nb.from_dtype(np.dtype([('probability', oasis_float),
                                       ('intensity_bin_id', np.int32)]))



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ProbMean = nb.from_dtype(np.dtype([('prob_to', oasis_float),
                                   ('bin_mean', oasis_float)
                                   ]))


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ProbMean_size = ProbMean.size



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damagecdfrec_stream = nb.from_dtype(np.dtype([('event_id', np.int32),
                                              ('areaperil_id', areaperil_int),
                                              ('vulnerability_id', np.int32)
                                              ]))



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damagecdfrec = nb.from_dtype(np.dtype([('areaperil_id', areaperil_int),
                                       ('vulnerability_id', np.int32)
                                       ]))




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gulSampleslevelHeader = nb.from_dtype(np.dtype([('event_id', 'i4'),
                                                ('item_id', 'i4'),
                                                ]))


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gulSampleslevelHeader_size = gulSampleslevelHeader.size



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gulSampleslevelRec = nb.from_dtype(np.dtype([('sidx', 'i4'),
                                             ('loss', oasis_float),
                                             ]))


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gulSampleslevelRec_size = gulSampleslevelRec.size




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Keys = {'LocID': np.int32,
        'PerilID': 'category',
        'CoverageTypeID': np.int32,
        'AreaPerilID': areaperil_int,
        'VulnerabilityID': np.int32}




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NormInversionParameters = nb.from_dtype(np.dtype([('x_min', np.float32),
                                                  ('x_max', np.float32),
                                                  ('N', np.int32),
                                                  ('cdf_min', np.float32),
                                                  ('cdf_max', np.float32),
                                                  ]))