def setUp(self):
self.pprocessing_result_filename = get_data_path('out.csv', DATA_DIR)
self.first_data_row = {'eventID': 1, 'Agency': 'AAA', 'month': 1,
'depthError': 0.5, 'second': 13.0,
'SemiMajor90': 2.43, 'year': 2000,
'ErrorStrike': 298.0, 'timeError': 0.02,
'sigmamb': '', 'latitude': 44.368,
'sigmaMw': 0.355, 'sigmaMs': '',
'Mw': 1.71, 'Ms': '',
'Identifier': 20000102034913, 'day': 2,
'minute': 49, 'hour': 3,
'mb': '', 'SemiMinor90': 1.01,
'longitude': 7.282, 'depth': 9.3,
'ML': 1.7, 'sigmaML': 0.1}
self.second_data_row = {'eventID': 2, 'Agency': 'AAA', 'month': 1,
'depthError': 0.5, 'second': 57.0,
'SemiMajor90': 0.77, 'year': 2000,
'ErrorStrike': 315.0, 'timeError': 0.1,
'sigmamb': 0.1, 'latitude': 44.318,
'sigmaMw': 0.199, 'sigmaMs': '',
'Mw': 3.89, 'Ms': '',
'Identifier': 20000105132157, 'day': 5,
'minute': 21, 'hour': 13,
'mb': 3.8, 'SemiMinor90': 0.25,
'longitude': 11.988, 'depth': 7.9,
'ML': '', 'sigmaML': ''}
self.writer = EqEntryWriter(self.pprocessing_result_filename)
self.expected_csv = get_data_path('expected_entries.csv', DATA_DIR)
def setUp(self):
self.context_jobs = create_context('config_jobs.yml')
self.expected_preprocessed_catalogue = get_data_path(
'expected_preprocessed_catalogue.csv', DATA_DIR)
self.expected_preprocessed_ctable = get_data_path(
'expected_completeness_table.csv', DATA_DIR)
def setUp(self):
self.context_jobs = create_context('config_jobs.yml')
self.expected_preprocessed_catalogue = get_data_path(
'expected_preprocessed_catalogue.csv', DATA_DIR)
self.expected_preprocessed_ctable = get_data_path(
'expected_completeness_table.csv', DATA_DIR)
def setUp(self):
self.context_preprocessing = Context(
get_data_path('config_preprocessing.yml', DATA_DIR))
self.preprocessing_builder = PreprocessingBuilder()
self.context_processing = Context(
get_data_path('config_processing.yml', DATA_DIR))
self.processing_builder = ProcessingBuilder()
def setUp(self):
self.correct_filename = get_data_path('ISC_small_data.csv', DATA_DIR)
self.csv_reader = CsvReader(self.correct_filename)
self.first_data_row = [
'1', 'AAA', '20000102034913',
'2000', '01', '02',
'03', '49', '13',
'0.02', '7.282', '44.368',
'2.43', '1.01', '298',
'9.3', '0.5', '1.71',
'0.355', ' ', ' ',
' ', ' ', '1.7',
'0.1']
def setUp(self):
self.first_data_row = [
1, 'AAA', 20000102034913, 2000, 01, 02, 03, 49, 13, 0.02, 7.282,
44.368, 2.43, 1.01, 298, 9.3, 0.5, 1.71, 0.355, '', '', '', '',
1.7, 0.1
]
self.data_row_to_convert = [
'2', 'AAA', '20000105132157', '2000', '01', '05', '13', '21', '57',
'0.10', '11.988', '44.318', '0.77', '0.25', '315', '7.9', '0.5',
'3.89', '0.199', ' ', ' ', '3.8', '0.1', ' ', ' '
]
self.eq_reader = EqEntryReader(
open(get_data_path('ISC_small_data.csv', DATA_DIR)))
def setUp(self):
def square_job(context):
value = context.number
context.number = value * value
def double_job(context):
value = context.number
context.number = 2 * value
self.square_job = square_job
self.double_job = double_job
self.pipeline = PipeLine()
self.context_preprocessing = Context(
get_data_path('config_preprocessing.yml', DATA_DIR))
self.context_preprocessing.number = 2
def setUp(self):
self.first_data_row = [1, 'AAA', 20000102034913,
2000, 01, 02,
03, 49, 13,
0.02, 7.282, 44.368,
2.43, 1.01, 298,
9.3, 0.5, 1.71,
0.355, '', '',
'', '', 1.7, 0.1]
self.data_row_to_convert = ['2', 'AAA', '20000105132157',
'2000', '01', '05',
'13', '21', '57',
'0.10', '11.988', '44.318',
'0.77', '0.25', '315',
'7.9', '0.5', '3.89',
'0.199', ' ', ' ',
'3.8', '0.1', ' ', ' ']
self.eq_reader = EqEntryReader(open(get_data_path('ISC_small_data.csv',
DATA_DIR)))
import os
from lxml import etree
from nrml.nrml_xml import get_data_path, DATA_DIR, SCHEMA_DIR
from nrml.reader import NRMLReader
from nrml.writer import AreaSourceWriter
from mtoolkit.source_model import (AreaSource, POINT, AREA_BOUNDARY,
TRUNCATED_GUTEN_RICHTER)
from mtoolkit.source_model import (MAGNITUDE, RUPTURE_RATE_MODEL,
RUPTURE_DEPTH_DISTRIB)
AREA_SOURCE = get_data_path('area_source_model.xml', DATA_DIR)
AREA_SOURCES = get_data_path('area_sources.xml', DATA_DIR)
INCORRECT_NRML = get_data_path('incorrect_area_source_model.xml', DATA_DIR)
SCHEMA = get_data_path('nrml.xsd', SCHEMA_DIR)
OUTPUT_NRML = os.path.join(get_data_path('', DATA_DIR),
'serialized_models.xml')
def create_area_source():
asource = AreaSource()
asource.nrml_id = "n1"
asource.source_model_id = "sm1"
asource.area_source_id = "src03"
asource.name = "Quito"
def setUp(self):
self.pprocessing_result_filename = get_data_path('out.csv', DATA_DIR)
self.first_data_row = {
'eventID': 1,
'Agency': 'AAA',
'month': 1,
'depthError': 0.5,
'second': 13.0,
'SemiMajor90': 2.43,
'year': 2000,
'ErrorStrike': 298.0,
'timeError': 0.02,
'sigmamb': '',
'latitude': 44.368,
'sigmaMw': 0.355,
'sigmaMs': '',
'Mw': 1.71,
'Ms': '',
'Identifier': 20000102034913,
'day': 2,
'minute': 49,
'hour': 3,
'mb': '',
'SemiMinor90': 1.01,
'longitude': 7.282,
'depth': 9.3,
'ML': 1.7,
'sigmaML': 0.1
}
self.second_data_row = {
'eventID': 2,
'Agency': 'AAA',
'month': 1,
'depthError': 0.5,
'second': 57.0,
'SemiMajor90': 0.77,
'year': 2000,
'ErrorStrike': 315.0,
'timeError': 0.1,
'sigmamb': 0.1,
'latitude': 44.318,
'sigmaMw': 0.199,
'sigmaMs': '',
'Mw': 3.89,
'Ms': '',
'Identifier': 20000105132157,
'day': 5,
'minute': 21,
'hour': 13,
'mb': 3.8,
'SemiMinor90': 0.25,
'longitude': 11.988,
'depth': 7.9,
'ML': '',
'sigmaML': ''
}
self.writer = EqEntryWriter(self.pprocessing_result_filename)
self.expected_csv = get_data_path('expected_entries.csv', DATA_DIR)
def create_context(filename=None):
"""Create a context using config file"""
return Context(get_data_path(filename, DATA_DIR))
def create_context(filename=None):
"""Create a context using config file"""
return Context(get_data_path(filename, DATA_DIR))
"""
The purpose of this module is to provide functions which tackle specific job,
some of them wrap scientific functions defined in the scientific module.
"""
import logging
import numpy as np
from mtoolkit.eqcatalog import EqEntryReader, EqEntryWriter
from nrml.reader import NRMLReader
from nrml.nrml_xml import get_data_path, SCHEMA_DIR
from mtoolkit.source_model import default_area_source
NRML_SCHEMA_PATH = get_data_path('nrml.xsd', SCHEMA_DIR)
CATALOG_COMPLETENESS_MATRIX_YEAR_INDEX = 0
CATALOG_MATRIX_MW_INDEX = 5
CATALOG_MATRIX_FIXED_COLOUMNS = ['year', 'month', 'day',
'longitude', 'latitude', 'Mw', 'sigmaMw']
COMPLETENESS_TABLE_MW_INDEX = 1
SIGMA_MW_INDEX = 6
LOGGER = logging.getLogger('mt_logger')
def logged_job(job):
"""
Decorate a job by adding logging
statements before and after the execution
of the job.
def setUp(self):
self.context_preprocessing = Context(
get_data_path('config_preprocessing.yml', DATA_DIR))
"""
The purpose of this module is to provide functions which tackle specific job,
some of them wrap scientific functions defined in the scientific module.
"""
import logging
import numpy as np
from mtoolkit.eqcatalog import EqEntryReader, EqEntryWriter
from nrml.reader import NRMLReader
from nrml.nrml_xml import get_data_path, SCHEMA_DIR
from mtoolkit.source_model import default_area_source
NRML_SCHEMA_PATH = get_data_path('nrml.xsd', SCHEMA_DIR)
CATALOG_COMPLETENESS_MATRIX_YEAR_INDEX = 0
CATALOG_MATRIX_MW_INDEX = 5
CATALOG_MATRIX_FIXED_COLOUMNS = ['year', 'month', 'day',
'longitude', 'latitude', 'Mw', 'sigmaMw']
COMPLETENESS_TABLE_MW_INDEX = 1
LOGGER = logging.getLogger('mt_logger')
def logged_job(job):
"""
Decorate a job by adding logging
statements before and after the execution
of the job.
"""
"""
The purpose of this module is to provide functions which tackle specific job,
some of them wrap scientific functions defined in the scientific module.
"""
import logging
import numpy as np
from mtoolkit.eqcatalog import EqEntryReader, EqEntryWriter
from nrml.reader import NRMLReader
from nrml.nrml_xml import get_data_path, SCHEMA_DIR
from mtoolkit.source_model import default_area_source
NRML_SCHEMA_PATH = get_data_path("nrml.xsd", SCHEMA_DIR)
CATALOG_COMPLETENESS_MATRIX_YEAR_INDEX = 0
CATALOG_MATRIX_MW_INDEX = 5
CATALOG_MATRIX_FIXED_COLOUMNS = ["year", "month", "day", "longitude", "latitude", "Mw", "sigmaMw"]
COMPLETENESS_TABLE_MW_INDEX = 1
SIGMA_MW_INDEX = 6
LOGGER = logging.getLogger("mt_logger")
def logged_job(job):
"""
Decorate a job by adding logging
statements before and after the execution
of the job.
"""
import os
from lxml import etree
from nrml.nrml_xml import get_data_path, DATA_DIR, SCHEMA_DIR
from nrml.reader import NRMLReader
from nrml.writer import AreaSourceWriter
from mtoolkit.source_model import (AreaSource, POINT, AREA_BOUNDARY,
TRUNCATED_GUTEN_RICHTER)
from mtoolkit.source_model import (MAGNITUDE, RUPTURE_RATE_MODEL,
RUPTURE_DEPTH_DISTRIB)
AREA_SOURCE = get_data_path('area_source_model.xml', DATA_DIR)
AREA_SOURCES = get_data_path('area_sources.xml', DATA_DIR)
INCORRECT_NRML = get_data_path('incorrect_area_source_model.xml', DATA_DIR)
SCHEMA = get_data_path('nrml.xsd', SCHEMA_DIR)
OUTPUT_NRML = os.path.join(
get_data_path('', DATA_DIR), 'serialized_models.xml')
def create_area_source():
asource = AreaSource()
asource.nrml_id = "n1"
asource.source_model_id = "sm1"
asource.area_source_id = "src03"
asource.name = "Quito"