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_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))
""" 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"