def setUp(self):
self.pathToConfgiFiles = os.path.dirname(os.path.abspath(__file__))
self.path_to_default_test_config_file = self.pathToConfgiFiles + '/test_config.cfg'
self.defaultSpec = {
"Section1": [
ConfigurationOption(
"aPositiveInt",
"",
int,
[
ConfigurationOptionValidation(
lambda value: value > 0,
"This value must be positive.")]),
ConfigurationOption(
"aNegativeInt",
"",
int,
[
ConfigurationOptionValidation(
lambda value: value < 0,
"This value must be negative.")]),
ConfigurationOption(
"aBoolean",
"",
to_bool)
],
"Section2": [
ConfigurationOption(
"aPositiveInt",
"",
int,
[
ConfigurationOptionValidation(
lambda value: value > 0,
"This value must be positive.")]),
ConfigurationOption(
"aNegativeInt",
"",
int,
[
ConfigurationOptionValidation(
lambda value: value < 0,
"This value must be negative.")]),
ConfigurationOption(
"aFloat",
"",
float),
ConfigurationOption(
"aBoolean",
"",
to_bool)
],
}
def test_invalid_value(self):
spec = {
"Section1": [
ConfigurationOption(
"aPositiveInt",
"",
int,
[
ConfigurationOptionValidation(
lambda value: value > 200,
"This value must be very large.")])
]
}
self.assertRaises(ValueError, Configuration, self.path_to_default_test_config_file, spec)
"""
Created on Nov 19, 2015
@author: Fabian Leven
"""
from driftchamber.core.configuration.configuration_option import ConfigurationOption
from driftchamber.core.configuration.configuration_option_validation import ConfigurationOptionValidation
from driftchamber.core.configuration.parsing_functions import parse_module_sequence
configuration_specification = {
"MultiModule": [
ConfigurationOption("moduleSequence", (
"A list of the module names that shall be executed by the run engine. "
"Separate the module names using line breaks. "
"The corresponding module has to be present in the module folder. "
"In more detail, this means there must be a python file present called "
"'ModuleNameModule' in the module folder in a sub folder also called "
"'ModuleNameModule'. "
"It must hold a class called 'ModuleName' "
"(without the 'Module' at the end)."
), parse_module_sequence, [
ConfigurationOptionValidation(
lambda value: len(value) > 0,
"There must be at least one module in the module sequence of the 'MultiModule'."
)
]),
],
}
# [#A list of conditions the value must satisfy.
# _ConfigurationOptionValidation(lambda value: value > 0,
# "This value must be greater than 0"),
# _ConfigurationOptionValidation(lambda value: value < 10,
# "This value must be smaller than 10"),
# ]
# # weather the option must be present (True) in the configuration or not (False)
# False,
#),
ConfigurationOption(
"nEvent",
"The amount of events to simulate. This has to be a positive integer.",
int,
[
ConfigurationOptionValidation(
lambda value: value > 0,
"The amount of events must be a positive integer.")]),
ConfigurationOption(
"levelOfLogging",
("The level of the logging. Must be one of the following: "
"'CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG', 'NOTSET'."),
lambda value: {'CRITICAL': logging.CRITICAL,
'ERROR': logging.ERROR,
'WARNING': logging.WARNING,
'INFO': logging.INFO,
'DEBUG': logging.DEBUG,
'NOTSET': logging.NOTSET}[value.upper()],
p_isCompulsory = False)
],
"Modules":[
ConfigurationOption(
from driftchamber.core.configuration.configuration_option import ConfigurationOption
from driftchamber.core.configuration.configuration_option_validation import ConfigurationOptionValidation
configuration_specification = {
'Particle': [
ConfigurationOption('mass',
'The mass of the particle in GeV.',
float,
[ConfigurationOptionValidation(
lambda value: value > 0,
'The mass of the particle must be positive.'
)],
p_isCompulsory=True),
ConfigurationOption('name',
'The name of a particle.',
lambda value: str(value),
p_isCompulsory=True),
ConfigurationOption('max_mom',
'The maximum momentum of a particle in GeV.',
float,
[ConfigurationOptionValidation(
lambda value: value > 0,
'The maximum momentum of a particle must be positive.'
)],
p_isCompulsory=True),
ConfigurationOption('x_pos',
'The initial x-position of the particle in cells of the detector',
int,
p_isCompulsory=True),
ConfigurationOption('y_pos',
from driftchamber.core.configuration.configuration_option import ConfigurationOption
from driftchamber.core.configuration.configuration_option_validation import ConfigurationOptionValidation
configuration_specification = {
'Particle': [
ConfigurationOption(
'mass',
'The mass of the particle in GeV.',
float, [
ConfigurationOptionValidation(
lambda value: value > 0,
'The mass of the particle must be positive.')
],
p_isCompulsory=True),
ConfigurationOption('name',
'The name of a particle.',
lambda value: str(value),
p_isCompulsory=True),
ConfigurationOption(
'probability',
'The probability for noise per cell and event',
float, [
ConfigurationOptionValidation(
lambda value: value >= 0 and value <= 1,
'The probability must be a number between 0 and 1.')
],
p_isCompulsory=True)
]
}
# -*- coding: utf-8 -*-
"""
@author: elcerdo
"""
__author__ = 'elcerdo'
from driftchamber.core.configuration.configuration_option import ConfigurationOption
from driftchamber.core.configuration.configuration_option_validation import ConfigurationOptionValidation
configuration_specification = {
'Tracking': [
ConfigurationOption('precision',
'Decimal precision',
float, [
ConfigurationOptionValidation(
lambda value: value >= 0,
'The precision should be positive.')
],
p_isCompulsory=True),
ConfigurationOption('threshold',
'minimum hits in houghspace to generate Track',
int, [
ConfigurationOptionValidation(
lambda value: value >= 0,
'The threshold should be positive.')
],
p_isCompulsory=True),
ConfigurationOption('minDistance',
'minimum distance in houghspace from other Tracks',
int, [
ConfigurationOptionValidation(
from ast import literal_eval
from driftchamber.core.configuration.configuration_option import ConfigurationOption
from driftchamber.core.configuration.configuration_option_validation import ConfigurationOptionValidation
configuration_specification = {
'Detector': [
ConfigurationOption('nSuperLayers',
'The number of super layers.',
int,
[ConfigurationOptionValidation(
lambda value: value > 0,
'The number of super layers has to be a positive integer.'
)],
p_isCompulsory=True),
ConfigurationOption('nLayersList',
'List of layers per super layer.',
lambda value: literal_eval(value),
[ConfigurationOptionValidation(
lambda value: isinstance(value, list),
"'layers' has to be a list that can be parsed by python."),
ConfigurationOptionValidation(
lambda value: all(isinstance(nLayer, int) for nLayer in value),
"The amount of layers per super layer must be an integer."),
ConfigurationOptionValidation(
lambda value: all(nLayer > 0 for nLayer in value),
"The amount of layers per super layer must be a positive integer.")
],
p_isCompulsory=True),