def __init__(self, setting: RIDTConfig, data_store: DataStore,
dir_agent: DirectoryAgent, quantity: str):
"""The :class:`DataStoreCSVWriter` constructor.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
dir_agent : :class:`~.DirectoryAgent`
The path to the output directory for the run.
data_store : :class:`~.DataStore`
The data store to be analysed.
quantity: :obj:`str`
The string id for the quantity stored in the data store.
"""
self.dir_agent = dir_agent
self.setting = setting
self.units = Units(setting)
self.domain = Domain(setting)
self.quantity = quantity
self.write(data_store)
def setUp(self) -> None:
this_dir = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(this_dir, "../../default/config.json")
with open(path) as f:
loaded_json = json.load(f)
self.config = RIDTConfig(loaded_json)
self.domain = Domain(self.config)
def __init__(self, setting: RIDTConfig):
"""The :class:`~.UncertaintyMask` constructor.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run.
"""
self.setting = setting
self.radius = setting.models.eddy_diffusion.analysis.exclude_radius_meters
self.sources = self.get_source_locations()
self.domain = Domain(setting)
def __init__(self, setting: RIDTConfig, space: ComputationalSpace,
analysis: Dict[RIDTConfig, DataStoreAnalyser], outdir: str,
quantity: str):
"""The :class`~.BatchResultsWriter` class initialiser.
Parameters
----------
setting : :class:`~.RIDTConfig`
The settings for the run in question.
space : :class:`~.ComputationalSpace`
The :class:`~.ComputationalSpace` instance corresponding to the
:attr:`settings` attribute.
analysis : :obj:`dict` [:class:`~.RIDTConfig`, :class:`~.DataStoreAnalyser`]
A dictionary of :class:`~.DataStoreAnalyser` instances for each
:class:`~.RIDTConfig` object in :attr:`space`.
outdir : :obj:`str`
The path to the output directory for the run.
quantity : :obj:`str`
The string id for the quantity stored in the data store.
"""
self.setting = setting
self.domain = Domain(setting)
self.units = Units(setting)
self.quantity = quantity
self.thresholds = self.threshold_converter()
self.space = space
self.analysis = analysis
self.outdir = outdir
self.summary()
self.write()
def __init__(self,
setting: RIDTConfig,
analysis: DataStoreAnalyser,
dir_agent: DirectoryAgent,
quantity: str):
"""The :class`~.ResultsWriter` class initialiser.
Parameters
----------
setting : :class:`~.RIDTConfig`
The settings for the run in question.
analysis : :class:`~.DataStoreAnalyser`
:class:`~.DataStoreAnalyser` instance to be written.
dir_agent: :class:`~.DirectoryAgent`
The directory agent for run.
quantity : :obj:`str`
The string id for the quantity stored in the data store.
"""
self.setting = setting
self.units = Units(setting)
self.quantity = quantity
self.thresholds = self.threshold_converter()
self.analysis = analysis
self.dir_agent = dir_agent
self.domain = Domain(setting)
if quantity == "concentration":
self.summary()
self.maximum()
self.exceedance_analysis()
self.extrema()
def run(self, setting: RIDTConfig) -> None:
"""Evaluates the model for a set of parameters, for all geometries.
Loops over all monitor locations that have been selected for evaluation
and evaluates them over their respective domains. Writes output to
:attr:`data_store`.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
Returns
-------
None
"""
self.data_store.add_run(setting)
domain = Domain(setting)
solver = EddyDiffusion(setting)
locations = setting.models.eddy_diffusion.monitor_locations
for geometry in self.geometries:
print(f"Evaluating {geometry} monitor locations...")
for name, item in getattr(locations, geometry).items():
print(f"Evaluating {name}...")
space = getattr(domain, geometry)(item)
output = solver(*getattr(domain, geometry)(item), domain.time)
self.data_store[setting].add(geometry, name, squeeze(output))
def __init__(self, setting: RIDTConfig, geometry: str, id: str,
quantity: str):
self.setting = setting
self.geometry = geometry
self.id = id
self.quantity = quantity
self.units = Units(setting)
self.domain = Domain(setting)
def setUp(self) -> None:
this_dir = os.path.dirname(os.path.abspath(__file__))
with ConfigFileParser(join(this_dir, "st23/config.json")) as cfp:
self.c = cfp
self.bds = BatchDataStore()
self.domain = Domain(self.c)
self.output_dir = join(this_dir, "st23/data")
Path(self.output_dir).mkdir(parents=True, exist_ok=True)
self.edr = EddyDiffusionRun(self.c, self.output_dir)
class TestDomain(unittest.TestCase):
def setUp(self) -> None:
this_dir = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(this_dir, "../../default/config.json")
with open(path) as f:
loaded_json = json.load(f)
self.config = RIDTConfig(loaded_json)
self.domain = Domain(self.config)
def test_point(self):
"""Tests to make sure that the types of the points
are arrays."""
points = self.config.models.eddy_diffusion.monitor_locations.points
for point in points.values():
for array in self.domain.points(point):
self.assertEqual(type(array), np.ndarray)
def test_line(self):
"""Tests to make sure that the types of the lines
are arrays."""
lines = self.config.models.eddy_diffusion.monitor_locations.lines
for line in lines.values():
for array in self.domain.lines(line):
self.assertEqual(type(array), np.ndarray)
def test_plane(self):
"""Tests to make sure that the types of the planes
are arrays."""
planes = self.config.models.eddy_diffusion.monitor_locations.planes
for plane in planes.values():
for array in self.domain.planes(plane):
self.assertEqual(type(array), np.ndarray)
def run(self, setting: RIDTConfig) -> None:
"""Evaluates the model for a set of parameters.
Writes output to :attr:`data_store`.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
Returns
-------
None
"""
self.data_store.add_run(setting)
domain = Domain(setting)
solver = WellMixed(setting)
output = solver(domain.time)
self.data_store[setting].add("points", "well_mixed", output)
def __init__(self, settings: RIDTConfig, output_dir: str, quantity: str):
"""The :class:`~.ContourPlot` constructor.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
outdir : :obj:`str`
The path to the output directory for the run.
quantity : :obj:`str`
The string id for the quantity stored in the data store.
"""
self.settings = settings
self.output_dir = output_dir
self.units = Units(settings)
self.domain = Domain(self.settings)
self.quantity = quantity
self.config = self.settings.models.eddy_diffusion.planes_plots
def __init__(self, setting: RIDTConfig, data_store: DataStore,
quantity: str):
"""The :class`~.DataStoreAnalyser` class initialiser.
Calls the :meth:`~.DataStoreAnalyser.evaluate` method.
If flag is set in config file, will exclude values within 2m of all
sources.
Parameters
----------
setting : :class:`~.RIDTConfig`
The settings for the run in question.
data_store : :class:`~.DataStore`
The data store to be analysed.
quantity : :obj:`str`
The string id for the quantity stored in the data store.
"""
self.setting = setting
self.units = Units(setting)
self.domain = Domain(self.setting)
self.quantity = quantity
self.thresholds = self.threshold_converter()
self.data_store = data_store
if self.setting.models.eddy_diffusion.analysis.exclude_uncertain_values:
self.exclude_uncertain_values()
self.maximum = list()
self.exceedance = list()
self.percent_exceedance = list()
self.max_percent_exceedance = list()
self.evaluate()
class UncertaintyMask:
"""Provides the ability to mask uncertain values in quantity grids.
Attributes
----------
settings : :class:`~.RIDTConfig`
The settings for the run.
sources : :obj:`List`[:class:`~numpy.ndarray`]
The list of source term positions found in the settings instance.
domain : :class:`~.Domain`
The instance of :class:`~.Domain` corresponding to :attr:`settings`.
radius : :obj:`float`
The radius of the sphere around each source, inside which values will be
masked.
"""
def __init__(self, setting: RIDTConfig):
"""The :class:`~.UncertaintyMask` constructor.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run.
"""
self.setting = setting
self.radius = setting.models.eddy_diffusion.analysis.exclude_radius_meters
self.sources = self.get_source_locations()
self.domain = Domain(setting)
def get_source_locations(self):
"""Get the source settings objects from the run settings instance.
Returns
-------
:obj:`List`[:class:`~numpy.ndarray`]
The list of source term positions found in the settings instance.
"""
rv = list()
modes = ["instantaneous", "infinite_duration", "fixed_duration"]
for mode in modes:
sources = getattr(self.setting.modes, mode).sources
rv += [array((s.x, s.y, s.z)) for s in sources.values()]
return rv
def mask(self, geometry: str, id: str, data: ndarray):
"""Masks all elements in the grid that are within 2m of a source.
Parameters
----------
geometry : :obj:`str`
The type of grid to be masked.
id : :obj:`str`
The id of the grid to be masked.
data : :class:`~ndarray.ndarray`
The grid to be masked.
Returns
-------
:class:`~numpy.ndarray`
The masked array.
"""
print(f"Excluding uncertain values in {id}...")
return getattr(self, f"mask_{geometry}")(id, data)
def mask_points(self, id: str, data: ndarray):
"""Mask values in point array close to a source.
Parameters
----------
id : :obj:`str`
The id of the point.
data : :class:`~.numpy.ndarray`
The array to be masked.
Returns
-------
:class:`~.numpy.ndarray`
The masked copy.
"""
point = self.setting.models.eddy_diffusion.monitor_locations.points[id]
location = self.domain.point_cartesian(point)
rv = deepcopy(data)
for s in self.sources:
if norm(s - location) <= self.radius:
rv.fill(nan)
return rv
def mask_lines(self, id: str, data: ndarray):
"""Mask values in line array close to a source.
Parameters
----------
id : :obj:`str`
The id of the line.
data : :class:`~.numpy.ndarray`
The array to be masked.
Returns
-------
:class:`~.numpy.ndarray`
The masked copy.
"""
line = self.setting.models.eddy_diffusion.monitor_locations.lines[id]
locations = self.domain.line_cartesian(line)
rv = deepcopy(data)
for idx, location in locations:
for s in self.sources:
if norm(s - array(location)) <= self.radius:
for idt, time in enumerate(self.domain.time):
rv[idt][idx] = nan
return rv
def mask_planes(self, id: str, data: ndarray):
"""Mask values in plane array close to a source.
Parameters
----------
id : :obj:`str`
The id of the plane.
data : :class:`~.numpy.ndarray`
The array to be masked.
Returns
-------
:class:`~.numpy.ndarray`
The masked copy.
"""
plane = self.setting.models.eddy_diffusion.monitor_locations.planes[id]
locations = self.domain.plane_cartesian(plane)
rv = deepcopy(data)
for idx, location in locations:
for s in self.sources:
if norm(s - array(location)) <= self.radius:
for idt, time in enumerate(self.domain.time):
rv[idt][idx] = nan
return rv
def mask_domain(self, id: str, data: ndarray):
"""Mask values in domain array close to a source.
Note
----
The `id` parameter is a placeholder for future functionality, where
multiple domains can be defined.
Parameters
----------
id : :obj:`str`
The id of the domain.
data : :class:`~.numpy.ndarray`
The array to be masked.
Returns
-------
:class:`~.numpy.ndarray`
The masked copy.
"""
locations = self.domain.domain_cartesian()
rv = deepcopy(data)
for idx, location in locations:
for s in self.sources:
if norm(s - array(location)) <= self.radius:
for idt, time in enumerate(self.domain.time):
rv[idt][idx] = nan
return rv
class DataStoreCSVWriter:
"""Class that writes a :class:`~.DataStore` instance to CSV files.
Attributes
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
dir_agent : :class:`~.DirectoryAgent`
The path to the output directory for the run.
domain : :class:`~.Domain`
The instance of :class:`~.Domain` corresponding to :attr:`setting`.
units : :class:`~.Units`
The instance of :class:`~.Units` corresponding to :attr:`setting`.
data_store : :class:`~.DataStore`
The data store to be analysed.
quantity: :obj:`str`
The string id for the quantity stored in the data store.
"""
def __init__(self, setting: RIDTConfig, data_store: DataStore,
dir_agent: DirectoryAgent, quantity: str):
"""The :class:`DataStoreCSVWriter` constructor.
Parameters
----------
settings : :class:`~.RIDTConfig`
The settings for the run in question.
dir_agent : :class:`~.DirectoryAgent`
The path to the output directory for the run.
data_store : :class:`~.DataStore`
The data store to be analysed.
quantity: :obj:`str`
The string id for the quantity stored in the data store.
"""
self.dir_agent = dir_agent
self.setting = setting
self.units = Units(setting)
self.domain = Domain(setting)
self.quantity = quantity
self.write(data_store)
@property
def geometries(self):
""":obj:`list` [:obj:`str`] : the list of geometries selected for
evaluation in :attr:`settings`.
"""
locations = self.setting.models.eddy_diffusion.monitor_locations
return [g for g, e in locations.evaluate.items() if e]
def write(self, data_store: DataStore) -> None:
"""Loops over entries in the data store and writes the data to csv file.
Parameters
----------
data_store : :class:`~.DataStore`
The data store to be analysed.
Returns
-------
None
"""
for geometry in self.geometries:
self.dir_agent.create_data_dir(geometry, self.quantity)
for id in getattr(data_store, geometry):
self.write_csv(geometry, id, data_store.get(geometry, id))
def write_csv(self, geometry: str, id: str, data: ndarray) -> None:
"""Takes string identifiers and the grid and writes them to a csv file.
Parameters
----------
geometry : :obj:`str`
The type of grid to be written.
id : :obj:`str`
The id of the grid to be written.
data : :class:`~numpy.ndarray`
The grid to be written.
Raises
------
:class:`~.RIDTOSError`
If unable to create the file on disk.
Returns
-------
None
"""
path = join(self.dir_agent.ddir, id + ".csv")
factor = getattr(self.units, f"{self.quantity}_factor")
try:
f = open(path, 'w', newline="")
except OSError as e:
raise RIDTOSError(e)
writer = csv.writer(f, delimiter=",")
writer.writerow([
f"time ({self.units.time})", f"x ({self.units.space})",
f"y ({self.units.space})", f"z ({self.units.space})",
f"value ({getattr(self.units, f'{self.quantity}')})"
])
indices = list(product(*[range(i) for i in data.shape]))
print(f"Writing {id} {self.quantity} data to a csv file...")
for index in tqdm(indices, total=len(indices), **bar_args):
values = self.domain.values(id, index)
writer.writerow(list(values) + [data[index] / factor])
f.close()
