def test_multinetwork_subsample(network_params, samples: int, min_radii: float):
"""
Test MultiNetwork.subsample.
"""
assert min_radii > 0.0
assert samples > 0
networks = [Network(**kwargs) for kwargs in network_params]
multi_network = MultiNetwork(networks=tuple(networks))
subsamples = multi_network.subsample(min_radii=min_radii, samples=samples)
assert isinstance(subsamples, list)
assert len(networks) * samples == len(subsamples)
for subsample in subsamples:
if subsample.error:
raise subsample.result
identifiers = [subsample.identifier for subsample in subsamples]
assert not any(subsample.error for subsample in subsamples)
for network in networks:
assert network.name in identifiers
gathered = subsampling.gather_subsample_descriptions(subsample_results=subsamples)
assert isinstance(gathered, list)
assert len(gathered) > 0
def multinetwork_plot_multi_length_distribution(
network_params,
using_branches=False,
automatic_cut_offs=True,
plot_truncated_data=True,
):
"""
Create and test multi_network plot_multi_length_distribution.
"""
# using_branches = False
# automatic_cut_offs = True
networks = [
Network(**kwargs, determine_branches_nodes=using_branches)
for kwargs in network_params
]
multi_network = MultiNetwork(networks=tuple(networks))
mld = multi_network.multi_length_distributions(using_branches=using_branches)
assert len(mld.distributions) == len(network_params)
mld, polyfit, fig, ax = multi_network.plot_multi_length_distribution(
using_branches=using_branches,
automatic_cut_offs=automatic_cut_offs,
plot_truncated_data=plot_truncated_data,
)
assert isinstance(mld, length_distributions.MultiLengthDistribution)
assert isinstance(polyfit, length_distributions.Polyfit)
assert isinstance(fig, Figure)
assert isinstance(ax, Axes)
return mld, fig, ax
def multinetwork_plot_multi_length_distribution(
network_params, using_branches=False, cut_distributions=True
):
"""
Create and test multi_network plot_multi_length_distribution.
"""
# using_branches = False
# cut_distributions = True
networks = [
Network(**kwargs, determine_branches_nodes=using_branches)
for kwargs in network_params
]
multi_network = MultiNetwork(networks=tuple(networks))
mld = multi_network.multi_length_distributions(
using_branches=using_branches, cut_distributions=cut_distributions
)
assert len(mld.distributions) == len(network_params)
mld, fig, ax = multi_network.plot_multi_length_distribution(
using_branches=using_branches, cut_distributions=cut_distributions
)
assert isinstance(mld, length_distributions.MultiLengthDistribution)
assert isinstance(fig, Figure)
assert isinstance(ax, Axes)
return mld, fig, ax
def test_multinetwork_methods(
network_params, using_branches, automatic_cut_offs, tmp_path: Path
):
"""
Test MultiNetwork methods generally.
"""
networks = [
Network(**params, determine_branches_nodes=using_branches)
for params in network_params
]
multi_network = MultiNetwork(tuple(networks))
mlds, polyfits, figs, axes = multi_network._plot_azimuth_set_lengths(
automatic_cut_offs=automatic_cut_offs,
using_branches=using_branches,
plot_truncated_data=True,
)
for name, fig in zip(mlds, figs):
output_path = general.save_fig(fig=fig, results_dir=tmp_path, name=name)
logging.info(f"Saved plot to {output_path}.")
assert isinstance(mlds, dict)
assert isinstance(polyfits, list)
assert isinstance(figs, list)
assert isinstance(axes, list)
assert isinstance(figs[0], Figure)
assert isinstance(axes[0], Axes)
assert isinstance(polyfits[0], length_distributions.Polyfit)
# Test basic_network_descriptions_df
if not using_branches:
return
connection_frequency_new = "C FREQ"
columns = {
general.NAME: (None, str),
general.Param.AREA.value.name: (None, float),
general.Param.TRACE_MEAN_LENGTH.value.name: (None, float),
general.Param.BRANCH_MEAN_LENGTH.value.name: (None, float),
general.Param.FRACTURE_INTENSITY_P21.value.name: (None, float),
general.Param.CONNECTION_FREQUENCY.value.name: (
connection_frequency_new,
float,
),
}
basic_network_descriptions_df = multi_network.basic_network_descriptions_df(
columns=columns
)
assert isinstance(basic_network_descriptions_df, pd.DataFrame)
assert general.NAME not in basic_network_descriptions_df.index.values
assert general.Param.AREA.value.name in basic_network_descriptions_df.index.values
# Test renaming
for old_column, (new_column, _) in columns.items():
if new_column is not None:
assert new_column in basic_network_descriptions_df.index.values
assert old_column not in basic_network_descriptions_df.index.values
def test_multinetwork_plot_azimuth_set_lengths(
network_params, using_branches, cut_distributions, tmp_path: Path
):
"""
Test MultiNetwork._plot_azimuth_set_lengths.
"""
networks = [
Network(**params, determine_branches_nodes=using_branches)
for params in network_params
]
multi_network = MultiNetwork(tuple(networks))
mlds, figs, axes = multi_network._plot_azimuth_set_lengths(
cut_distributions=cut_distributions, using_branches=using_branches
)
for name, fig in zip(mlds, figs):
output_path = general.save_fig(fig=fig, results_dir=tmp_path, name=name)
logging.info(f"Saved plot to {output_path}.")
assert isinstance(mlds, dict)
assert isinstance(figs, list)
assert isinstance(axes, list)
assert isinstance(figs[0], Figure)
assert isinstance(axes[0], Axes)
def perf_profile(
do_validation: bool = True,
do_network: bool = True,
do_grid: bool = True,
do_subsampling: bool = False,
):
"""
Profile ``fractopo`` performance.
"""
if not all(path.exists()
for path in (SAMPLE_TRACES_PATH, SAMPLE_AREA_PATH)):
logging.error(f"Current path: {Path.cwd().resolve()}")
raise FileNotFoundError("Expected sample to exist at:"
f" {(SAMPLE_TRACES_PATH, SAMPLE_AREA_PATH)}")
traces = read_geofile(SAMPLE_TRACES_PATH)
area = read_geofile(SAMPLE_AREA_PATH)
name = SAMPLE_AREA_PATH.stem
snap_threshold = 0.001
if do_validation:
validator = Validation(
traces=traces,
area=area,
SNAP_THRESHOLD=snap_threshold,
name=name,
allow_fix=True,
)
validator.run_validation()
if do_network:
network = Network(
trace_gdf=traces,
area_gdf=area,
snap_threshold=snap_threshold,
name=name,
circular_target_area=True,
truncate_traces=True,
determine_branches_nodes=True,
)
network.numerical_network_description()
if do_grid:
network.contour_grid(cell_width=2.0)
if do_subsampling:
multi_network = MultiNetwork((network, ))
multi_network.subsample(min_radii=5.0, samples=5)
def test_multinetwork_plot_ternary(network_params, tmp_path):
"""
Test MultiNetwork.plot_xyi and plot_branch.
"""
networks = [
Network(**params, determine_branches_nodes=True) for params in network_params
]
multi_network = MultiNetwork(tuple(networks))
for plot_func in ("plot_xyi", "plot_branch"):
fig, ax, tax = getattr(multi_network, plot_func)()
assert isinstance(fig, Figure)
assert isinstance(ax, Axes)
assert isinstance(tax, TernaryAxesSubplot)
tmp_path = Path(tmp_path)
tmp_path.mkdir(exist_ok=True)
plot_path = tmp_path / f"{plot_func}.png"
fig.savefig(plot_path, bbox_inches="tight")
logging.info(f"Saved {plot_func} plot to {plot_path.absolute()}.")
# Note that azimuth sets are explicitly set here for both networks. They are
# user-defined though the Network will use default azimuth sets if not set by
# the user.
import geopandas as gpd
from fractopo import Network
kb11_network = Network(
name="KB11",
trace_gdf=gpd.read_file(
"https://raw.githubusercontent.com/nialov/"
"fractopo/master/tests/sample_data/KB11/KB11_traces.geojson"),
area_gdf=gpd.read_file(
"https://raw.githubusercontent.com/nialov/"
"fractopo/master/tests/sample_data/KB11/KB11_area.geojson"),
truncate_traces=True,
circular_target_area=False,
determine_branches_nodes=True,
snap_threshold=0.001,
# Explicitly set azimuth sets
azimuth_set_names=("N-S", "E-W"),
azimuth_set_ranges=((135, 45), (45, 135)),
)
hastholmen_network = Network(
name="Hastholmen",
trace_gdf=gpd.read_file(
"https://raw.githubusercontent.com/nialov/"
"fractopo/master/tests/sample_data/hastholmen_traces_validated.geojson"
),
area_gdf=gpd.read_file(
# Load kb11_network network from examples/example_networks.py
from example_networks import kb11_network
# Import Network class from fractopo
from fractopo import Network
from fractopo.analysis.parameters import plot_parameters_plot
# Make kb7_network here
kb7_network = Network(
name="KB7",
trace_gdf=gpd.read_file(
"https://raw.githubusercontent.com/nialov/"
"fractopo/master/tests/sample_data/KB7/KB7_traces.geojson"),
area_gdf=gpd.read_file(
"https://raw.githubusercontent.com/nialov/"
"fractopo/master/tests/sample_data/KB7/KB7_area.geojson"),
truncate_traces=True,
circular_target_area=False,
determine_branches_nodes=True,
snap_threshold=0.001,
)
# %%
# Geometric and topological Network parameters
# --------------------------------------------
#
# All parameters are accessible through an attribute
kb11_parameters = kb11_network.parameters
kb7_parameters = kb7_network.parameters