def network(
trace_file: Path = typer.Argument(...,
exists=True,
dir_okay=False,
help=TRACE_FILE_HELP),
area_file: Path = typer.Argument(...,
exists=True,
dir_okay=False,
help=AREA_FILE_HELP),
snap_threshold: float = typer.Option(0.001, help=SNAP_THRESHOLD_HELP),
determine_branches_nodes: bool = typer.Option(
True,
help=
"Whether to determine branches and nodes as part of analysis. Recommended.",
),
name: Optional[str] = typer.Option(
None,
help="Name for Network. Used when saving outputs and as plot titles."),
circular_target_area: bool = typer.Option(
False, help="Is/are target area(s) circles?"),
truncate_traces: bool = typer.Option(
True,
help="Whether to cut traces at target area boundary. Recommended."),
censoring_area: Optional[Path] = typer.Option(
None,
help=
"Path to area data that delineates censored areas within target areas.",
),
branches_output: Optional[Path] = typer.Option(
None, help="Where to save branch data."),
nodes_output: Optional[Path] = typer.Option(
None, help="Where to save node data."),
general_output: Optional[Path] = typer.Option(
None,
help="Where to save general network analysis outputs e.g. plots."),
parameters_output: Optional[Path] = typer.Option(
None, help="Where to save numerical parameter data from analysis."),
):
"""
Analyze the geometry and topology of trace network.
"""
network_name = name if name is not None else area_file.stem
console = Console()
console.print(
Text.assemble("Performing network analysis of ",
(network_name, "bold green"), "."))
network = Network(
trace_gdf=read_geofile(trace_file),
area_gdf=read_geofile(area_file),
snap_threshold=snap_threshold,
determine_branches_nodes=determine_branches_nodes,
name=network_name,
circular_target_area=circular_target_area,
truncate_traces=truncate_traces,
censoring_area=read_geofile(censoring_area)
if censoring_area is not None else gpd.GeoDataFrame(),
)
(
general_output_path,
branches_output_path,
nodes_output_path,
parameters_output_path,
) = default_network_output_paths(
network_name=network_name,
general_output=general_output,
branches_output=branches_output,
nodes_output=nodes_output,
parameters_output=parameters_output,
)
# Save branches and nodes
console.print(
Text.assemble(
"Saving branches to ",
(str(branches_output_path), "bold green"),
" and nodes to ",
(str(nodes_output_path), "bold green"),
".",
))
network.branch_gdf.to_file(branches_output_path, driver="GPKG")
network.node_gdf.to_file(nodes_output_path, driver="GPKG")
console.print(rich_table_from_parameters(network.parameters))
pd.DataFrame([network.numerical_network_description()
]).to_csv(parameters_output_path)
console.print(
Text.assemble(
"Saving extensive network parameter csv to path:\n",
(str(parameters_output_path), "bold green"),
))
# Plot ternary XYI-node proportion plot
fig, _, _ = network.plot_xyi()
save_fig(fig=fig, results_dir=general_output_path, name="xyi_ternary_plot")
# Plot ternary branch proportion plot
fig, _, _ = network.plot_branch()
save_fig(fig=fig,
results_dir=general_output_path,
name="branch_ternary_plot")
# Plot trace azimuth rose plot
_, fig, _ = network.plot_trace_azimuth()
save_fig(fig=fig, results_dir=general_output_path, name="trace_azimuth")
# Plot trace length distribution plot
_, fig, _ = network.plot_trace_lengths()
save_fig(fig=fig,
results_dir=general_output_path,
name="trace_length_distribution")
def network_extensive_testing(
network: Network,
traces: gpd.GeoDataFrame,
area: gpd.GeoDataFrame,
snap_threshold: float,
):
"""
Test Network attributes extensively.
"""
# Test resetting
copy_trace_gdf = network.trace_data._line_gdf.copy()
copy_branch_gdf = network.branch_data._line_gdf.copy()
# Test resetting
network.reset_length_data()
assert_frame_equal(copy_trace_gdf, network.trace_data._line_gdf)
assert_frame_equal(copy_branch_gdf, network.branch_data._line_gdf)
network_anisotropy = network.anisotropy
assert isinstance(network_anisotropy, tuple)
assert isinstance(network_anisotropy[0], np.ndarray)
assert isinstance(network.trace_length_set_array, np.ndarray)
assert isinstance(network.branch_length_set_array, np.ndarray)
# Test passing old branch and node data
branch_copy = network.branch_gdf.copy()
network_test = Network(
trace_gdf=traces,
area_gdf=area,
name="teeest_with_old",
branch_gdf=branch_copy,
node_gdf=network.node_gdf.copy(),
determine_branches_nodes=False,
truncate_traces=True,
snap_threshold=snap_threshold,
)
assert_frame_equal(network_test.branch_gdf, branch_copy)
# Test plotting
fig_returns = network.plot_branch()
assert fig_returns is not None
fig, ax, tax = fig_returns
assert isinstance(fig, Figure)
assert isinstance(ax, Axes)
assert isinstance(tax, TernaryAxesSubplot)
plt.close("all")
# Test plotting
fig_returns = network.plot_xyi()
assert fig_returns is not None
fig, ax, tax = fig_returns
assert isinstance(fig, Figure)
assert isinstance(ax, Axes)
assert isinstance(tax, TernaryAxesSubplot)
plt.close("all")
for plot in (
"plot_parameters",
"plot_anisotropy",
"plot_trace_azimuth_set_count",
"plot_branch_azimuth_set_count",
"plot_trace_length_set_count",
"plot_branch_length_set_count",
"plot_trace_azimuth",
"plot_branch_azimuth",
"plot_trace_lengths",
"plot_branch_lengths",
"plot_trace_azimuth_set_lengths",
"plot_branch_azimuth_set_lengths",
):
# Test plotting
fig_returns = getattr(network, plot)()
assert fig_returns is not None
if len(fig_returns) == 2:
fig, ax = fig_returns
elif len(fig_returns) == 3 and "length" in plot:
other, fig, ax = fig_returns
if not isinstance(other, powerlaw.Fit):
# assume fits, figs, axes from plot_*_set_lengths
assert isinstance(other, list)
assert isinstance(other[0], powerlaw.Fit)
# Check just the first value of returns
assert len(other) == len(fig)
assert len(other) == len(ax)
assert len(other) == len(network.azimuth_set_names)
other, fig, ax = other[0], fig[0], ax[0]
elif len(fig_returns) == 3 and "azimuth" in plot:
other, fig, ax = fig_returns
assert isinstance(other, AzimuthBins)
else:
raise ValueError("Expected 3 max returns.")
assert isinstance(fig, Figure)
assert isinstance(ax, (Axes, PolarAxes))
plt.close("all")