umami.calculations.residual.joint_density_misfit module

joint_density_misfit(model_grid, data_grid, field_1, field_2, field_1_percentile_edges, field_2_percentile_edges)

Calculate the joint-density misfit on a Landlab grid field.

Density bounds are calculated with the data grid.

Parameters

• model_grid (Landlab model grid) –

• data_grid (Landlab model grid) –

• field_1 (str) – An at-node Landlab grid field that is present on the model grid.

• field_2 (str) – An at-node Landlab grid field that is present on the model grid.

• field_1_percentile_edges (list) – A list of percentile edges applied to field_1. For example, [0, 60, 100] specifies splitting field_1 into two parts, separated at the 60th percentile.

• field_2_percentile_edges (list) – A list of percentile edges applied to field_2. For example, [0, 60, 100] specifies splitting field_2 into two parts, separated at the 60th percentile.

Returns

out – The misfit

Return type

float

Examples

First an example that only uses the joint_density_misfit function.

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from umami.calculations import joint_density_misfit
>>> np.random.seed(42)
>>> model = RasterModelGrid((10, 10))
>>> z_model = model.add_zeros("node", "topographic__elevation")
>>> z_model += model.x_of_node + model.y_of_node
>>> data = RasterModelGrid((10, 10))
>>> z_data = data.add_zeros("node", "topographic__elevation")
>>> z_data +=  data.x_of_node + data.y_of_node
>>> z_data[data.core_nodes] += np.random.random(data.core_nodes.shape)
>>> data_fa = FlowAccumulator(data)
>>> data_fa.run_one_step()
>>> model_fa = FlowAccumulator(model)
>>> model_fa.run_one_step()
>>> np.isclose(
...     joint_density_misfit(
...         model,
...         data,
...         "topographic__elevation",
...         "drainage_area",
...         [0, 25, 50, 75, 100],
...         [0, 20, 40, 60, 80, 100]),
...         0.056599, atol=1e-03)
True

Next, the same calculations are shown as part of an umami Residual.

>>> from io import StringIO
>>> from umami import Residual
>>> file_like=StringIO('''
... jdm:
...     _func: joint_density_misfit
...     field_1: topographic__elevation
...     field_2: drainage_area
...     field_1_percentile_edges:
...         - 0
...         - 25
...         - 50
...         - 75
...         - 100
...     field_2_percentile_edges:
...         - 0
...         - 20
...         - 40
...         - 60
...         - 80
...         - 100
... ''')
>>> residual = Residual(model, data)
>>> residual.add_from_file(file_like)
>>> residual.names
['jdm']
>>> residual.calculate()
>>> np.round(residual.values, decimals=3)
array([ 0.057])