def calc_grad_at_link(grid, node_values, out=None):
"""Calculate gradients in node_values at links.
Construction::
calc_grad_at_link(grid, node_values, out=None)
Parameters
----------
grid : RasterModelGrid
A grid.
node_values : array_like or field name
Values at nodes.
out : ndarray, optional
Buffer to hold result. If `None`, create a new array.
Returns
-------
ndarray
Gradients of the nodes values for each link.
Examples
--------
>>> from landlab import RasterModelGrid
>>> grid = RasterModelGrid((3, 3))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_link(node_values)
array([ 0., 0., 1., 3., 1., 2., -2., 1., -1., 1., 0., 0.])
>>> out = np.empty(grid.number_of_links, dtype=float)
>>> rtn = grid.calc_grad_at_link(node_values, out=out)
>>> rtn is out
True
>>> out
array([ 0., 0., 1., 3., 1., 2., -2., 1., -1., 1., 0., 0.])
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> grid.calc_grad_at_link(node_values)
array([ 0., 0., 1., 3., 1., 1., -1., 1., -1., 1., 0., 0.])
>>> _ = grid.add_field('node', 'elevation', node_values)
>>> grid.calc_grad_at_link('elevation')
array([ 0., 0., 1., 3., 1., 1., -1., 1., -1., 1., 0., 0.])
LLCATS: LINF GRAD
"""
grads = gradients.calc_diff_at_link(grid, node_values, out=out)
grads /= grid.length_of_link[:grid.number_of_links]
# n_vertical_links = (grid.shape[0] - 1) * grid.shape[1]
# diffs[:n_vertical_links] /= grid.dy
# diffs[n_vertical_links:] /= grid.dx
return grads
def calc_grad_at_link(grid, node_values, out=None):
"""Calculate gradients in node_values at links.
Construction::
calc_grad_at_link(grid, node_values, out=None)
Parameters
----------
grid : RasterModelGrid
A grid.
node_values : array_like or field name
Values at nodes.
out : ndarray, optional
Buffer to hold result. If `None`, create a new array.
Returns
-------
ndarray
Gradients of the nodes values for each link.
Examples
--------
>>> from landlab import RasterModelGrid
>>> grid = RasterModelGrid((3, 3))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_link(node_values)
array([ 0., 0., 1., 3., 1., 2., -2., 1., -1., 1., 0., 0.])
>>> out = np.empty(grid.number_of_links, dtype=float)
>>> rtn = grid.calc_grad_at_link(node_values, out=out)
>>> rtn is out
True
>>> out
array([ 0., 0., 1., 3., 1., 2., -2., 1., -1., 1., 0., 0.])
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> grid.calc_grad_at_link(node_values)
array([ 0., 0., 1., 3., 1., 1., -1., 1., -1., 1., 0., 0.])
>>> _ = grid.add_field('node', 'elevation', node_values)
>>> grid.calc_grad_at_link('elevation')
array([ 0., 0., 1., 3., 1., 1., -1., 1., -1., 1., 0., 0.])
"""
grads = gradients.calc_diff_at_link(grid, node_values, out=out)
grads /= grid.length_of_link[:grid.number_of_links]
# n_vertical_links = (grid.shape[0] - 1) * grid.shape[1]
# diffs[:n_vertical_links] /= grid.dy
# diffs[n_vertical_links:] /= grid.dx
return grads
def calc_grad_at_active_link(grid, node_values, out=None):
"""Calculate gradients over active links.
.. deprecated:: 0.1
Use :func:`calc_grad_across_cell_faces`
or :func:`calc_grad_across_cell_corners` instead
Calculates the gradient in quantity s at each active link in the grid.
This is nearly identical to the method of the same name in ModelGrid,
except that it uses a constant node spacing for link length to improve
efficiency.
Note that a negative gradient corresponds to a lower node in the
direction of the link.
Returns
-------
ndarray
Gradients of the nodes values for each link.
Examples
--------
>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> grid = RasterModelGrid(4, 5, 1.0)
>>> u = [0., 1., 2., 3., 0.,
... 1., 2., 3., 2., 3.,
... 0., 1., 2., 1., 2.,
... 0., 0., 2., 2., 0.]
>>> grad = grid.calc_grad_at_active_link(u)
>>> grad # doctest: +NORMALIZE_WHITESPACE
array([ 1., 1., -1.,
1., 1., -1., 1.,
-1., -1., -1.,
1., 1., -1., 1.,
-1., 0., 1.])
For greater speed, sending a pre-created numpy array as an argument
avoids having to create a new one with each call:
>>> grad = np.empty(grid.number_of_active_links)
>>> rtn = grid.calc_grad_at_active_link(u, out=grad)
>>> grad # doctest: +NORMALIZE_WHITESPACE
array([ 1., 1., -1.,
1., 1., -1., 1.,
-1., -1., -1.,
1., 1., -1., 1.,
-1., 0., 1.])
>>> rtn is grad
True
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_active_link(node_values)
array([ 3., 1., -1., -1.])
This function is *deprecated*. Instead, use ``calc_grad_at_link``.
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_link(node_values)[grid.active_links]
array([ 3., 1., -1., -1.])
LLCATS: LINF GRAD
"""
if out is None:
out = grid.empty(at='active_link')
if len(out) != grid.number_of_active_links:
raise ValueError('output buffer does not match that of the grid.')
# grads = gradients.calculate_diff_at_active_links(grid, node_values,
# out=out)
grads = gradients.calc_diff_at_link(grid, node_values)
out[:] = grads[grid.active_links]
out /= grid.length_of_link[grid.active_links]
return out
def calc_grad_at_active_link(grid, node_values, out=None):
"""Calculate gradients over active links.
.. deprecated:: 0.1
Use :func:`calc_grad_across_cell_faces`
or :func:`calc_grad_across_cell_corners` instead
Calculates the gradient in quantity s at each active link in the grid.
This is nearly identical to the method of the same name in ModelGrid,
except that it uses a constant node spacing for link length to improve
efficiency.
Note that a negative gradient corresponds to a lower node in the
direction of the link.
Returns
-------
ndarray
Gradients of the nodes values for each link.
Examples
--------
>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> grid = RasterModelGrid(4, 5, 1.0)
>>> u = [0., 1., 2., 3., 0.,
... 1., 2., 3., 2., 3.,
... 0., 1., 2., 1., 2.,
... 0., 0., 2., 2., 0.]
>>> grad = grid.calc_grad_at_active_link(u)
>>> grad # doctest: +NORMALIZE_WHITESPACE
array([ 1., 1., -1.,
1., 1., -1., 1.,
-1., -1., -1.,
1., 1., -1., 1.,
-1., 0., 1.])
For greater speed, sending a pre-created numpy array as an argument
avoids having to create a new one with each call:
>>> grad = np.empty(grid.number_of_active_links)
>>> rtn = grid.calc_grad_at_active_link(u, out=grad)
>>> grad # doctest: +NORMALIZE_WHITESPACE
array([ 1., 1., -1.,
1., 1., -1., 1.,
-1., -1., -1.,
1., 1., -1., 1.,
-1., 0., 1.])
>>> rtn is grad
True
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_active_link(node_values)
array([ 3., 1., -1., -1.])
This function is *deprecated*. Instead, use ``calc_grad_at_link``.
>>> grid = RasterModelGrid((3, 3), spacing=(1, 2))
>>> node_values = [0., 0., 0.,
... 1., 3., 1.,
... 2., 2., 2.]
>>> grid.calc_grad_at_link(node_values)[grid.active_links]
array([ 3., 1., -1., -1.])
"""
if out is None:
out = grid.empty(at='active_link')
if len(out) != grid.number_of_active_links:
raise ValueError('output buffer does not match that of the grid.')
# grads = gradients.calculate_diff_at_active_links(grid, node_values,
# out=out)
grads = gradients.calc_diff_at_link(grid, node_values)
out[:] = grads[grid.active_links]
out /= grid.length_of_link[grid.active_links]
return out