landlab.utils.channel_network_grid_tools¶
- choose_from_repeated(sorted_array, choose='last')[source]¶
Mark the first/last element of repeated values in a sorted 1-D array.
- Parameters:
sorted_array (array_like) – Assumed sorted by the grouping key.
choose ({'first','last'}, optional) – Whether to mark the first or last item of each run.
- Return type:
Examples
>>> array = [0, 0, 0, 2, 2, 5, 6, 6, 6, 6, 6] >>> is_last = choose_from_repeated(array, choose="last") >>> is_last.astype(int) array([0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1])
- choose_unique(values, order_by=None, choose='last')[source]¶
Find indices of unique values, selecting one representative if repeated.
Examples
>>> choose_unique([0, 1, 0, 0, 1], order_by=([10.0, 11.0, 12.0, 13.0, 14],)) array([3, 4])
>>> choose_unique([1, 0, 0, 1, 0], order_by=([10.0, 11.0, 12.0, 13.0, 14],)) array([3, 4])
- extract_channel_nodes(grid, Ct)[source]¶
interpret which nodes of the DEM represent the channel network as all nodes that have a drainage area >= to the average drainage area at which channels initiate in the DEM (Ct, based on field or remote sensing evidence).
Use Ct = average drainage area at which colluvial channels to get the entire channel network.
Use Ct = the drainage area at which cascade channels typically begin to get a channel network where sediment transport is primarily via fluvial processes
- extract_terrace_nodes(grid, terrace_width, acn, fcn)[source]¶
Determine which raster model grid nodes coincide with channel terraces, which presently are assumed to be a fixed width (number of nodes) from the channel nodes
- Parameters:
grid (raster model grid)
terrace_width (int) – Width of terrace in number of nodes. If provided as float, will be rounded to nearest int.
acn (np array) – array of all node IDs included in the channel network
fcn (np array) – array of all node IDs included in the fluvial channel network
- Raises:
ValueError – Occurs if terrace width less than 1.
- Returns:
terrace_nodes – array of all node IDs included in the terrace
- Return type:
np array
- get_link_nodes(nmgrid)[source]¶
Get the downstream (head) and upstream (tail) nodes at a link from flow director. The network model grid nodes_at_link attribute may not be ordered according to flow direction. Output from this function should be used for all channel_network_grid_tools functions that require a link_nodes input
- Parameters:
nmgrid (network model grid)
- Returns:
link_nodes – for a nmgrid of n nodes, returns a nx2 np array, the ith row of the array is the [downstream node id, upstream node id] of the ith link
- Return type:
np.array
- map_nmg_links_to_rmg_coincident_nodes(grid, nmgrid, link_nodes, remove_duplicates=False)[source]¶
Map links of a network model grid to all coincident raster model grid nodes. Each coincident raster model grid node is defined in terms of its x and y coordinates, the link it is mapped to and distance downstream from the upstream (tail) end of the link.
- Parameters:
grid (raster model grid)
nmgrid (network model grid)
link_nodes (np array) – head and tail node of each link
remove_duplicates (bool) – if True, when two or more links are coincident with the same node, the node is assigned to the link with the largest drainage area. If False, the node is assigned to each coincident link. The default is False.
- Returns:
nmg_link_to_rmg_coincident_nodes_mapper – each row of the dataframe lists the link ID, the coincident node ID, the x and y coordinates and the downstream distance of the coincident node and the drainage area of the link
- Return type:
pandas dataframe
- min_distance_to_network(grid, acn, node_id)[source]¶
Determine the shortest distance (as the crow flies) from a node to the channel network and the closest channel node
- Parameters:
- Returns:
offset (float) – distance between node and channel network
mdn (int) – ID of channel node that is closest node