bmi_topography package¶
Submodules¶
bmi_topography.api_key module¶
- class bmi_topography.api_key.ApiKey(api_key, source='user')[source]¶
Bases:
object
Store an API key to use when fetching topography data from OpenTopography.
- Parameters:
api_key (str) – An API key as a (non-empty) string.
source (str, optional) – A string that indicates where the key came from. Possible values are: user, env, file, and demo.
- Raises:
BadKeyError – The provided API key is invalid.
MissingKeyError – A key could not be found in the usual places.
BadApiKeySource – An invalid source was provided.
Examples
>>> from bmi_topography.api_key import ApiKey >>> api_key = ApiKey("foobar") >>> api_key ApiKey('foobar', source='user')
- API_KEY_ENV_VAR = 'OPENTOPOGRAPHY_API_KEY'¶
- API_KEY_FILES = ('.opentopography.txt', '~/.opentopography.txt')¶
- DEMO_API_KEY = 'demoapikeyot2022'¶
- property api_key¶
The API key.
- classmethod from_sources(api_key=None)[source]¶
Get a key from the first of a series of sources.
Look for a key from the following sources, returning the first found: (1) provided by a user through the api_key keyword, (2) provided by an environment variable, (3) provided in a text file, and (4) use a demo key
- property source¶
Where the API key came from.
bmi_topography.bbox module¶
- class bmi_topography.bbox.BoundingBox(lower_left: Tuple[float], upper_right: Tuple[float])[source]¶
Bases:
object
Represent a simple latitude-longitude bounding box.
Examples
Create a bounding box:
>>> from bmi_topography import BoundingBox >>> bbox = BoundingBox((33, 111), (44, 122)) >>> print(bbox) [(33, 111), (44, 122)]
- property east¶
- property lower_left¶
The southwest corner of the box, given by tuple of (south, west).
- property north¶
- property south¶
- property upper_right¶
The northeast corner of the box, given by tuple of (north, east).
- property west¶
bmi_topography.bmi module¶
- class bmi_topography.bmi.BmiGridUniformRectilinear(shape, yx_spacing, yx_of_lower_left)¶
Bases:
tuple
- shape¶
Alias for field number 0
- yx_of_lower_left¶
Alias for field number 2
- yx_spacing¶
Alias for field number 1
- class bmi_topography.bmi.BmiTopography[source]¶
Bases:
Bmi
BMI-mediated access to NASA SRTM land elevation data.
- finalize() None [source]¶
Perform tear-down tasks for the model.
Perform all tasks that take place after exiting the model’s time loop. This typically includes deallocating memory, closing files and printing reports.
- get_component_name() str [source]¶
Name of the component.
- Returns:
The name of the component.
- Return type:
str
- get_current_time() float [source]¶
Current time of the model.
- Returns:
The current model time.
- Return type:
float
- get_end_time() float [source]¶
End time of the model.
- Returns:
The maximum model time.
- Return type:
float
- get_grid_edge_count(grid: int) int [source]¶
Get the number of edges in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid edges.
- Return type:
int
- get_grid_edge_nodes(grid: int, edge_nodes: ndarray) ndarray [source]¶
Get the edge-node connectivity.
- Parameters:
grid (int) – A grid identifier.
edge_nodes (ndarray of int, shape (2 x nnodes,)) – A numpy array to place the edge-node connectivity. For each edge, connectivity is given as node at edge tail, followed by node at edge head.
- Returns:
The input numpy array that holds the edge-node connectivity.
- Return type:
ndarray of int
- get_grid_face_count(grid: int) int [source]¶
Get the number of faces in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid faces.
- Return type:
int
- get_grid_face_edges(grid: int, face_edges: ndarray) ndarray [source]¶
Get the face-edge connectivity.
- Parameters:
grid (int) – A grid identifier.
face_edges (ndarray of int) – A numpy array to place the face-edge connectivity.
- Returns:
The input numpy array that holds the face-edge connectivity.
- Return type:
ndarray of int
- get_grid_face_nodes(grid: int, face_nodes: ndarray) ndarray [source]¶
Get the face-node connectivity.
- Parameters:
grid (int) – A grid identifier.
face_nodes (ndarray of int) – A numpy array to place the face-node connectivity. For each face, the nodes (listed in a counter-clockwise direction) that form the boundary of the face.
- Returns:
The input numpy array that holds the face-node connectivity.
- Return type:
ndarray of int
- get_grid_node_count(grid: int) int [source]¶
Get the number of nodes in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid nodes.
- Return type:
int
- get_grid_nodes_per_face(grid: int, nodes_per_face: ndarray) ndarray [source]¶
Get the number of nodes for each face.
- Parameters:
grid (int) – A grid identifier.
nodes_per_face (ndarray of int, shape (nfaces,)) – A numpy array to place the number of edges per face.
- Returns:
The input numpy array that holds the number of nodes per edge.
- Return type:
ndarray of int
- get_grid_origin(grid: int, origin: ndarray) ndarray [source]¶
Get coordinates for the lower-left corner of the computational grid.
- Parameters:
grid (int) – A grid identifier.
origin (ndarray of float, shape (ndim,)) – A numpy array to hold the coordinates of the lower-left corner of the grid.
- Returns:
The input numpy array that holds the coordinates of the grid’s lower-left corner.
- Return type:
ndarray of float
- get_grid_rank(grid: int) int [source]¶
Get number of dimensions of the computational grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Rank of the grid.
- Return type:
int
- get_grid_shape(grid: int, shape: ndarray) ndarray [source]¶
Get dimensions of the computational grid.
- Parameters:
grid (int) – A grid identifier.
shape (ndarray of int, shape (ndim,)) – A numpy array into which to place the shape of the grid.
- Returns:
The input numpy array that holds the grid’s shape.
- Return type:
ndarray of int
- get_grid_size(grid: int) int [source]¶
Get the total number of elements in the computational grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Size of the grid.
- Return type:
int
- get_grid_spacing(grid: int, spacing: ndarray) ndarray [source]¶
Get distance between nodes of the computational grid.
- Parameters:
grid (int) – A grid identifier.
spacing (ndarray of float, shape (ndim,)) – A numpy array to hold the spacing between grid rows and columns.
- Returns:
The input numpy array that holds the grid’s spacing.
- Return type:
ndarray of float
- get_grid_type(grid: int) str [source]¶
Get the grid type as a string.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Type of grid as a string.
- Return type:
str
- get_grid_x(grid: int, x: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the x direction.
- Parameters:
grid (int) – A grid identifier.
x (ndarray of float, shape (nrows,)) – A numpy array to hold the x-coordinates of the grid node columns.
- Returns:
The input numpy array that holds the grid’s column x-coordinates.
- Return type:
ndarray of float
- get_grid_y(grid: int, y: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the y direction.
- Parameters:
grid (int) – A grid identifier.
y (ndarray of float, shape (ncols,)) – A numpy array to hold the y-coordinates of the grid node rows.
- Returns:
The input numpy array that holds the grid’s row y-coordinates.
- Return type:
ndarray of float
- get_grid_z(grid: int, z: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the z direction.
- Parameters:
grid (int) – A grid identifier.
z (ndarray of float, shape (nlayers,)) – A numpy array to hold the z-coordinates of the grid nodes layers.
- Returns:
The input numpy array that holds the grid’s layer z-coordinates.
- Return type:
ndarray of float
- get_input_item_count() int [source]¶
Count of a model’s input variables.
- Returns:
The number of input variables.
- Return type:
int
- get_input_var_names() Tuple[str] [source]¶
List of a model’s input variables.
Input variable names must be CSDMS Standard Names, also known as long variable names.
- Returns:
The input variables for the model.
- Return type:
list of str
Notes
Standard Names enable the CSDMS framework to determine whether an input variable in one model is equivalent to, or compatible with, an output variable in another model. This allows the framework to automatically connect components.
Standard Names do not have to be used within the model.
- get_output_item_count() int [source]¶
Count of a model’s output variables.
- Returns:
The number of output variables.
- Return type:
int
- get_output_var_names() Tuple[str] [source]¶
List of a model’s output variables.
Output variable names must be CSDMS Standard Names, also known as long variable names.
- Returns:
The output variables for the model.
- Return type:
list of str
- get_start_time() float [source]¶
Start time of the model.
Model times should be of type float.
- Returns:
The model start time.
- Return type:
float
- get_time_step() float [source]¶
Current time step of the model.
The model time step should be of type float.
- Returns:
The time step used in model.
- Return type:
float
- get_time_units() str [source]¶
Time units of the model.
- Returns:
The model time unit; e.g., days or s.
- Return type:
float
Notes
CSDMS uses the UDUNITS standard from Unidata.
- get_value(name: str, dest: ndarray) ndarray [source]¶
Get a copy of values of the given variable.
This is a getter for the model, used to access the model’s current state. It returns a copy of a model variable, with the return type, size and rank dependent on the variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
dest (ndarray) – A numpy array into which to place the values.
- Returns:
The same numpy array that was passed as an input buffer.
- Return type:
ndarray
- get_value_at_indices(name: str, dest: ndarray, inds: ndarray) ndarray [source]¶
Get values at particular indices.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
dest (ndarray) – A numpy array into which to place the values.
indices (array_like) – The indices into the variable array.
- Returns:
Value of the model variable at the given location.
- Return type:
array_like
- get_value_ptr(name: str) ndarray [source]¶
Get a reference to values of the given variable.
This is a getter for the model, used to access the model’s current state. It returns a reference to a model variable, with the return type, size and rank dependent on the variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
A reference to a model variable.
- Return type:
array_like
- get_var_grid(name: str) int [source]¶
Get grid identifier for the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The grid identifier.
- Return type:
int
- get_var_itemsize(name: str) int [source]¶
Get memory use for each array element in bytes.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
Item size in bytes.
- Return type:
int
- get_var_location(name: str) str [source]¶
Get the grid element type that the a given variable is defined on.
The grid topology can be composed of nodes, edges, and faces.
- node
A point that has a coordinate pair or triplet: the most basic element of the topology.
- edge
A line or curve bounded by two nodes.
- face
A plane or surface enclosed by a set of edges. In a 2D horizontal application one may consider the word “polygon”, but in the hierarchy of elements the word “face” is most common.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The grid location on which the variable is defined. Must be one of “node”, “edge”, or “face”.
- Return type:
str
Notes
CSDMS uses the ugrid conventions to define unstructured grids.
- get_var_nbytes(name: str) int [source]¶
Get size, in bytes, of the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The size of the variable, counted in bytes.
- Return type:
int
- get_var_type(name: str) str [source]¶
Get data type of the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The Python variable type; e.g.,
str
,int
,float
.- Return type:
str
- get_var_units(name: str) str [source]¶
Get units of the given variable.
Standard unit names, in lower case, should be used, such as
meters
orseconds
. Standard abbreviations, likem
for meters, are also supported. For variables with compound units, each unit name is separated by a single space, with exponents other than 1 placed immediately after the name, as inm s-1
for velocity,W m-2
for an energy flux, orkm2
for an area.- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The variable units.
- Return type:
str
Notes
CSDMS uses the UDUNITS standard from Unidata.
- initialize(config_file: str) None [source]¶
Perform startup tasks for the model.
Perform all tasks that take place before entering the model’s time loop, including opening files and initializing the model state. Model inputs are read from a text-based configuration file, specified by filename.
- Parameters:
config_file (str, optional) – The path to the model configuration file.
Notes
Models should be refactored, if necessary, to use a configuration file. CSDMS does not impose any constraint on how configuration files are formatted, although YAML is recommended. A template of a model’s configuration file with placeholder values is used by the BMI.
- set_value(name: str, values: ndarray) None [source]¶
Specify a new value for a model variable.
This is the setter for the model, used to change the model’s current state. It accepts, through src, a new value for a model variable, with the type, size and rank of src dependent on the variable.
- Parameters:
var_name (str) – An input or output variable name, a CSDMS Standard Name.
src (array_like) – The new value for the specified variable.
- set_value_at_indices(name: str, inds: ndarray, src: ndarray) None [source]¶
Specify a new value for a model variable at particular indices.
- Parameters:
var_name (str) – An input or output variable name, a CSDMS Standard Name.
indices (array_like) – The indices into the variable array.
src (array_like) – The new value for the specified variable.
- update() None [source]¶
Advance model state by one time step.
Perform all tasks that take place within one pass through the model’s time loop. This typically includes incrementing all of the model’s state variables. If the model’s state variables don’t change in time, then they can be computed by the
initialize()
method and this method can return with no action.
bmi_topography.cli module¶
Command-line interface for bmi-topography
bmi_topography.errors module¶
- exception bmi_topography.errors.BadApiKeySource[source]¶
Bases:
BmiTopographyError
Raise for an invalid API key source.
- exception bmi_topography.errors.BadKeyError[source]¶
Bases:
BmiTopographyError
Raise for an invalid key.
- exception bmi_topography.errors.BmiTopographyError[source]¶
Bases:
Exception
Base exception for all bmi_topography errors.
- exception bmi_topography.errors.MissingKeyError[source]¶
Bases:
BmiTopographyError
Raise if an API key cannot be found.
bmi_topography.topography module¶
Base class to access elevation data
- class bmi_topography.topography.Topography(dem_type=None, south=None, north=None, west=None, east=None, output_format=None, cache_dir=None, api_key=None)[source]¶
Bases:
object
Fetch and cache land elevation data from OpenTopography.
- DEFAULT = {'cache_dir': '~/.bmi_topography', 'dem_type': 'SRTMGL3', 'east': -118.465576, 'north': 38.091337, 'output_format': 'GTiff', 'south': 36.738884, 'west': -120.168457}¶
- NETLOC = 'portal.opentopography.org'¶
- PATH = '/API/globaldem'¶
- SCHEME = 'https'¶
- VALID_DEM_TYPES = ('SRTMGL3', 'SRTMGL1', 'SRTMGL1_E', 'AW3D30', 'AW3D30_E', 'SRTM15Plus', 'NASADEM', 'COP30', 'COP90')¶
- VALID_OUTPUT_FORMATS = {'AAIGrid': 'asc', 'GTiff': 'tif', 'HFA': 'img'}¶
- property bbox¶
- property cache_dir¶
- property da¶
- property dem_type¶
- fetch()[source]¶
Download and locally store topography data.
- Returns:
The path to the downloaded file
- Return type:
pathlib.Path
- property file_extension¶
- load()[source]¶
Load a cached topography data file into an xarray DataArray.
- Returns:
A container for the data
- Return type:
xarray.DataArray
- property output_format¶
Module contents¶
- class bmi_topography.BmiTopography[source]¶
Bases:
Bmi
BMI-mediated access to NASA SRTM land elevation data.
- finalize() None [source]¶
Perform tear-down tasks for the model.
Perform all tasks that take place after exiting the model’s time loop. This typically includes deallocating memory, closing files and printing reports.
- get_component_name() str [source]¶
Name of the component.
- Returns:
The name of the component.
- Return type:
str
- get_current_time() float [source]¶
Current time of the model.
- Returns:
The current model time.
- Return type:
float
- get_end_time() float [source]¶
End time of the model.
- Returns:
The maximum model time.
- Return type:
float
- get_grid_edge_count(grid: int) int [source]¶
Get the number of edges in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid edges.
- Return type:
int
- get_grid_edge_nodes(grid: int, edge_nodes: ndarray) ndarray [source]¶
Get the edge-node connectivity.
- Parameters:
grid (int) – A grid identifier.
edge_nodes (ndarray of int, shape (2 x nnodes,)) – A numpy array to place the edge-node connectivity. For each edge, connectivity is given as node at edge tail, followed by node at edge head.
- Returns:
The input numpy array that holds the edge-node connectivity.
- Return type:
ndarray of int
- get_grid_face_count(grid: int) int [source]¶
Get the number of faces in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid faces.
- Return type:
int
- get_grid_face_edges(grid: int, face_edges: ndarray) ndarray [source]¶
Get the face-edge connectivity.
- Parameters:
grid (int) – A grid identifier.
face_edges (ndarray of int) – A numpy array to place the face-edge connectivity.
- Returns:
The input numpy array that holds the face-edge connectivity.
- Return type:
ndarray of int
- get_grid_face_nodes(grid: int, face_nodes: ndarray) ndarray [source]¶
Get the face-node connectivity.
- Parameters:
grid (int) – A grid identifier.
face_nodes (ndarray of int) – A numpy array to place the face-node connectivity. For each face, the nodes (listed in a counter-clockwise direction) that form the boundary of the face.
- Returns:
The input numpy array that holds the face-node connectivity.
- Return type:
ndarray of int
- get_grid_node_count(grid: int) int [source]¶
Get the number of nodes in the grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
The total number of grid nodes.
- Return type:
int
- get_grid_nodes_per_face(grid: int, nodes_per_face: ndarray) ndarray [source]¶
Get the number of nodes for each face.
- Parameters:
grid (int) – A grid identifier.
nodes_per_face (ndarray of int, shape (nfaces,)) – A numpy array to place the number of edges per face.
- Returns:
The input numpy array that holds the number of nodes per edge.
- Return type:
ndarray of int
- get_grid_origin(grid: int, origin: ndarray) ndarray [source]¶
Get coordinates for the lower-left corner of the computational grid.
- Parameters:
grid (int) – A grid identifier.
origin (ndarray of float, shape (ndim,)) – A numpy array to hold the coordinates of the lower-left corner of the grid.
- Returns:
The input numpy array that holds the coordinates of the grid’s lower-left corner.
- Return type:
ndarray of float
- get_grid_rank(grid: int) int [source]¶
Get number of dimensions of the computational grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Rank of the grid.
- Return type:
int
- get_grid_shape(grid: int, shape: ndarray) ndarray [source]¶
Get dimensions of the computational grid.
- Parameters:
grid (int) – A grid identifier.
shape (ndarray of int, shape (ndim,)) – A numpy array into which to place the shape of the grid.
- Returns:
The input numpy array that holds the grid’s shape.
- Return type:
ndarray of int
- get_grid_size(grid: int) int [source]¶
Get the total number of elements in the computational grid.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Size of the grid.
- Return type:
int
- get_grid_spacing(grid: int, spacing: ndarray) ndarray [source]¶
Get distance between nodes of the computational grid.
- Parameters:
grid (int) – A grid identifier.
spacing (ndarray of float, shape (ndim,)) – A numpy array to hold the spacing between grid rows and columns.
- Returns:
The input numpy array that holds the grid’s spacing.
- Return type:
ndarray of float
- get_grid_type(grid: int) str [source]¶
Get the grid type as a string.
- Parameters:
grid (int) – A grid identifier.
- Returns:
Type of grid as a string.
- Return type:
str
- get_grid_x(grid: int, x: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the x direction.
- Parameters:
grid (int) – A grid identifier.
x (ndarray of float, shape (nrows,)) – A numpy array to hold the x-coordinates of the grid node columns.
- Returns:
The input numpy array that holds the grid’s column x-coordinates.
- Return type:
ndarray of float
- get_grid_y(grid: int, y: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the y direction.
- Parameters:
grid (int) – A grid identifier.
y (ndarray of float, shape (ncols,)) – A numpy array to hold the y-coordinates of the grid node rows.
- Returns:
The input numpy array that holds the grid’s row y-coordinates.
- Return type:
ndarray of float
- get_grid_z(grid: int, z: ndarray) ndarray [source]¶
Get coordinates of grid nodes in the z direction.
- Parameters:
grid (int) – A grid identifier.
z (ndarray of float, shape (nlayers,)) – A numpy array to hold the z-coordinates of the grid nodes layers.
- Returns:
The input numpy array that holds the grid’s layer z-coordinates.
- Return type:
ndarray of float
- get_input_item_count() int [source]¶
Count of a model’s input variables.
- Returns:
The number of input variables.
- Return type:
int
- get_input_var_names() Tuple[str] [source]¶
List of a model’s input variables.
Input variable names must be CSDMS Standard Names, also known as long variable names.
- Returns:
The input variables for the model.
- Return type:
list of str
Notes
Standard Names enable the CSDMS framework to determine whether an input variable in one model is equivalent to, or compatible with, an output variable in another model. This allows the framework to automatically connect components.
Standard Names do not have to be used within the model.
- get_output_item_count() int [source]¶
Count of a model’s output variables.
- Returns:
The number of output variables.
- Return type:
int
- get_output_var_names() Tuple[str] [source]¶
List of a model’s output variables.
Output variable names must be CSDMS Standard Names, also known as long variable names.
- Returns:
The output variables for the model.
- Return type:
list of str
- get_start_time() float [source]¶
Start time of the model.
Model times should be of type float.
- Returns:
The model start time.
- Return type:
float
- get_time_step() float [source]¶
Current time step of the model.
The model time step should be of type float.
- Returns:
The time step used in model.
- Return type:
float
- get_time_units() str [source]¶
Time units of the model.
- Returns:
The model time unit; e.g., days or s.
- Return type:
float
Notes
CSDMS uses the UDUNITS standard from Unidata.
- get_value(name: str, dest: ndarray) ndarray [source]¶
Get a copy of values of the given variable.
This is a getter for the model, used to access the model’s current state. It returns a copy of a model variable, with the return type, size and rank dependent on the variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
dest (ndarray) – A numpy array into which to place the values.
- Returns:
The same numpy array that was passed as an input buffer.
- Return type:
ndarray
- get_value_at_indices(name: str, dest: ndarray, inds: ndarray) ndarray [source]¶
Get values at particular indices.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
dest (ndarray) – A numpy array into which to place the values.
indices (array_like) – The indices into the variable array.
- Returns:
Value of the model variable at the given location.
- Return type:
array_like
- get_value_ptr(name: str) ndarray [source]¶
Get a reference to values of the given variable.
This is a getter for the model, used to access the model’s current state. It returns a reference to a model variable, with the return type, size and rank dependent on the variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
A reference to a model variable.
- Return type:
array_like
- get_var_grid(name: str) int [source]¶
Get grid identifier for the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The grid identifier.
- Return type:
int
- get_var_itemsize(name: str) int [source]¶
Get memory use for each array element in bytes.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
Item size in bytes.
- Return type:
int
- get_var_location(name: str) str [source]¶
Get the grid element type that the a given variable is defined on.
The grid topology can be composed of nodes, edges, and faces.
- node
A point that has a coordinate pair or triplet: the most basic element of the topology.
- edge
A line or curve bounded by two nodes.
- face
A plane or surface enclosed by a set of edges. In a 2D horizontal application one may consider the word “polygon”, but in the hierarchy of elements the word “face” is most common.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The grid location on which the variable is defined. Must be one of “node”, “edge”, or “face”.
- Return type:
str
Notes
CSDMS uses the ugrid conventions to define unstructured grids.
- get_var_nbytes(name: str) int [source]¶
Get size, in bytes, of the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The size of the variable, counted in bytes.
- Return type:
int
- get_var_type(name: str) str [source]¶
Get data type of the given variable.
- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The Python variable type; e.g.,
str
,int
,float
.- Return type:
str
- get_var_units(name: str) str [source]¶
Get units of the given variable.
Standard unit names, in lower case, should be used, such as
meters
orseconds
. Standard abbreviations, likem
for meters, are also supported. For variables with compound units, each unit name is separated by a single space, with exponents other than 1 placed immediately after the name, as inm s-1
for velocity,W m-2
for an energy flux, orkm2
for an area.- Parameters:
name (str) – An input or output variable name, a CSDMS Standard Name.
- Returns:
The variable units.
- Return type:
str
Notes
CSDMS uses the UDUNITS standard from Unidata.
- initialize(config_file: str) None [source]¶
Perform startup tasks for the model.
Perform all tasks that take place before entering the model’s time loop, including opening files and initializing the model state. Model inputs are read from a text-based configuration file, specified by filename.
- Parameters:
config_file (str, optional) – The path to the model configuration file.
Notes
Models should be refactored, if necessary, to use a configuration file. CSDMS does not impose any constraint on how configuration files are formatted, although YAML is recommended. A template of a model’s configuration file with placeholder values is used by the BMI.
- set_value(name: str, values: ndarray) None [source]¶
Specify a new value for a model variable.
This is the setter for the model, used to change the model’s current state. It accepts, through src, a new value for a model variable, with the type, size and rank of src dependent on the variable.
- Parameters:
var_name (str) – An input or output variable name, a CSDMS Standard Name.
src (array_like) – The new value for the specified variable.
- set_value_at_indices(name: str, inds: ndarray, src: ndarray) None [source]¶
Specify a new value for a model variable at particular indices.
- Parameters:
var_name (str) – An input or output variable name, a CSDMS Standard Name.
indices (array_like) – The indices into the variable array.
src (array_like) – The new value for the specified variable.
- update() None [source]¶
Advance model state by one time step.
Perform all tasks that take place within one pass through the model’s time loop. This typically includes incrementing all of the model’s state variables. If the model’s state variables don’t change in time, then they can be computed by the
initialize()
method and this method can return with no action.
- class bmi_topography.BoundingBox(lower_left: Tuple[float], upper_right: Tuple[float])[source]¶
Bases:
object
Represent a simple latitude-longitude bounding box.
Examples
Create a bounding box:
>>> from bmi_topography import BoundingBox >>> bbox = BoundingBox((33, 111), (44, 122)) >>> print(bbox) [(33, 111), (44, 122)]
- property east¶
- property lower_left¶
The southwest corner of the box, given by tuple of (south, west).
- property north¶
- property south¶
- property upper_right¶
The northeast corner of the box, given by tuple of (north, east).
- property west¶
- class bmi_topography.Topography(dem_type=None, south=None, north=None, west=None, east=None, output_format=None, cache_dir=None, api_key=None)[source]¶
Bases:
object
Fetch and cache land elevation data from OpenTopography.
- DEFAULT = {'cache_dir': '~/.bmi_topography', 'dem_type': 'SRTMGL3', 'east': -118.465576, 'north': 38.091337, 'output_format': 'GTiff', 'south': 36.738884, 'west': -120.168457}¶
- NETLOC = 'portal.opentopography.org'¶
- PATH = '/API/globaldem'¶
- SCHEME = 'https'¶
- VALID_DEM_TYPES = ('SRTMGL3', 'SRTMGL1', 'SRTMGL1_E', 'AW3D30', 'AW3D30_E', 'SRTM15Plus', 'NASADEM', 'COP30', 'COP90')¶
- VALID_OUTPUT_FORMATS = {'AAIGrid': 'asc', 'GTiff': 'tif', 'HFA': 'img'}¶
- property bbox¶
- property cache_dir¶
- property da¶
- property dem_type¶
- fetch()[source]¶
Download and locally store topography data.
- Returns:
The path to the downloaded file
- Return type:
pathlib.Path
- property file_extension¶
- load()[source]¶
Load a cached topography data file into an xarray DataArray.
- Returns:
A container for the data
- Return type:
xarray.DataArray
- property output_format¶