Grid

The grid capabilities are one of the main features of this pylawr package and are used to georeference radar fields. This georeference is necessary for noise-correction, attenuation-correction, remapping and plotting. All grids have a common interface and are automatically used for different purposes. The most important interface is the translation of grid coordinates to latitude and longitude coordinates. This translation is defined within every grid type and excessively used within pylawr.

Different grid types are defined in this submodule, which are shortly reviewed in the following:

Polar coordinates (native radar grid)

Every point within this coordinate system is defined with an azimuth angle and a range distance from the center point and an altitude in meters. This grid is centered around a given center point (lat, lon, height). Further settings of the resolution and number of grid points in azimuthal and range direction are possible. The altitude for every grid point is estimated based on the center height and specified beam elevation.

These polar coordinates are normally the native radar grid and almost any non-processed radar data will be on this grid. The pre-settings are set to the default values for the X-band radar on the Geomatikum.

pylawr.grid.PolarGrid([center, beam_ele, ...])

The PolarGrid is the natural grid of a radar.

Rectangular coordinates

Rectangular coordinates are commonly defined by a X- and Y-position and a static altitude. These grids have a starting point (start) and resolution in its own coordinates. The number of coordinates can be additionally defined (nr_points). The grid altitude is defined by the height of a specified center point (lat, lon, height).

Two different kinds of rectangular grid are defined at the moment:

The cartesian grid defines the X- and Y-position as relative position in meters to a given center point (lat, lon, height). An additional plate carre grid (LatLonGrid) defines the X- and Y-position as absolute position in terms of latitude and longitude.

These grids are normally used to compare and combine data from different radars. The pre-settings are set to cover the area of the X-band radar on top of the Geomatikum.

pylawr.grid.CartesianGrid([resolution, ...])	The CartesianGrid can be used for easier composite calculations of radar fields.
pylawr.grid.LatLonGrid([resolution, start, ...])	The LatLonGrid can be used to translate RadarGrids into NWP weather model grids.
pylawr.grid.RectangularGrid([resolution, ...])	The RectangularGrid can be used for easier composite calculations of radar fields.

Unstructured coordinates

Coordinates of the unstructured grid are defined by their position in latitude and longitude, specified with an array of in_coords. An additional dimension of altitudes can be given. If the altitudes are not given, they will be inferred from a specified center point (lat, lon, height). In comparison to the rectangular latitude and longitude grid, this unstructured grid follows no building structure and the coordinates have to be given explicitly.

This grid can be used as interface to non-specified grids and is currently only used to fill-in holes after clutter detection in operations. Further this grid is not fully defined at the moment and can therefore only be used for intermediate remapping purpose.

pylawr.grid.UnstructuredGrid(in_coords[, ...])

An unstructured grid is a grid, where for every grid point latitude and longitude values are given, but they don't need to be in their own structured grid.

Helper functions

Different helper functions are used to translate different grid definitions into other grids.

get_latlon_grid() translates the latitude and longitude coordinates of any given grid into a rectangular LatLonGrid and infers automatically the settings of this rectangular grid.

A similar function is get_cartesian(), translating the latitude and longitude coordinates of any given grid into an array of cartesian coordinates. These cartesian coordinates are then relative to the center of the source grid.

An additional helper function, called get_masked_grid(), masks coordinates within any given grid. The grid coordinates are masked based on a given mask array. Due to masking, the resulting grid is an UnstructuredGrid, which can be remapped to a structured grid.

pylawr.functions.grid.get_latlon_grid(orig_grid)	This function can be used to get a rectangular LatLonGrid.
pylawr.functions.grid.get_cartesian(grid[, ...])	This method calculates cartesian coordinates based on the given grid.
pylawr.functions.grid.get_masked_grid(...)	Mask value within a given origin grid.

Functional API

The functional grid API can be used for a simplified handling of grids within this pylawr package.

Only a function to remap data from a source grid to a target grid is defined at the moment. This remap_data() function remaps the data with a given remapper (see also Remapping). If no remapper is given, the data is interpolated by nearest neighbor.

pylawr.functions.grid.remap_data(data, ...)

This function remaps data based on given grids with given remap instance.