climada.hazard.centroids package#

climada.hazard.centroids.centr module#

class climada.hazard.centroids.centr.Centroids(lat: Optional[numpy.ndarray] = None, lon: Optional[numpy.ndarray] = None, geometry: Optional[geopandas.geoseries.GeoSeries] = None, meta: Optional[Dict[Any, Any]] = None, area_pixel: Optional[numpy.ndarray] = None, on_land: Optional[numpy.ndarray] = None, region_id: Optional[numpy.ndarray] = None, elevation: Optional[numpy.ndarray] = None, dist_coast: Optional[numpy.ndarray] = None)[source]#

Bases: object

Contains raster or vector centroids.

meta#

rasterio meta dictionary containing raster properties: width, height, crs and transform must be present at least. The affine ransformation needs to be shearless (only stretching) and have positive x- and negative y-orientation.

Type: dict, optional

lat#

latitude of size size

Type: np.array, optional

lon#

longitude of size size

Type: np.array, optional

geometry#

contains lat and lon crs. Might contain geometry points for lat and lon

Type: gpd.GeoSeries, optional

area_pixel#

area of size size

Type: np.array, optional

dist_coast#

distance to coast of size size

Type: np.array, optional

on_land#

on land (True) and on sea (False) of size size

Type: np.array, optional

region_id#

country region code of size size

Type: np.array, optional

elevation#

elevation of size size

Type: np.array, optional

vars_check = {'area_pixel', 'dist_coast', 'elevation', 'geometry', 'lat', 'lon', 'on_land', 'region_id'}#: Variables whose size will be checked

__init__(lat: Optional[numpy.ndarray] = None, lon: Optional[numpy.ndarray] = None, geometry: Optional[geopandas.geoseries.GeoSeries] = None, meta: Optional[Dict[Any, Any]] = None, area_pixel: Optional[numpy.ndarray] = None, on_land: Optional[numpy.ndarray] = None, region_id: Optional[numpy.ndarray] = None, elevation: Optional[numpy.ndarray] = None, dist_coast: Optional[numpy.ndarray] = None)[source]#

Initialization

Parameters

lat (np.array, optional) – latitude of size size. Defaults to empty array
lon (np.array, optional) – longitude of size size. Defaults to empty array
geometry (gpd.GeoSeries, optional) – contains lat and lon crs. Might contain geometry points for lat and lon. Defaults to empty gpd.Geoseries with crs=DEF_CRS
meta (dict, optional) – rasterio meta dictionary containing raster properties: width, height, crs and transform must be present at least. The affine ransformation needs to be shearless (only stretching) and have positive x- and negative y-orientation. Defaults to empty dict()
area_pixel (np.array, optional) – area of size size. Defaults to empty array
on_land (np.array, optional) – on land (True) and on sea (False) of size size. Defaults to empty array
region_id (np.array, optional) – country region code of size size, Defaults to empty array
elevation (np.array, optional) – elevation of size size. Defaults to empty array
dist_coast (np.array, optional) – distance to coast of size size. Defaults to empty array

check()[source]#

Check integrity of stored information.

Checks that either meta attribute is set, or lat, lon and geometry.crs. Checks sizes of (optional) data attributes.

equal(centr)[source]#

Return True if two centroids equal, False otherwise

Parameters: centr (Centroids) – centroids to compare
Returns: eq
Return type: bool

static from_base_grid(land=False, res_as=360, base_file=None)[source]#

Initialize from base grid data provided with CLIMADA

Parameters

land (bool, optional) – If True, restrict to grid points on land. Default: False.
res_as (int, optional) – Base grid resolution in arc-seconds (one of 150, 360). Default: 360.
base_file (str, optional) – If set, read this file instead of one provided with climada.

classmethod from_geodataframe(gdf, geometry_alias='geom')[source]#

Create Centroids instance from GeoDataFrame.

Deprecated since version 3.3: This method will be removed in a future version. Pass the data you want to construct the Centroids with to the constructor instead.

The geometry, lat, and lon attributes are set from the GeoDataFrame.geometry attribute, while the columns are copied as attributes to the Centroids object in the form of numpy.ndarrays using pandas.Series.to_numpy. The Series dtype will thus be respected.

Columns named lat or lon are ignored, as they would overwrite the coordinates extracted from the point features. If the geometry attribute bears an alias, it can be dropped by setting the geometry_alias parameter.

If the GDF includes a region_id column, but no on_land column, then on_land=True is inferred for those centroids that have a set region_id.

Example

>>> gdf = geopandas.read_file('centroids.shp')
>>> gdf.region_id = gdf.region_id.astype(int)  # type coercion
>>> centroids = Centroids.from_geodataframe(gdf)

Parameters

gdf (GeoDataFrame) – Where the geometry column needs to consist of point features. See above for details on processing.
geometry_alias (str, opt) – Alternate name for the geometry column; dropped to avoid duplicate assignment.

Returns

centr – Centroids with data from given GeoDataFrame

Return type

Centroids

classmethod from_pix_bounds(xf_lat, xo_lon, d_lat, d_lon, n_lat, n_lon, crs='EPSG:4326')[source]#

Create Centroids object with meta attribute according to pixel border data.

Deprecated since version 3.3: This method will be removed in a future version. CLIMADA will only support regular grids with a constant lat/lon resolution then. Use from_pnt_bounds() instead.

Parameters

xf_lat (float) – upper latitude (top)
xo_lon (float) – left longitude
d_lat (float) – latitude step (negative)
d_lon (float) – longitude step (positive)
n_lat (int) – number of latitude points
n_lon (int) – number of longitude points
crs (dict() or rasterio.crs.CRS, optional) – CRS. Default: DEF_CRS

Returns

centr – Centroids with meta according to given pixel border data.

Return type

Centroids

set_raster_from_pnt_bounds(*args, **kwargs)[source]#: This function is deprecated, use Centroids.from_pnt_bounds instead.

classmethod from_pnt_bounds(points_bounds, res, crs='EPSG:4326')[source]#

Create Centroids object with meta attribute according to points border data.

raster border = point border + res/2

Parameters

points_bounds (tuple) – points’ lon_min, lat_min, lon_max, lat_max
res (float) – desired resolution in same units as points_bounds
crs (dict() or rasterio.crs.CRS, optional) – CRS. Default: DEF_CRS

Returns

centr – Centroids with meta according to given points border data.

Return type

Centroids

set_lat_lon(*args, **kwargs)[source]#: This function is deprecated, use Centroids.from_lat_lon instead.

classmethod from_lat_lon(lat, lon, crs='EPSG:4326')[source]#

Create Centroids object from given latitude, longitude and CRS.

Parameters

lat (np.array) – latitude
lon (np.array) – longitude
crs (dict() or rasterio.crs.CRS, optional) – CRS. Default: DEF_CRS

Returns

centr – Centroids with points according to given coordinates

Return type

Centroids

set_raster_file(file_name, band=None, **kwargs)[source]#: This function is deprecated, use Centroids.from_raster_file and Centroids.values_from_raster_files instead.

classmethod from_raster_file(file_name, src_crs=None, window=None, geometry=None, dst_crs=None, transform=None, width=None, height=None, resampling=Resampling.nearest)[source]#

Create a new Centroids object from a raster file

Select region using window or geometry. Reproject input by providing dst_crs and/or (transform, width, height).

Parameters

file_name (str) – path of the file
src_crs (crs, optional) – source CRS. Provide it if error without it.
window (rasterio.windows.Window, optional) – window to read
geometry (list of shapely.geometry, optional) – consider pixels only within these shapes
dst_crs (crs, optional) – reproject to given crs
transform (rasterio.Affine) – affine transformation to apply
wdith (float) – number of lons for transform
height (float) – number of lats for transform
resampling (rasterio.warp,.Resampling optional) – resampling function used for reprojection to dst_crs

Returns

centr – Centroids with meta attribute according to the given raster file

Return type

Centroids

values_from_raster_files(file_names, band=None, src_crs=None, window=None, geometry=None, dst_crs=None, transform=None, width=None, height=None, resampling=Resampling.nearest)[source]#

Read raster of bands and set 0 values to the masked ones.

Each band is an event. Select region using window or geometry. Reproject input by proving dst_crs and/or (transform, width, height).

Parameters

file_names (str) – path of the file
band (list(int), optional) – band number to read. Default: [1]
src_crs (crs, optional) – source CRS. Provide it if error without it.
window (rasterio.windows.Window, optional) – window to read
geometry (list of shapely.geometry, optional) – consider pixels only within these shapes
dst_crs (crs, optional) – reproject to given crs
transform (rasterio.Affine) – affine transformation to apply
wdith (float) – number of lons for transform
height (float) – number of lats for transform
resampling (rasterio.warp,.Resampling optional) – resampling function used for reprojection to dst_crs

Raises

ValueError –

Returns

inten – Each row is an event.

Return type

scipy.sparse.csr_matrix

set_vector_file(file_name, inten_name=None, **kwargs)[source]#: This function is deprecated, use Centroids.from_vector_file and Centroids.values_from_vector_files instead.

classmethod from_vector_file(file_name, dst_crs=None)[source]#

Create Centroids object from vector file (any format supported by fiona).

Parameters

file_name (str) – vector file with format supported by fiona and ‘geometry’ field.
dst_crs (crs, optional) – reproject to given crs

Returns

centr – Centroids with points according to the given vector file

Return type

Centroids

values_from_vector_files(file_names, val_names=None, dst_crs=None)[source]#

Read intensity or other data from vector files, making sure that geometry is compatible.

If the geometry of the shapes in any of the given files does not agree with the geometry of this Centroids instance, a ValueError is raised.

Parameters

file_names (list(str)) – vector files with format supported by fiona and ‘geometry’ field.
val_names (list(str), optional) – list of names of the columns of the values. Default: [‘intensity’]
dst_crs (crs, optional) – reproject to given crs

Raises

ValueError –

Returns

values – Sparse array of shape (len(val_name), len(geometry)).

Return type

scipy.sparse.csr_matrix

read_mat(*args, **kwargs)[source]#: This function is deprecated, use Centroids.from_mat instead.

classmethod from_mat(file_name, var_names=None)[source]#

Read centroids from CLIMADA’s MATLAB version.

Parameters

file_name (str) – absolute or relative file name
var_names (dict, optional) – name of the variables

Raises

KeyError –

Returns

centr – Centroids with data from the given file

Return type

Centroids

read_excel(*args, **kwargs)[source]#: This function is deprecated, use Centroids.from_excel instead.

classmethod from_excel(file_name, var_names=None)[source]#

Generate a new centroids object from an excel file with column names in var_names.

Parameters

file_name (str) – absolute or relative file name
var_names (dict, default) – name of the variables

Raises

KeyError –

Returns

centr – Centroids with data from the given file

Return type

Centroids

clear()[source]#: Clear vector and raster data.

append(centr)[source]#

Append centroids points.

If centr or self are rasters they are converted to points first using Centroids.set_meta_to_lat_lon. Note that self is modified in-place, and meta is set to {}. Thus, raster information in self is lost.

Note: this is a wrapper for centroids.union.

Parameters: centr (Centroids) – Centroids to append. The centroids need to have the same CRS.

CLIMADA 4.0.1 documentation

climada.hazard.centroids package

Contents

climada.hazard.centroids package#

climada.hazard.centroids.centr module#