def test_resample_grid(tgrid):
"""
Test resampling grid
"""
new_mask_grid = os.path.join(tgrid.input, 'v_mask.tif')
era_grid = os.path.join(tgrid.input, 'era_raw.tif')
resampled_grid = os.path.join(tgrid.write, 'resampled.tif')
resample_grid(original_grid=era_grid,
match_grid=new_mask_grid,
to_file=resampled_grid)
compare_resampled_grid = os.path.join(tgrid.write, 'resampled.tif')
compare_files(resampled_grid, compare_resampled_grid, raster=True)
def resample(self, variable, match_grid):
"""Resample data to grid.
Parameters
----------
variable: :obj:`str`
Name of variable in dataset.
match_grid: :func:`gdal.Dataset` or :func:`sloot.grid.GDALGrid`
Grid you want the data resampled to match resolution.
You can also pass the path to the grid.
"""
new_data = []
for band in range(self._obj.dims[self.time_dim]):
data = self._obj[variable][band].values
arr_grid = ArrayGrid(in_array=data,
wkt_projection=self.projection.ExportToWkt(),
geotransform=self.geotransform)
resampled_data_grid = resample_grid(original_grid=arr_grid,
match_grid=match_grid,
as_gdal_grid=True)
new_data.append(resampled_data_grid.np_array())
self.to_datetime()
return self._export_dataset(variable, np.array(new_data),
resampled_data_grid)
def addRoughnessMapFromLandUse(self, name,
session,
land_use_grid,
land_use_to_roughness_table=None,
land_use_grid_id=None,
):
'''
Adds a roughness map from land use file
Example::
from gsshapy.orm import ProjectFile
from gsshapy.lib import db_tools as dbt
from os import path, chdir
gssha_directory = '/gsshapy/tests/grid_standard/gssha_project'
land_use_grid = 'LC_5min_global_2012.tif'
land_use_to_roughness_table = ''/gsshapy/gridtogssha/land_cover/land_cover_glcf_modis.txt'
chdir(gssha_directory)
# Create Test DB
sqlalchemy_url, sql_engine = dbt.init_sqlite_memory()
# Create DB Sessions
db_session = dbt.create_session(sqlalchemy_url, sql_engine)
# Instantiate GSSHAPY object for reading to database
project_manager = ProjectFile()
# Call read method
project_manager.readInput(directory=gssha_directory,
projectFileName='grid_standard.prj',
session=db_session)
project_manager.mapTableFile.addRoughnessMapFromLandUse("roughness",
db_session,
land_use_to_roughness_table,
land_use_grid,
)
# WRITE OUT UPDATED GSSHA PROJECT FILE
project_manager.writeInput(session=db_session,
directory=gssha_directory,
name='grid_standard')
'''
LAND_USE_GRID_TABLES = {
'nga' : 'land_cover_nga.txt',
'glcf' : 'land_cover_glcf_modis.txt',
'nlcd' : 'land_cover_nlcd.txt',
}
# read in table
if isinstance(land_use_to_roughness_table, pd.DataFrame):
df = land_use_to_roughness_table
else:
if land_use_to_roughness_table is None:
if land_use_grid_id is None:
raise ValueError("Must have land_use_to_roughness_table or land_use_grid_id set ...")
land_use_to_roughness_table = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'..', 'grid',
'land_cover',
LAND_USE_GRID_TABLES[land_use_grid_id])
df = pd.read_table(land_use_to_roughness_table, delim_whitespace=True,
header=None, skiprows=1,
names=('id', 'description', 'roughness'),
dtype={'id':'int', 'description':'str', 'roughness':'float'},
)
# resample land use grid to gssha grid
land_use_resampled = resample_grid(land_use_grid,
self.projectFile.getGrid(),
resample_method=gdalconst.GRA_NearestNeighbour,
as_gdal_grid=True)
unique_land_use_ids = np.unique(land_use_resampled.np_array())
#only add ids in index map subset
df = df[df.id.isin(unique_land_use_ids)]
# make sure all needed land use IDs exist
for land_use_id in unique_land_use_ids:
if land_use_id not in df.id.values:
raise IndexError("Land use ID {0} not found in table.".format(land_use_id))
# delete duplicate/old tables with same name if they exist
self.deleteMapTable("ROUGHNESS", session)
# get num ids
mapTable = MapTable(name="ROUGHNESS",
numIDs=len(df.index),
maxNumCells=0,
numSed=0,
numContam=0)
# Create GSSHAPY IndexMap object from result object
indexMap = IndexMap(name=name)
indexMap.mapTableFile = self
mapTable.indexMap = indexMap
# Associate MapTable with this MapTableFile and IndexMaps
mapTable.mapTableFile = self
# add values to table
for row in df.itertuples():
idx = MTIndex(str(row.id), row.description, '')
idx.indexMap = indexMap
val = MTValue('ROUGH', row.roughness)
val.index = idx
val.mapTable = mapTable
project_path = ""
proj_path_card = self.projectFile.getCard('PROJECT_PATH')
if proj_path_card:
project_path = proj_path_card.value.strip('"').strip("'")
# remove MANNING_N card becasue it is mutually exclusive
manningn_card = self.projectFile.getCard('MANNING_N')
if manningn_card:
session.delete(manningn_card)
session.commit()
# add path to file
mapTable.indexMap.filename = os.path.join(project_path,
'{0}.idx'.format(name))
# write file
land_use_resampled.to_grass_ascii(mapTable.indexMap.filename,
print_nodata=False)
# update project card
if not self.projectFile.getCard('MAPPING_TABLE'):
self.projectFile.setCard('MAPPING_TABLE',
'{0}.cmt'.format(self.projectFile.name),
add_quotes=True)
def generateFromRaster(self,
elevation_raster,
shapefile_path=None,
out_elevation_grid=None,
resample_method=gdalconst.GRA_Average,
load_raster_to_db=True):
"""
Generates an elevation grid for the GSSHA simulation
from an elevation raster
Example::
from gsshapy.orm import ProjectFile, ElevationGridFile
from gsshapy.lib import db_tools as dbt
gssha_directory = '/gsshapy/tests/grid_standard/gssha_project'
elevation_raster = 'elevation.tif'
project_manager, db_sessionmaker = \
dbt.get_project_session('grid_standard',
gssha_directory)
db_session = db_sessionmaker()
# read project file
project_manager.readInput(directory=gssha_directory,
projectFileName='grid_standard.prj',
session=db_session)
# generate elevation grid
elevation_grid = ElevationGridFile(session=db_session,
project_file=project_manager)
elevation_grid.generateFromRaster(elevation_raster)
# write out updated parameters
project_manager.writeInput(session=db_session,
directory=gssha_directory,
name='grid_standard')
"""
if not self.projectFile:
raise ValueError("Must be connected to project file ...")
# make sure paths are absolute as the working directory changes
elevation_raster = os.path.abspath(elevation_raster)
shapefile_path = os.path.abspath(shapefile_path)
# must match elevation mask grid
mask_grid = self.projectFile.getGrid()
if out_elevation_grid is None:
out_elevation_grid = '{0}.{1}'.format(self.projectFile.name,
self.fileExtension)
elevation_grid = resample_grid(elevation_raster,
mask_grid,
resample_method=resample_method,
as_gdal_grid=True)
with tmp_chdir(self.projectFile.project_directory):
elevation_grid.to_grass_ascii(out_elevation_grid,
print_nodata=False)
# read raster into object
if load_raster_to_db:
self._load_raster_text(out_elevation_grid)
self.filename = out_elevation_grid
self.projectFile.setCard("ELEVATION",
out_elevation_grid,
add_quotes=True)
# find outlet and add slope
self.projectFile.findOutlet(shapefile_path)
def generateFromRaster(self,
elevation_raster,
shapefile_path=None,
out_elevation_grid=None,
resample_method=gdalconst.GRA_Average):
'''
Generates an elevation grid for the GSSHA simulation
from an elevation raster
Example::
from gsshapy.orm import ProjectFile, ElevationGridFile
from gsshapy.lib import db_tools as dbt
from os import path, chdir
gssha_directory = '/gsshapy/tests/grid_standard/gssha_project'
elevation_raster = 'elevation.tif'
# Create Test DB
sqlalchemy_url, sql_engine = dbt.init_sqlite_memory()
# Create DB Sessions
db_session = dbt.create_session(sqlalchemy_url, sql_engine)
# Instantiate GSSHAPY object for reading to database
project_manager = ProjectFile()
# read project file
project_manager.readInput(directory=gssha_directory,
projectFileName='grid_standard.prj',
session=db_session)
# generate elevation grid
elevation_grid = ElevationGridFile(session=db_session,
project_file=project_manager)
elevation_grid.generateFromRaster(elevation_raster)
# write out updated parameters
project_manager.writeInput(session=db_session,
directory=gssha_directory,
name='grid_standard')
'''
if not self.projectFile:
raise ValueError("Must be connected to project file ...")
# must match elevation mask grid
mask_grid = self.projectFile.getGrid()
if out_elevation_grid is None:
project_path = ''
project_path_card = self.projectFile.getCard('PROJECT_PATH')
if project_path_card:
project_path = project_path_card.value.strip('"').strip("'")
out_elevation_grid = os.path.join(
project_path,
'{0}.{1}'.format(self.projectFile.name, self.fileExtension),
)
elevation_grid = resample_grid(elevation_raster,
mask_grid,
resample_method=resample_method,
as_gdal_grid=True)
elevation_grid.to_grass_ascii(out_elevation_grid, print_nodata=False)
self.filename = out_elevation_grid
self.projectFile.setCard("ELEVATION",
out_elevation_grid,
add_quotes=True)
# read raster into object
self._load_raster_text(out_elevation_grid)
# find outlet and add slope
self.projectFile.findOutlet(shapefile_path)
def addRoughnessMapFromLandUse(self, name,
session,
land_use_grid,
land_use_to_roughness_table=None,
land_use_grid_id=None,
):
"""
Adds a roughness map from land use file
Example::
from gsshapy.orm import ProjectFile
from gsshapy.lib import db_tools as dbt
from os import path, chdir
gssha_directory = '/gsshapy/tests/grid_standard/gssha_project'
land_use_grid = 'LC_5min_global_2012.tif'
land_use_to_roughness_table = ''/gsshapy/gridtogssha/land_cover/land_cover_glcf_modis.txt'
# Create Test DB
sqlalchemy_url, sql_engine = dbt.init_sqlite_memory()
# Create DB Sessions
db_session = dbt.create_session(sqlalchemy_url, sql_engine)
# Instantiate GSSHAPY object for reading to database
project_manager = ProjectFile()
# Call read method
project_manager.readInput(directory=gssha_directory,
projectFileName='grid_standard.prj',
session=db_session)
project_manager.mapTableFile.addRoughnessMapFromLandUse("roughness",
db_session,
land_use_to_roughness_table,
land_use_grid,
)
# WRITE OUT UPDATED GSSHA PROJECT FILE
project_manager.writeInput(session=db_session,
directory=gssha_directory,
name='grid_standard')
"""
LAND_USE_GRID_TABLES = {
'nga' : 'land_cover_nga.txt',
'glcf' : 'land_cover_glcf_modis.txt',
'nlcd' : 'land_cover_nlcd.txt',
}
# read in table
if isinstance(land_use_to_roughness_table, pd.DataFrame):
df = land_use_to_roughness_table
else:
if land_use_to_roughness_table is None:
if land_use_grid_id is None:
raise ValueError("Must have land_use_to_roughness_table or land_use_grid_id set ...")
land_use_to_roughness_table = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'..', 'grid',
'land_cover',
LAND_USE_GRID_TABLES[land_use_grid_id])
# make sure paths are absolute as the working directory changes
land_use_to_roughness_table = os.path.abspath(land_use_to_roughness_table)
df = pd.read_table(land_use_to_roughness_table, delim_whitespace=True,
header=None, skiprows=1,
names=('id', 'description', 'roughness'),
dtype={'id':'int', 'description':'str', 'roughness':'float'},
)
# make sure paths are absolute as the working directory changes
land_use_grid = os.path.abspath(land_use_grid)
# resample land use grid to gssha grid
land_use_resampled = resample_grid(land_use_grid,
self.projectFile.getGrid(),
resample_method=gdalconst.GRA_NearestNeighbour,
as_gdal_grid=True)
unique_land_use_ids = np.unique(land_use_resampled.np_array())
# only add ids in index map subset
df = df[df.id.isin(unique_land_use_ids)]
# make sure all needed land use IDs exist
for land_use_id in unique_land_use_ids:
if land_use_id not in df.id.values:
raise IndexError("Land use ID {0} not found in table.".format(land_use_id))
# delete duplicate/old tables with same name if they exist
self.deleteMapTable("ROUGHNESS", session)
# get num ids
mapTable = MapTable(name="ROUGHNESS",
numIDs=len(df.index),
maxNumCells=0,
numSed=0,
numContam=0)
# Create GSSHAPY IndexMap object from result object
indexMap = IndexMap(name=name)
indexMap.mapTableFile = self
mapTable.indexMap = indexMap
# Associate MapTable with this MapTableFile and IndexMaps
mapTable.mapTableFile = self
# add values to table
for row in df.itertuples():
idx = MTIndex(str(row.id), row.description, '')
idx.indexMap = indexMap
val = MTValue('ROUGH', row.roughness)
val.index = idx
val.mapTable = mapTable
# remove MANNING_N card becasue it is mutually exclusive
manningn_card = self.projectFile.getCard('MANNING_N')
if manningn_card:
session.delete(manningn_card)
session.commit()
mapTable.indexMap.filename = '{0}.idx'.format(name)
# write file
with tmp_chdir(self.projectFile.project_directory):
land_use_resampled.to_grass_ascii(mapTable.indexMap.filename,
print_nodata=False)
# update project card
if not self.projectFile.getCard('MAPPING_TABLE'):
self.projectFile.setCard('MAPPING_TABLE',
'{0}.cmt'.format(self.projectFile.name),
add_quotes=True)
def generateFromRaster(self,
elevation_raster,
shapefile_path=None,
out_elevation_grid=None,
resample_method=gdalconst.GRA_Average,
load_raster_to_db=True):
"""
Generates an elevation grid for the GSSHA simulation
from an elevation raster
Example::
from gsshapy.orm import ProjectFile, ElevationGridFile
from gsshapy.lib import db_tools as dbt
gssha_directory = '/gsshapy/tests/grid_standard/gssha_project'
elevation_raster = 'elevation.tif'
project_manager, db_sessionmaker = \
dbt.get_project_session('grid_standard',
gssha_directory)
db_session = db_sessionmaker()
# read project file
project_manager.readInput(directory=gssha_directory,
projectFileName='grid_standard.prj',
session=db_session)
# generate elevation grid
elevation_grid = ElevationGridFile(session=db_session,
project_file=project_manager)
elevation_grid.generateFromRaster(elevation_raster)
# write out updated parameters
project_manager.writeInput(session=db_session,
directory=gssha_directory,
name='grid_standard')
"""
if not self.projectFile:
raise ValueError("Must be connected to project file ...")
# make sure paths are absolute as the working directory changes
elevation_raster = os.path.abspath(elevation_raster)
shapefile_path = os.path.abspath(shapefile_path)
# must match elevation mask grid
mask_grid = self.projectFile.getGrid()
if out_elevation_grid is None:
out_elevation_grid = '{0}.{1}'.format(self.projectFile.name,
self.fileExtension)
elevation_grid = resample_grid(elevation_raster,
mask_grid,
resample_method=resample_method,
as_gdal_grid=True)
with tmp_chdir(self.projectFile.project_directory):
elevation_grid.to_grass_ascii(out_elevation_grid, print_nodata=False)
# read raster into object
if load_raster_to_db:
self._load_raster_text(out_elevation_grid)
self.filename = out_elevation_grid
self.projectFile.setCard("ELEVATION", out_elevation_grid, add_quotes=True)
# find outlet and add slope
self.projectFile.findOutlet(shapefile_path)