def study_area_gpis():
#=========STUDY AREA GRID POINTS ============
gpi_path = "C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\pointlist_India_warp.csv"
gpis = pd.read_csv(gpi_path)
gpi_path_p = "C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\pointlist_Pakistan_warp.csv"
gpis_p = pd.read_csv(gpi_path_p)
gpis = gpis.append(gpis_p)
grid = BasicGrid(gpis.lon, gpis.lat, gpis.point)
gpis = grid.get_bbox_grid_points(14.7148, 29.3655, 68.15, 81.8419)
lon, lat = grid.get_bbox_grid_points(14.7148, 29.3655, 68.15, 81.8419, coords=True)
gp = pd.DataFrame(gpis, columns=['gpi'])
lon = pd.DataFrame(lon, columns=['lon'])
lat = pd.DataFrame(lat, columns=['lat'])
gplon = pd.concat([gp, lon], axis=1)
gplonlat = pd.concat([gplon, lat], axis=1)
gplonlat.to_csv("C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\study_area_gp_lonlat_new.csv")
def study_area_gpis():
#=========STUDY AREA GRID POINTS ============
gpi_path = "C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\pointlist_India_warp.csv"
gpis = pd.read_csv(gpi_path)
gpi_path_p = "C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\pointlist_Pakistan_warp.csv"
gpis_p = pd.read_csv(gpi_path_p)
gpis = gpis.append(gpis_p)
grid = BasicGrid(gpis.lon, gpis.lat, gpis.point)
gpis = grid.get_bbox_grid_points(14.7148, 29.3655, 68.15, 81.8419)
lon, lat = grid.get_bbox_grid_points(14.7148,
29.3655,
68.15,
81.8419,
coords=True)
gp = pd.DataFrame(gpis, columns=['gpi'])
lon = pd.DataFrame(lon, columns=['lon'])
lat = pd.DataFrame(lat, columns=['lat'])
gplon = pd.concat([gp, lon], axis=1)
gplonlat = pd.concat([gplon, lat], axis=1)
gplonlat.to_csv(
"C:\\Users\\s.hochstoger\\Desktop\\0_IWMI_DATASETS\\study_area_gp_lonlat_new.csv"
)
def __init__(self, bbox=None):
"""
Parameters
----------
bbox: tuple, optional (default: None)
(min_lon, min_lat, max_lon, max_lat)
Bounding box to create subset for, if None is passed a global
grid is used.
"""
ease25 = EASE2_grid(25000)
lons, lats = ease25.londim, ease25.latdim
lons, lats = np.meshgrid(lons, lats)
assert lons.shape == lats.shape
shape = lons.shape
lats = np.flipud(lats) # flip lats, so that origin in bottom left
lons, lats = lons.flatten(), lats.flatten()
globgrid = BasicGrid(lons, lats, shape=shape)
sgpis = globgrid.activegpis
self.bbox = bbox
if self.bbox:
sgpis = globgrid.get_bbox_grid_points(latmin=self.bbox[1],
latmax=self.bbox[3],
lonmin=self.bbox[0],
lonmax=self.bbox[2])
self.cellsize = 5.
super(EASE25CellGrid,
self).__init__(lon=globgrid.arrlon,
lat=globgrid.arrlat,
subset=sgpis,
cells=lonlat2cell(globgrid.arrlon,
globgrid.arrlat, self.cellsize),
shape=shape)
self.subset_shape = (len(np.unique(self.activearrlat)),
len(np.unique(self.activearrlon)))
def ERA_IrregularImgGrid(
lons: np.ndarray,
lats: np.ndarray,
bbox: Tuple[float, float, float, float] = None,
) -> CellGrid:
"""
Create a irregular grid from the passed coordinates.
"""
lons_gt_180 = np.where(lons > 180.0)
lons[lons_gt_180] = lons[lons_gt_180] - 360
grid = BasicGrid(lons.flatten(), lats.flatten())\
.to_cell_grid(cellsize=5.0)
if bbox is not None:
gpis = grid.get_bbox_grid_points(
lonmin=bbox[0], latmin=bbox[1], lonmax=bbox[2], latmax=bbox[3]
)
grid = grid.subgrid_from_gpis(gpis)
return grid
