Dear all:
This is my code:
import pygmt
grid = pygmt.datasets.load_earth_relief(resolution="05m", region=[-92.5, -82.5, -3, 7])
but it returned the error:
[Session pygmt-session (27)]: Error returned from GMT API: GMT_FILE_NOT_FOUND (16)
[Session pygmt-session (27)]: Error returned from GMT API: GMT_GRID_READ_ERROR (18)
[Session pygmt-session (27)]: Error returned from GMT API: GMT_GRID_READ_ERROR (18)
IndexError Traceback (most recent call last)
Cell In[10], line 4
1 import pygmt
3 # Load sample earth relief data
----> 4 grid = pygmt.datasets.load_earth_relief(resolution="05m", region=[-92.5, -82.5, -3, 7])
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\helpers\decorators.py:773, in kwargs_to_strings.<locals>.converter.<locals>.new_module(*args, **kwargs)
770 bound.arguments["kwargs"][arg] = newvalue
772 # Execute the original function and return its output
--> 773 return module_func(*bound.args, **bound.kwargs)
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\datasets\earth_relief.py:168, in load_earth_relief(resolution, region, registration, data_source, use_srtm)
166 case "gebco" | "gebcosi":
167 name = "earth_gebco"
--> 168 grid = _load_remote_dataset(
169 name=name,
170 prefix=prefix,
171 resolution=resolution,
172 region=region,
173 registration=registration,
174 )
175 return grid
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\helpers\decorators.py:773, in kwargs_to_strings.<locals>.converter.<locals>.new_module(*args, **kwargs)
770 bound.arguments["kwargs"][arg] = newvalue
772 # Execute the original function and return its output
--> 773 return module_func(*bound.args, **bound.kwargs)
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\datasets\load_remote_dataset.py:418, in _load_remote_dataset(name, prefix, resolution, region, registration)
413 with lib.virtualfile_out(kind="grid") as voutgrd:
414 lib.call_module(
415 module="read",
416 args=[fname, voutgrd, *build_arg_list(kwdict)],
417 )
--> 418 grid = lib.virtualfile_to_raster(outgrid=None, vfname=voutgrd)
420 # Full path to the grid if not tiled grids.
421 source = which(fname, download="a") if not resinfo.tiled else None
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\clib\session.py:2021, in Session.virtualfile_to_raster(self, vfname, kind, outgrid)
2015 family = self.inquire_virtualfile(vfname)
2016 kind = { # type: ignore[assignment]
2017 self["GMT_IS_GRID"]: "grid",
2018 self["GMT_IS_IMAGE"]: "image",
2019 self["GMT_IS_CUBE"]: "cube",
2020 }[family]
-> 2021 return self.read_virtualfile(vfname, kind=kind).contents.to_dataarray()
File D:\anaconda\envs\pygmt\Lib\site-packages\pygmt\datatypes\grid.py:192, in _GMT_GRID.to_dataarray(self)
188 # Flip the coordinates and data if necessary so that coordinates are ascending.
189 # `grid.sortby(list(grid.dims))` sometimes causes crashes.
190 # The solution comes from https://github.com/pydata/xarray/discussions/6695.
191 for dim in grid.dims:
--> 192 if grid[dim][0] > grid[dim][1]:
193 grid = grid.isel({dim: slice(None, None, -1)})
195 # Set GMT accessors.
196 # Must put at the end, otherwise info gets lost after certain grid operations.
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\dataarray.py:901, in DataArray.__getitem__(self, key)
898 return self._getitem_coord(key)
899 else:
900 # xarray-style array indexing
--> 901 return self.isel(indexers=self._item_key_to_dict(key))
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\dataarray.py:1540, in DataArray.isel(self, indexers, drop, missing_dims, **indexers_kwargs)
1535 return self._from_temp_dataset(ds)
1537 # Much faster algorithm for when all indexers are ints, slices, one-dimensional
1538 # lists, or zero or one-dimensional np.ndarray's
-> 1540 variable = self._variable.isel(indexers, missing_dims=missing_dims)
1541 indexes, index_variables = isel_indexes(self.xindexes, indexers)
1543 coords = {}
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\variable.py:1049, in Variable.isel(self, indexers, missing_dims, **indexers_kwargs)
1046 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)
1048 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims)
-> 1049 return self[key]
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\variable.py:816, in Variable.__getitem__(self, key)
813 dims, indexer, new_order = self._broadcast_indexes(key)
814 indexable = as_indexable(self._data)
--> 816 data = indexing.apply_indexer(indexable, indexer)
818 if new_order:
819 data = np.moveaxis(data, range(len(new_order)), new_order)
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\indexing.py:1033, in apply_indexer(indexable, indexer)
1031 return indexable.oindex[indexer]
1032 else:
-> 1033 return indexable[indexer]
File D:\anaconda\envs\pygmt\Lib\site-packages\xarray\core\indexing.py:1798, in PandasIndexingAdapter.__getitem__(self, indexer)
1795 indexable = NumpyIndexingAdapter(np.asarray(self))
1796 return indexable[indexer]
-> 1798 result = self.array[key]
1800 return self._handle_result(result)
File D:\anaconda\envs\pygmt\Lib\site-packages\pandas\core\indexes\base.py:5389, in Index.__getitem__(self, key)
5386 if is_integer(key) or is_float(key):
5387 # GH#44051 exclude bool, which would return a 2d ndarray
5388 key = com.cast_scalar_indexer(key)
-> 5389 return getitem(key)
5391 if isinstance(key, slice):
5392 # This case is separated from the conditional above to avoid
5393 # pessimization com.is_bool_indexer and ndim checks.
5394 return self._getitem_slice(key)
IndexError: index 0 is out of bounds for axis 0 with size 0
How can I deal with it？
!