Hi everyone,

I'm trying to perform a decimated read of a dataset that already contains overviews. Regardless of which value I pass to the resampling= argument of the read method, it seems that the already existing overview is used. Is there any way to ignore it? See the reproducible example below.

Cheers,
Loïc

---

import tempfile
import os

import numpy as np
import rasterio
from rasterio.enums import Resampling


filename = os.path.join(tempfile.gettempdir(), 'overview_test.tif')

# Create random int array
shape = (100, 100)
arr = np.random.randint(0, 9999, size=shape, dtype=np.uint16)

meta = {'height': 100,
        'width': 100,
        'driver': 'GTiff',
        'dtype': np.uint16,
        'count': 1}

# Write random array to file and compute first overview
with rasterio.open(filename, 'w', **meta) as dst:
    dst.write(arr, 1)
    dst.build_overviews([2], Resampling.nearest)

# Read with downsample
with rasterio.open(filename) as src:
    arr_avg = src.read(1, out_shape=(1,50,50), resampling=Resampling.average,
                        out_dtype=np.float)
    arr_nrt = src.read(1, out_shape=(1,50,50), resampling=Resampling.nearest)

print(np.max(arr_avg - arr_nrt))
# when the source file does not contain overviews, the max of the difference array
# is > 0

--

Thank you!

I have install rasterio with pip3 install rasterio --no-binary rasterio
When I'm trying to read an HDF4 MODIS file I get an error:

Matplotlib created a temporary config/cache directory at /tmp/matplotlib-m5kstvas because the default path (/home/kokkytos/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
Traceback (most recent call last):
File "rasterio/_base.pyx", line 216, in rasterio._base.DatasetBase.init
File "rasterio/_shim.pyx", line 67, in rasterio._shim.open_dataset
File "rasterio/_err.pyx", line 205, in rasterio._err.exc_wrap_pointer
rasterio._err.CPLE_OpenFailedError: 'MOD11A1.A2014152.h18v04.006.2016204003609.hdf' not recognized as a supported file format.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/bin/rio", line 8, in
sys.exit(main_group())
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 1259, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/click/decorators.py", line 21, in new_func
return f(get_current_context(), *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/rasterio/rio/info.py", line 66, in info
with ctx.obj['env'], rasterio.open(input) as src:
File "/usr/local/lib/python3.7/dist-packages/rasterio/env.py", line 433, in wrapper
return f(*args, **kwds)
File "/usr/local/lib/python3.7/dist-packages/rasterio/init.py", line 218, in open
s = DatasetReader(path, driver=driver, sharing=sharing, **kwargs)
File "rasterio/_base.pyx", line 218, in rasterio._base.DatasetBase.init
rasterio.errors.RasterioIOError: 'MOD11A1.A2014152.h18v04.006.2016204003609.hdf' not recognized as a supported file format.

Thank you for this. It's been bugging for quite some time.
I use it here: https://gitlab.com/thermopolis/public/ecor/-/blob/master/ecor/utilities.py.

I have the same question, as this snippet need to appear in every function that `rasterio.open()`s a HDF5 (sub)dataset:
is there a more elegant way to silence this warning?

Cheers

This should be fixed in 1.1.5 IIRC: #1248

Hi all: as part of using rasterio for OGC API - Coverages work in pygeoapi, a client can pass a bbox parameter as a shortcut to spatially subset a coverage using lat/long coordinates. The idea here, then, is that lat/long coordinates would be reprojected into the data source's native coordinates and then the coverage would be subsetted accordingly.

Having said this, using example files in https://dd.weather.gc.ca/model_hrdps/continental/grib2/06/002, I'm unable to derive the native crs from rasterio in Python:

>>> import rasterio
>>> ds = rasterio.open('CMC_hrdps_continental_HGT_ISBL_0985_ps2.5km_2020102706_P002-00.grib2')
>>> ds.bounds
BoundingBox(left=-0.5, bottom=1455.5, right=2575.5, top=-0.5)
>>> ds.crs
>>> ds.crs is None
True
>>> 

However, when running through rio info, I am able to see bounds and CRS:

$ rio info CMC_hrdps_continental_HGT_ISBL_0985_ps2.5km_2020102706_P002-00.grib2
WARNING:rasterio._env:CPLE_AppDefined in Unable to perform coordinate transformations, so the correct projected geotransform could not be deduced from the lat/long control points.  Defaulting to ungeoreferenced.
{"bounds": [-2099127.4944969374, -5739388.521499627, 4340872.505503062, -2099388.5214996273], "colorinterp": ["undefined"], "count": 1, "crs": "PROJCS[\"unnamed\",GEOGCS[\"Coordinate System imported from GRIB file\",DATUM[\"unknown\",SPHEROID[\"Sphere\",6371229,0]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.0174532925199433]],PROJECTION[\"Polar_Stereographic\"],PARAMETER[\"latitude_of_origin\",60],PARAMETER[\"central_meridian\",252],PARAMETER[\"scale_factor\",1],PARAMETER[\"false_easting\",0],PARAMETER[\"false_northing\",0],UNIT[\"Metre\",1]]", "descriptions": ["98500[Pa] ISBL=\"Isobaric surface\""], "driver": "GRIB", "dtype": "float64", "height": 1456, "indexes": [1], "lnglat": [-92.0404517295466, 52.147885433427845], "mask_flags": [["nodata"]], "nodata": 9999.0, "res": [2500.0, 2500.0], "shape": [1456, 2576], "tiled": false, "transform": [2500.0, 0.0, -2099127.4944969374, 0.0, -2500.0, -2099388.5214996273, 0.0, 0.0, 1.0], "units": [null], "width": 2576}

I need the crs value to be able to reproject the incoming lat/long bbox into native coordinates to subset accordingly. Is there a way to set a given dataset's CRS through code (in readonly mode)?

Thanks

..Tom

I believe that this is what you are looking for: https://rasterio.readthedocs.io/en/latest/topics/resampling.html