73 lines
1.1 KiB
Python
73 lines
1.1 KiB
Python
#!/usr/bin/env python
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# coding: utf-8
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# In[2]:
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get_ipython().run_line_magic('matplotlib', 'inline')
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from new_import import *
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# Dask gateway
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cluster, client = notebook_utils.initialize_dask(use_gateway=True, workers=(1,4))
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dc = datacube.Datacube()
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# Configure s3 access
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configure_s3_access(aws_unsigned=False, requester_pays=True, client=client)
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# In[3]:
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ds = dc.load(
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product="sentinel1_grd_gamma0_20m",
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x=(105.5, 106.4),
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y=(9.2, 10.0),
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time=("2022-09-01", "2023-10-01"),
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measurements=["vv", "vh"],
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output_crs="EPSG:32648",
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resolution=(-10,10),
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dask_chunks={"x":2048, "y":2048},
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skip_broken_datasets=True,
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group_by="solar_day"
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)
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notebook_utils.heading(notebook_utils.xarray_object_size(ds))
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ds
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# In[18]:
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vh = ds.vh.resample(time='1M').mean().persist()
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vh = vh.compute()
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vv = ds.vv.resample(time='1M').mean().persist()
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vv = vv.compute()
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# In[28]:
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vv.min()
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# In[33]:
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import matplotlib.pyplot as plt
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# Plot the data
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plt.imshow(vh.isel(time=0), cmap='viridis', vmin=0, vmax=1)
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plt.colorbar() # Add colorbar for reference
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plt.show()
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# In[ ]:
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