diff --git a/v0.9.2/_examples/delineate_basin.html b/v0.9.2/_examples/delineate_basin.html index 8e74d6e1c..2aceca506 100644 --- a/v0.9.2/_examples/delineate_basin.html +++ b/v0.9.2/_examples/delineate_basin.html @@ -563,7 +563,7 @@

Import packages
-2024-01-31 08:52:57,468 - basin_delineation - log - INFO - HydroMT version: 0.9.2
+2024-01-31 09:12:13,120 - basin_delineation - log - INFO - HydroMT version: 0.9.2
 
@@ -585,7 +585,7 @@

Read data
-2024-01-31 08:52:57,495 - basin_delineation - data_catalog - INFO - Reading data catalog archive artifact_data v0.0.8
+2024-01-31 09:12:13,148 - basin_delineation - data_catalog - INFO - Reading data catalog archive artifact_data v0.0.8
 
diff --git a/v0.9.2/_examples/doing_extreme_value_analysis.html b/v0.9.2/_examples/doing_extreme_value_analysis.html index e2d6e5101..75b57c95f 100644 --- a/v0.9.2/_examples/doing_extreme_value_analysis.html +++ b/v0.9.2/_examples/doing_extreme_value_analysis.html @@ -925,17 +925,17 @@

Example: Doing Extreme Value Analysis (EVA) for time series @@ -1371,8 +1371,8 @@

Step 2: fit a EV distribution on these peaks @@ -1890,27 +1890,27 @@

TL;DR#< return_values (stations, rps) float64 1.426e+03 2.252e+03 ... 2.193e+03 Attributes: long_name: discharge - units: m3/s
  • stations
    PandasIndex
    PandasIndex(Index([1, 2], dtype='int32', name='stations'))
  • dparams
    PandasIndex
    PandasIndex(Index(['shape', 'loc', 'scale'], dtype='object', name='dparams'))
  • rps
    PandasIndex
    PandasIndex(Index([2, 5, 25, 100, 500], dtype='int64', name='rps'))
  • long_name :
    discharge
    units :
    m3/s
  • diff --git a/v0.9.2/_examples/export_data.html b/v0.9.2/_examples/export_data.html index b30bfc877..85f52096b 100644 --- a/v0.9.2/_examples/export_data.html +++ b/v0.9.2/_examples/export_data.html @@ -536,7 +536,7 @@

    Example: Exporting data from a data catalog
    -2024-01-31 08:53:20,540 - export data - log - INFO - HydroMT version: 0.9.2
    +2024-01-31 09:12:37,321 - export data - log - INFO - HydroMT version: 0.9.2
     
    @@ -560,7 +560,7 @@

    Explore the current data catalog
    -2024-01-31 08:53:20,566 - export data - data_catalog - INFO - Reading data catalog archive artifact_data v0.0.8
    +2024-01-31 09:12:37,349 - export data - data_catalog - INFO - Reading data catalog archive artifact_data v0.0.8
     

    The artifact_data catalog is one of the pre-defined available DataCatalog of HydroMT. You can find an overview of pre-defined data catalogs in the online user guide. You can also get an overview of the pre-defined catalogs with their version number from HydroMT.

    @@ -647,7 +647,7 @@

    Explore the current data catalog
    -2024-01-31 08:53:20,627 - export data - rasterdataset - INFO - Reading era5 netcdf data from /home/runner/.hydromt_data/artifact_data/v0.0.8/era5.nc
    +2024-01-31 09:12:37,412 - export data - rasterdataset - INFO - Reading era5 netcdf data from /home/runner/.hydromt_data/artifact_data/v0.0.8/era5.nc
     

    @@ -1929,7 +1929,7 @@

    Open and explore the exported data
    -2024-01-31 08:53:21,086 - export data - rasterdataset - INFO - Reading merit_hydro raster data from /home/runner/.hydromt_data/artifact_data/v0.0.8/merit_hydro/{variable}.tif
    +2024-01-31 09:12:37,889 - export data - rasterdataset - INFO - Reading merit_hydro raster data from /home/runner/.hydromt_data/artifact_data/v0.0.8/merit_hydro/{variable}.tif
     

    The steps to use your own data within HydroMT are in brief:

    @@ -667,7 +667,7 @@

    RasterDataset from raster file
    -<matplotlib.collections.QuadMesh at 0x7f347149e390>
    +<matplotlib.collections.QuadMesh at 0x7f40bf44d410>
     
    @@ -4423,12 +4423,12 @@

    GeoDataset from a netcdf file @@ -4484,7 +4484,7 @@

    GeoDataset from a netcdf file
    -2024-01-31 08:53:33,464 - prepare data catalog - data_catalog - INFO - Parsing data catalog from tmpdir/gtsm.yml
    +2024-01-31 09:12:51,202 - prepare data catalog - data_catalog - INFO - Parsing data catalog from tmpdir/gtsm.yml
     
    @@ -993,7 +993,7 @@

    Netcdf or zarr driver + dtype='int32', name='stations'))
  • category :
    ocean
    paper_doi :
    10.24381/cds.8c59054f
    paper_ref :
    Copernicus Climate Change Service 2019
    source_license :
    https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products
    source_url :
    https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.8c59054f?tab=overview
    source_version :
    GTSM v3.0
  • The data can be visualized with the .plot() xarray method. We show the evolution of the water level over time for a specific point location (station).

    @@ -1602,7 +1602,7 @@

    Netcdf or zarr driver