Commit b040846d authored by Wit, Allard de's avatar Wit, Allard de
Browse files

- Updated the readme on grompy commandline

parent 5e1f40c1
......@@ -28,7 +28,7 @@ This includes the paths to the different CSV files, the path to the shapefile wi
the URI for the database where the data have to be written. The `grompy.yaml` file is the entry point for all
other grompy operations as well as the `DataAccessProvider`.
The `grompy.yaml` file can be generated with the command `grompy init <data path>` and for doing so, grompy assumes
The `grompy.yaml` file can be generated with the command `grompy init <year> <data path>` and for doing so, grompy assumes
a certain folder structure which looks like this:
```
<data path> /BRP/gewaspercelen_<year>.shp
......@@ -36,11 +36,13 @@ a certain folder structure which looks like this:
/Radar/ - CSV with radar data
```
In practice it is most convenient to keep the `grompy.yaml` file together with the data. So change directory
In practice it is most convenient to keep the `grompy.yaml` file together with the data and use paths relative
to the location of the `grompy.yaml` file. In this way you can copy to the grompy.yaml file and the corresponding
database to another location without having to edit the `grompy.yaml` file. So change directory
to the data folder and execute:
```commandline
cd <data path>
grompy init .
grompy init 2019 .
```
The init command creates the `grompy.yaml` and sets the path to the inputs/outputs based on the input
......@@ -49,30 +51,30 @@ for `<data path>`. In this case, the current directory `.`. The `grompy.yaml` no
grompy:
version: 1.0
parcel_info:
dsn: sqlite:////home/wit015/Data/groenmonitor/parcel_info.db3
counts_file: /home/wit015/Data/groenmonitor/Optisch/perceelscount.csv
shape_file: /home/wit015/Data/groenmonitor/BRP/gewaspercelen_2019.shp
dsn: sqlite:///./parcel_info.db3
counts_file: ./Optisch/perceelscount.csv
shape_file: ./BRP/gewaspercelen_2019.shp
table_name: parcel_info
datasets:
sentinel2_reflectance_values:
dsn: sqlite:////home/wit015/Data/groenmonitor/sentinel2_reflectance_values.db3
dsn: sqlite:///./sentinel2_reflectance_values.db3
bands:
NDVI: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_2019_ADC.csv
B02: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B02_2019_ADC.csv
B03: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B03_2019_ADC.csv
B04: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B04_2019_ADC.csv
B05: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B05_2019_ADC.csv
B06: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B06_2019_ADC.csv
B07: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B07_2019_ADC.csv
B08: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B08_2019_ADC.csv
B11: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B11_2019_ADC.csv
B12: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B12_2019_ADC.csv
B8A: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_mean_B8A_2019_ADC.csv
NDVI: ./Optisch/zonal_stats_mean_2019_ADC.csv
B02: ./Optisch/zonal_stats_mean_B02_2019_ADC.csv
B03: ./Optisch/zonal_stats_mean_B03_2019_ADC.csv
B04: ./Optisch/zonal_stats_mean_B04_2019_ADC.csv
B05: ./Optisch/zonal_stats_mean_B05_2019_ADC.csv
B06: ./Optisch/zonal_stats_mean_B06_2019_ADC.csv
B07: ./Optisch/zonal_stats_mean_B07_2019_ADC.csv
B08: ./Optisch/zonal_stats_mean_B08_2019_ADC.csv
B11: ./Optisch/zonal_stats_mean_B11_2019_ADC.csv
B12: ./Optisch/zonal_stats_mean_B12_2019_ADC.csv
B8A: ./Optisch/zonal_stats_mean_B8A_2019_ADC.csv
sentinel2_reflectance_std:
dsn: sqlite:////home/wit015/Data/groenmonitor/sentinel2_reflectance_std.db3
dsn: sqlite:///./sentinel2_reflectance_std.db3
bands:
NDVI: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_std_2019_ADC.csv
B02: /home/wit015/Data/groenmonitor/Optisch/zonal_stats_std_B02_2019_ADC.csv
NDVI: ./Optisch/zonal_stats_std_2019_ADC.csv
B02: ./Optisch/zonal_stats_std_B02_2019_ADC.csv
...
```
The `grompy.yaml` file specifies several sections:
......@@ -103,13 +105,13 @@ The `grompy.yaml` is a relatively complex input structure and manually checking
Therefore, grompy can check if the YAML file is OK by executing:
```commandline
grompy check
grompy check <grompy_yaml>
```
It assumes that the `grompy.yaml` resides in the current directory. Grompy will now read the YAML and carry out
several checks, including:
Grompy will now read the YAML and carry out several checks, including:
- If files exists.
- If connections to database can be opened.
- If the CSV files of the different datasets all have the same number of lines.
- If the shapefile with parcel info has the required attributes.
Grompy will display a lot of output on the screen. If everything is fine, the last line will show:
```commandline
......@@ -125,8 +127,7 @@ run `grompy check` first.
### loading
The final step is to load the parcel information and satellite observations into the database tables. This can be
done with the `grompy load` command. Also here grompy assumes that the `grompy.yaml` file resides in the current
directory. Grompy will now show the following output:
done with the `grompy load <grompy_yaml>` command. Grompy will now show the following output:
```commandline
Start loading parcel information. This will take some time...
Starting loading of: sentinel1_backscatter
......
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