Event detection and classification (rain versus irrigation)

Contents

Event detection and classification (rain versus irrigation)#

License: CC-BY-4.0
Github: BenjMy/centum
Subject: Tutorial Authors:

Benjamin Mary Email: benjamin.mary@ica.csic.es
ORCID: 0000-0001-7199-2885
Affiliation: ICA-CSIC

Date: 2025/01/10

import numpy as np
import pooch
import xarray as xr
import centum
import matplotlib.pyplot as plt
import july
from july.utils import date_range
import pandas as pd

from centum import plotting as pltC
from centum.delineation import ETAnalysis

Irrigation delineation#

scenario_analysis_usingET = ETAnalysis()
decision_ds, event_type = scenario_analysis_usingET.irrigation_delineation(EO_scenario_AquaCrop_sc7_weather_reference_EO_ds)
dates_dt = [pd.to_datetime(date).to_pydatetime() for date in decision_ds.datetime.values]

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/xarray/core/dataset.py in ?(self, name)
   1512             variable = self._variables[name]
   1513         except KeyError:
-> 1514             _, name, variable = _get_virtual_variable(self._variables, name, self.sizes)
   1515 

KeyError: 'ETa'

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/xarray/core/dataset.py in ?(self, key)
   1622                 if isinstance(key, tuple):
   1623                     message += f"\nHint: use a list to select multiple variables, for example `ds[{list(key)}]`"
-> 1624                 raise KeyError(message) from e
   1625 

/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/xarray/core/dataset.py in ?(self, name)
   1512             variable = self._variables[name]
   1513         except KeyError:
-> 1514             _, name, variable = _get_virtual_variable(self._variables, name, self.sizes)
   1515 

/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/xarray/core/dataset.py in ?(variables, key, dim_sizes)
    219     split_key = key.split(".", 1)
    220     if len(split_key) != 2:
--> 221         raise KeyError(key)
    222 

KeyError: 'ETa'

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
/tmp/ipykernel_2091/2509827761.py in ?()
      1 scenario_analysis_usingET = ETAnalysis()
----> 2 decision_ds, event_type = scenario_analysis_usingET.irrigation_delineation(EO_scenario_AquaCrop_sc7_weather_reference_EO_ds)
      3 dates_dt = [pd.to_datetime(date).to_pydatetime() for date in decision_ds.datetime.values]

/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/centum-0.1.5-py3.10.egg/centum/delineation.py in ?(self, decision_ds, threshold_local, threshold_regional, time_window)
    379                                time_window=10,
    380                                ):
    381 
    382         # Compute local and regional ETa/ETp ratios
--> 383         decision_ds = self.compute_ratio_ETap_local(decision_ds,time_window=time_window)
    384         decision_ds = self.compute_ratio_ETap_regional(decision_ds,time_window=time_window)
    385 
    386         # Apply local and regional threshold decision rules

/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/centum-0.1.5-py3.10.egg/centum/delineation.py in ?(self, ds_analysis, ETa_name, ETp_name, time_window)
     54         xr.Dataset
     55             The dataset with added local ETa/ETp ratio and temporal differences.
     56         """
     57         # Compute the local ratio of ETa/ETp
---> 58         ds_analysis["ratio_ETap_local"] = ds_analysis[ETa_name] / ds_analysis[ETp_name]
     59 
     60         # Compute the absolute temporal difference of the local ratio
     61         ds_analysis["ratio_ETap_local_diff"] = abs(

/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/xarray/core/dataset.py in ?(self, key)
   1620 
   1621                 # If someone attempts `ds['foo' , 'bar']` instead of `ds[['foo', 'bar']]`
   1622                 if isinstance(key, tuple):
   1623                     message += f"\nHint: use a list to select multiple variables, for example `ds[{list(key)}]`"
-> 1624                 raise KeyError(message) from e
   1625 
   1626         if utils.iterable_of_hashable(key):
   1627             return self._copy_listed(key)

KeyError: "No variable named 'ETa'. Did you mean one of ('ETp',)?"

Show 2d result#

event_type_node_IN = event_type.mean(['x','y'])
reference_date = pd.Timestamp("2025-01-01")
datetime = pd.to_datetime(reference_date + event_type_node_IN.time)

fig, axs = plt.subplots(2,1,sharex=True,figsize=(7,4))

july.heatmap(datetime, 
             irrigation_districts_grid['irr_daily'].sum(['x','y']), 
             title='Irrigation (mm/h)',
             cmap="github",
             colorbar=True,
             ax=axs[0]
             )
july.heatmap(datetime, 
             irrigation_districts_grid['rain_daily'].sum(['x','y']), 
             title='Rain (mm/h)',
             cmap="golden",
             colorbar=True,
             ax=axs[1]
             )

<Axes: title={'center': 'Rain (mm/h)'}>

../_images/7ecf569719ffdfec835d9d32d23d83a85abe399ea311d9e3f30fb0240f6372d4.png

fig, ax = plt.subplots(figsize=(7,4))

im = july.heatmap(dates_dt, 
              event_type_node_IN.values, 
              title='Irrigation detected',
              # cmap=white_cmap,
              ax=ax,
              linewidth=1, 
              value_label=True,
              )

../_images/83d56f98a6ac3578e8ea90125b0fc43a83cb79068d1713b32112780977d16e9a.png