Exercise 2: Using best fit methods in gwrefpy#

This notebook introduces how to use the best fit method for a large gwrefpy model.

This notebook can be downloaded from the source code here.

In this exercise, you will:

  1. Import the gwrefpy package and load the model (already done for you)

  2. Fit the model

  3. Plot the results

1. Import the gwrefpy package and load the data#

import gwrefpy as gr

model = gr.Model('large_example.gwref') # Load an example model for the package
model.fits = [] # Clear any fits that may be present in the example model
model.wells_summary()

Model 'Large Example' loaded from 'large_example.gwref'.
name well_type data_points start_date end_date mean_level latest_value latest_date latitude longitude elevation best_fit_ref_well best_rmse num_fits avg_rmse
0 01OBS observation 112 2020-01-01 2020-04-21 11.753155 11.562414 2020-04-21 None None None None None NaN NaN
1 02OBS observation 80 2020-01-01 2020-03-20 12.931890 12.925313 2020-03-20 None None None None None NaN NaN
2 03OBS observation 95 2020-01-01 2020-04-04 14.096635 14.106713 2020-04-04 None None None None None NaN NaN
3 04OBS observation 93 2020-01-01 2020-04-02 15.277157 15.287510 2020-04-02 None None None None None NaN NaN
4 05OBS observation 105 2020-01-01 2020-04-14 16.442842 16.579736 2020-04-14 None None None None None NaN NaN
5 06OBS observation 82 2020-01-01 2020-03-22 17.621488 17.655653 2020-03-22 None None None None None NaN NaN
6 07OBS observation 116 2020-01-01 2020-04-25 18.796522 18.716346 2020-04-25 None None None None None NaN NaN
7 08OBS observation 81 2020-01-01 2020-03-21 19.976834 20.053553 2020-03-21 None None None None None NaN NaN
8 09OBS observation 95 2020-01-01 2020-04-04 21.156969 20.993342 2020-04-04 None None None None None NaN NaN
9 10OBS observation 100 2020-01-01 2020-04-09 22.316877 22.388860 2020-04-09 None None None None None NaN NaN
10 11OBS observation 104 2020-01-01 2020-04-13 23.514971 23.588313 2020-04-13 None None None None None NaN NaN
11 12OBS observation 88 2020-01-01 2020-03-28 24.666201 24.744872 2020-03-28 None None None None None NaN NaN
12 01REF reference 112 2020-01-01 2020-04-21 8.759759 8.747352 2020-04-21 None None None NaN NaN 0.0 None
13 02REF reference 80 2020-01-01 2020-03-20 9.620159 9.607570 2020-03-20 None None None NaN NaN 0.0 None
14 03REF reference 95 2020-01-01 2020-04-04 10.494114 10.446796 2020-04-04 None None None NaN NaN 0.0 None
15 04REF reference 93 2020-01-01 2020-04-02 11.375509 11.427661 2020-04-02 None None None NaN NaN 0.0 None
16 05REF reference 105 2020-01-01 2020-04-14 12.253849 12.174917 2020-04-14 None None None NaN NaN 0.0 None
17 06REF reference 82 2020-01-01 2020-03-22 13.129146 13.109889 2020-03-22 None None None NaN NaN 0.0 None
18 07REF reference 116 2020-01-01 2020-04-25 13.999060 14.108201 2020-04-25 None None None NaN NaN 0.0 None
19 08REF reference 81 2020-01-01 2020-03-21 14.880381 14.838350 2020-03-21 None None None NaN NaN 0.0 None
20 09REF reference 95 2020-01-01 2020-04-04 15.745920 15.777444 2020-04-04 None None None NaN NaN 0.0 None
21 10REF reference 100 2020-01-01 2020-04-09 16.625979 16.671081 2020-04-09 None None None NaN NaN 0.0 None
22 11REF reference 104 2020-01-01 2020-04-13 17.500392 17.443029 2020-04-13 None None None NaN NaN 0.0 None
23 12REF reference 88 2020-01-01 2020-03-28 18.375225 18.342771 2020-03-28 None None None NaN NaN 0.0 None

2. Use the best fit method to fit the model#

# Use the best fit method here to fit the model

3. Plot the results#

# Plot the results here