Welcome to examples of ai4water’ Experiments module!
Experiments
The basic purpose of the experiments module of ai4water is comparison. It can be used for following scenarios
- Comparison between different machine learning algorithms for a classification or regression task.
This can be done using
MLRegressionExperimentsorMLClassificationExperimentsclass.
- Comparison between different neural network architectures for a classification or a regression task.
This can be done using
DLRegressionExperimentsorDLClassificationExperimentsclasses.
- Test a single algorithm in different scenarios e.g., by applying different transformations on a feature and compare the results
A use case is shown with
TransformationExperimentsclass.
- Optimize the hyperparameters of multiple models. This can be done by setting
run_typetooptimize in
experimnnt.fitmethod.
- Optimize the hyperparameters of multiple models. This can be done by setting
All the classes inherit from Experiments class.
Comparison of XGBRegressor with different transformations
Comparison of XGBRegressor with different transformations
Note
Click here to download the full example code
Machine learning algorithms for classification
# import site
# site.addsitedir("D:\\mytools\\AI4Water")
from ai4water.datasets import MtropicsLaos
from ai4water.experiments import MLClassificationExperiments
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/experimental/enable_hist_gradient_boosting.py:17: UserWarning: Since version 1.0, it is not needed to import enable_hist_gradient_boosting anymore. HistGradientBoostingClassifier and HistGradientBoostingRegressor are now stable and can be normally imported from sklearn.ensemble.
"Since version 1.0, "
dataset = MtropicsLaos()
#data = dataset.make_classification(lookback_steps=1)
#print(data.shape)
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unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/rain_guage.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/rain_guage
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/hydro.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/hydro
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/suro.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/suro
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/subs1.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/subs1
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/surf_feat.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/surf_feat
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/pcp.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/pcp
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/weather_station.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/weather_station
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/soilmap.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/soilmap
unzipping /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/lu.zip to /home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos/lu
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/mtropics.py:817: UserWarning: preprocessing of shapefiles can not be done because no fiona installation is found.
warnings.warn("preprocessing of shapefiles can not be done because no fiona installation is found.")
inputs = data.columns.tolist()[0:-1] outputs = data.columns.tolist()[-1:]
- exp = MLClassificationExperiments(
input_features=inputs, output_features=outputs, epochs=5, save=False
)
- exp.fit(data=data,
exclude=[‘LinearDiscriminantAnalysis’])
exp.plot_cv_scores(data=data)
exp.compare_precision_recall_curves(data[inputs].values, data[outputs].values)
Total running time of the script: ( 0 minutes 56.972 seconds)
Note
Click here to download the full example code
Neural Networks for classification
from ai4water.hyperopt import Categorical
from ai4water.datasets import MtropicsLaos
from ai4water.experiments import DLClassificationExperiments
dataset = MtropicsLaos()
#lookback = 5
#data = dataset.make_classification(lookback_steps=lookback)
#print(data.shape)
Not downloading the data since the directory
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/data/MtropicsLaos already exists.
Use overwrite=True to remove previously saved files and download again
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/datasets/mtropics.py:817: UserWarning: preprocessing of shapefiles can not be done because no fiona installation is found.
warnings.warn("preprocessing of shapefiles can not be done because no fiona installation is found.")
inputs = data.columns.tolist()[0:-1] outputs = data.columns.tolist()[-1:]
- exp = DLClassificationExperiments(
input_features=inputs, output_features=outputs, epochs=50, ts_args={“lookback”: lookback}, save=False
)
- exp.batch_size_space = Categorical(categories=[4, 8, 12, 16, 32],
name=”batch_size”)
- exp.fit(data=data,
include=[“MLP”, “CNN”, “LSTM”, “TFT”])
#exp.compare_errors('accuracy', data=data)
Total running time of the script: ( 0 minutes 0.001 seconds)
Note
Click here to download the full example code
Comparison of machine learning algorithms
from ai4water.datasets import busan_beach
from ai4water.utils.utils import get_version_info
from ai4water.experiments import MLRegressionExperiments
for k,v in get_version_info().items():
print(f"{k} version: {v}")
python version: 3.7.9 (default, Oct 19 2020, 15:13:17)
[GCC 7.5.0]
os version: posix
ai4water version: 1.06
lightgbm version: 3.3.5
tcn version: 3.5.0
catboost version: 1.1.1
xgboost version: 1.6.2
easy_mpl version: 0.21.2
SeqMetrics version: 1.3.4
tensorflow version: 2.7.0
keras.api._v2.keras version: 2.7.0
numpy version: 1.21.1
pandas version: 1.3.4
matplotlib version: 3.5.3
h5py version: 3.8.0
joblib version: 1.2.0
data = busan_beach()
print(data)
tide_cm wat_temp_c ... rel_hum tetx_coppml
index ...
2018-06-19 00:00:00 36.407149 19.321232 ... 95.000000 NaN
2018-06-19 00:30:00 35.562515 19.320124 ... 95.000000 NaN
2018-06-19 01:00:00 34.808016 19.319666 ... 95.000000 NaN
2018-06-19 01:30:00 30.645216 19.320406 ... 95.006667 NaN
2018-06-19 02:00:00 26.608980 19.326729 ... 95.006667 NaN
... ... ... ... ... ...
2019-09-07 22:00:00 -3.989912 20.990612 ... 88.170000 NaN
2019-09-07 22:30:00 -2.807042 21.012014 ... 88.256667 NaN
2019-09-07 23:00:00 -3.471326 20.831739 ... 87.833333 NaN
2019-09-07 23:30:00 0.707771 21.006086 ... 88.370000 NaN
2019-09-08 00:00:00 1.011731 20.896149 ... 87.700000 NaN
[1446 rows x 14 columns]
comparisons = MLRegressionExperiments(
input_features=data.columns.tolist()[0:-1],
output_features=data.columns.tolist()[-1:],
split_random=True,
verbosity=0,
save=False,
)
comparisons.fit(data=data,
run_type="dry_run")
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
running ARDRegression model
running AdaBoostRegressor model
running BaggingRegressor model
running BayesianRidge model
running CatBoostRegressor model
running DecisionTreeRegressor model
running DummyRegressor model
running ElasticNet model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.332e+14, tolerance: 2.710e+11
coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running ElasticNetCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
running ExtraTreeRegressor model
running ExtraTreesRegressor model
running GaussianProcessRegressor model
running GradientBoostingRegressor model
running HistGradientBoostingRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running HuberRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_huber.py:332: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running KNeighborsRegressor model
running KernelRidge model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_ridge.py:197: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.
"Singular matrix in solving dual problem. Using "
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running LGBMRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running Lars model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), Lars())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
FutureWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running LarsCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), LarsCV())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
FutureWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
running Lasso model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.650e+14, tolerance: 2.710e+10
coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running LassoCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
running LassoLars model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), LassoLars())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
Set parameter alpha to: original_alpha * np.sqrt(n_samples).
FutureWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running LassoLarsCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), LassoLarsCV())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
Set parameter alpha to: original_alpha * np.sqrt(n_samples).
FutureWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
running LassoLarsIC model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), LassoLarsIC())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
Set parameter alpha to: original_alpha * np.sqrt(n_samples).
FutureWarning,
running LinearRegression model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running LinearSVR model
running MLPRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neural_network/_multilayer_perceptron.py:696: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.
ConvergenceWarning,
running NuSVR model
running OneClassSVM model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running OrthogonalMatchingPursuit model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), OrthogonalMatchingPursuit())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
FutureWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_omp.py:766: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
return_n_iter=True,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running OrthogonalMatchingPursuitCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_base.py:138: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), OrthogonalMatchingPursuitCV())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
FutureWarning,
running PoissonRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_glm/glm.py:323: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
self.n_iter_ = _check_optimize_result("lbfgs", opt_res)
running RANSACRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running RadiusNeighborsRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/experiments/_main.py:2230: UserWarning: model RadiusNeighborsRegressor predicted only nans
warnings.warn(f"model {model.model_name} predicted only nans")
running RandomForestRegressor model
running Ridge model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running RidgeCV model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running SGDRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running SVR model
running TheilsenRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_theil_sen.py:131: ConvergenceWarning: Maximum number of iterations 50 reached in spatial median for TheilSen regressor.
ConvergenceWarning,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running TweedieRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/linear_model/_glm/glm.py:323: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
self.n_iter_ = _check_optimize_result("lbfgs", opt_res)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running XGBRFRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
running XGBRegressor model
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
comparisons.compare_errors('r2', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
best_models = comparisons.compare_errors(
'r2',
data=data,
cutoff_type='greater',
cutoff_val=0.01)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
comparisons.taylor_plot(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
<Figure size 900x700 with 2 Axes>
comparisons.taylor_plot(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
<Figure size 900x700 with 2 Axes>
comparisons.compare_edf_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
comparisons.compare_edf_plots(data=data, exclude=["SGDRegressor", "KernelRidge", "PoissonRegressor"])
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
comparisons.compare_regression_plots(data=data, figsize=(12, 14))
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
Model RadiusNeighborsRegressor only predicted nans
comparisons.compare_residual_plots(data=data, figsize=(12, 14))
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/sklearn/neighbors/_regression.py:470: UserWarning: One or more samples have no neighbors within specified radius; predicting NaN.
warnings.warn(empty_warning_msg)
<Figure size 1200x1400 with 49 Axes>
Total running time of the script: ( 2 minutes 13.912 seconds)
Note
Click here to download the full example code
Comparison of deep learning architectures
from ai4water.datasets import busan_beach
from ai4water.utils.utils import get_version_info
from ai4water.experiments import DLRegressionExperiments
for k,v in get_version_info().items():
print(f"{k} version: {v}")
python version: 3.7.9 (default, Oct 19 2020, 15:13:17)
[GCC 7.5.0]
os version: posix
ai4water version: 1.06
lightgbm version: 3.3.5
tcn version: 3.5.0
catboost version: 1.1.1
xgboost version: 1.6.2
easy_mpl version: 0.21.2
SeqMetrics version: 1.3.4
tensorflow version: 2.7.0
keras.api._v2.keras version: 2.7.0
numpy version: 1.21.1
pandas version: 1.3.4
matplotlib version: 3.5.3
h5py version: 3.8.0
joblib version: 1.2.0
data = busan_beach()
print(data)
tide_cm wat_temp_c ... rel_hum tetx_coppml
index ...
2018-06-19 00:00:00 36.407149 19.321232 ... 95.000000 NaN
2018-06-19 00:30:00 35.562515 19.320124 ... 95.000000 NaN
2018-06-19 01:00:00 34.808016 19.319666 ... 95.000000 NaN
2018-06-19 01:30:00 30.645216 19.320406 ... 95.006667 NaN
2018-06-19 02:00:00 26.608980 19.326729 ... 95.006667 NaN
... ... ... ... ... ...
2019-09-07 22:00:00 -3.989912 20.990612 ... 88.170000 NaN
2019-09-07 22:30:00 -2.807042 21.012014 ... 88.256667 NaN
2019-09-07 23:00:00 -3.471326 20.831739 ... 87.833333 NaN
2019-09-07 23:30:00 0.707771 21.006086 ... 88.370000 NaN
2019-09-08 00:00:00 1.011731 20.896149 ... 87.700000 NaN
[1446 rows x 14 columns]
comparisons = DLRegressionExperiments(
input_features=data.columns.tolist()[0:-1],
output_features=data.columns.tolist()[-1:],
split_random=True,
val_fraction=0.0,
epochs=200,
ts_args={"lookback": 12},
verbosity=0,
save=False,
)
comparisons.fit(data=data,
include=['MLP',
'LSTM',
'CNNLSTM',
'TCN',
"TFT",
"LSTMAutoEncoder",
])
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
running MLP model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
running LSTM model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
running CNNLSTM model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
running TCN model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
running TFT model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
running LSTMAutoEncoder model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
comparisons.compare_errors('r2', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
best_models = comparisons.compare_errors(
'r2',
data=data,
cutoff_type='greater',
cutoff_val=0.01)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
comparisons.taylor_plot(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
<Figure size 900x700 with 2 Axes>
comparisons.compare_edf_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
comparisons.compare_regression_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
comparisons.compare_residual_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (152, 12, 13)
target shape: (152, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (0,)
target shape: (0,)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 12, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/_main.py:1982: UserWarning:
argument test is deprecated and will be removed in future. Please
use 'predict_on_test_data' method instead.
use 'predict_on_{data}_data' method instead.""")
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
<Figure size 640x480 with 6 Axes>
comparisons.loss_comparison()
<AxesSubplot:>
Total running time of the script: ( 4 minutes 31.377 seconds)
Note
Click here to download the full example code
Comparison of LSTM with different transformations
from ai4water.models import LSTM
from ai4water.utils.utils import get_version_info
from ai4water.experiments import TransformationExperiments
from ai4water.hyperopt import Categorical, Integer
from ai4water.utils.utils import dateandtime_now
from ai4water.datasets import busan_beach
for k,v in get_version_info().items():
print(f"{k} version: {v}")
python version: 3.7.9 (default, Oct 19 2020, 15:13:17)
[GCC 7.5.0]
os version: posix
ai4water version: 1.06
lightgbm version: 3.3.5
tcn version: 3.5.0
catboost version: 1.1.1
xgboost version: 1.6.2
easy_mpl version: 0.21.2
SeqMetrics version: 1.3.4
tensorflow version: 2.7.0
keras.api._v2.keras version: 2.7.0
numpy version: 1.21.1
pandas version: 1.3.4
matplotlib version: 3.5.3
h5py version: 3.8.0
joblib version: 1.2.0
lookback = 14
data = busan_beach()
input_features = data.columns.tolist()[0:-1]
output_features = data.columns.tolist()[-1:]
class MyTransformationExperiments(TransformationExperiments):
def update_paras(self, **kwargs):
_layers = LSTM(units=kwargs['units'],
input_shape=(lookback, len(input_features)),
activation=kwargs['activation'])
y_transformation = kwargs['y_transformation']
if y_transformation == "none":
y_transformation = None
return {
'model': _layers,
'batch_size': int(kwargs['batch_size']),
'lr': float(kwargs['lr']),
'y_transformation': y_transformation
}
cases = {
'model_None': {'y_transformation': 'none'},
'model_minmax': {'y_transformation': 'minmax'},
'model_zscore': {'y_transformation': 'zscore'},
'model_robust': {'y_transformation': 'robust'},
'model_quantile': {'y_transformation': 'quantile'},
'model_log': {'y_transformation': {'method':'log', 'treat_negatives': True, 'replace_zeros': True}},
"model_pareto": {"y_transformation": "pareto"},
"model_vast": {"y_transformation": "vast"},
"model_mmad": {"y_transformation": "mmad"}
}
search_space = [
Integer(low=10, high=30, name='units', num_samples=10),
Categorical(categories=['relu', 'elu', 'tanh', "linear"], name='activation'),
Categorical(categories=[4, 8, 12, 16, 24, 32], name='batch_size'),
Categorical(categories=[0.05, 0.02, 0.009, 0.007, 0.005,
0.003, 0.001, 0.0009, 0.0007, 0.0005, 0.0003,
0.0001, 0.00009, 0.00007, 0.00005], name='lr'),
]
x0 = [16, "relu", 32, 0.0001]
experiment = MyTransformationExperiments(
cases=cases,
input_features=input_features,
output_features = output_features,
param_space=search_space,
x0=x0,
verbosity=0,
epochs=100,
exp_name = f"ecoli_lstm_y_exp_{dateandtime_now()}",
ts_args={"lookback": lookback},
save=False
)
experiment.fit(data = data, run_type='dry_run')
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
running None model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
running minmax model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:959: RuntimeWarning: overflow encountered in square
s = s**2
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:959: RuntimeWarning: overflow encountered in square
s = s**2
running zscore model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:959: RuntimeWarning: overflow encountered in square
s = s**2
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:959: RuntimeWarning: overflow encountered in square
s = s**2
running robust model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
running quantile model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in true_divide
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
running log model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1396: RuntimeWarning: All-NaN slice encountered
overwrite_input, interpolation)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1135: RuntimeWarning: overflow encountered in square
return sqrt(np.average((self.true - self.predicted) ** 2, axis=0, weights=weights))
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_main.py:486: RuntimeWarning: overflow encountered in square
return float(np.average((self.true - self.predicted) ** 2, axis=0, weights=weights))
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1171: RuntimeWarning: overflow encountered in square
numerator = (weight * (self.true - self.predicted) ** 2).sum(axis=0,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:951: RuntimeWarning: invalid value encountered in subtract
a_zero_mean = a - mean
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1545: RuntimeWarning: invalid value encountered in subtract
np.subtract(arr, avg, out=arr, casting='unsafe')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:4009: RuntimeWarning: invalid value encountered in subtract
diff_b_a = subtract(b, a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:980: RuntimeWarning: overflow encountered in square
_nse = 1 - sum((self.predicted - self.true) ** 2) / sum((self.true - np.mean(self.true)) ** 2)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1396: RuntimeWarning: All-NaN slice encountered
overwrite_input, interpolation)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:951: RuntimeWarning: invalid value encountered in subtract
a_zero_mean = a - mean
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1545: RuntimeWarning: invalid value encountered in subtract
np.subtract(arr, avg, out=arr, casting='unsafe')
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:4009: RuntimeWarning: invalid value encountered in subtract
diff_b_a = subtract(b, a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_main.py:486: RuntimeWarning: overflow encountered in square
return float(np.average((self.true - self.predicted) ** 2, axis=0, weights=weights))
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1135: RuntimeWarning: overflow encountered in square
return sqrt(np.average((self.true - self.predicted) ** 2, axis=0, weights=weights))
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1171: RuntimeWarning: overflow encountered in square
numerator = (weight * (self.true - self.predicted) ** 2).sum(axis=0,
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:980: RuntimeWarning: overflow encountered in square
_nse = 1 - sum((self.predicted - self.true) ** 2) / sum((self.true - np.mean(self.true)) ** 2)
running pareto model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
running vast model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
running mmad model
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.compare_errors('rmse', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.compare_errors('r2', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.compare_errors('nrmse', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.taylor_plot(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/SeqMetrics/_rgr.py:1148: RuntimeWarning: invalid value encountered in subtract
zy = (self.predicted - np.mean(self.predicted)) / np.std(self.predicted, ddof=1)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/_methods.py:230: RuntimeWarning: invalid value encountered in subtract
x = asanyarray(arr - arrmean)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2536: RuntimeWarning: invalid value encountered in subtract
X -= avg[:, None]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2691: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[:, None]
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/function_base.py:2692: RuntimeWarning: invalid value encountered in true_divide
c /= stddev[None, :]
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
<Figure size 900x700 with 2 Axes>
experiment.compare_edf_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/core/function_base.py:134: RuntimeWarning: invalid value encountered in double_scalars
delta = stop - start
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.compare_regression_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1396: RuntimeWarning: All-NaN slice encountered
overwrite_input, interpolation)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
experiment.compare_residual_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 14, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 14, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 14, 13)
target shape: (66, 1)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/ai4water/preprocessing/transformations/_transformations.py:570: RuntimeWarning: overflow encountered in exp
return self.inv_func(x)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
dot plot of model could not be plotted due to ('You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) ', 'for plot_model/model_to_dot to work.')
assigning name Input to IteratorGetNext:0 with shape (None, 14, 13)
<Figure size 640x480 with 9 Axes>
experiment.loss_comparison()
<AxesSubplot:>
Total running time of the script: ( 1 minutes 23.557 seconds)
Note
Click here to download the full example code
Comparison of XGBRegressor with different transformations
from ai4water.datasets import busan_beach
from ai4water.utils.utils import get_version_info
from ai4water.experiments import TransformationExperiments
from ai4water.hyperopt import Categorical, Integer, Real
from ai4water.utils.utils import dateandtime_now
for k,v in get_version_info().items():
print(f"{k} version: {v}")
python version: 3.7.9 (default, Oct 19 2020, 15:13:17)
[GCC 7.5.0]
os version: posix
ai4water version: 1.06
lightgbm version: 3.3.5
tcn version: 3.5.0
catboost version: 1.1.1
xgboost version: 1.6.2
easy_mpl version: 0.21.2
SeqMetrics version: 1.3.4
tensorflow version: 2.7.0
keras.api._v2.keras version: 2.7.0
numpy version: 1.21.1
pandas version: 1.3.4
matplotlib version: 3.5.3
h5py version: 3.8.0
joblib version: 1.2.0
data = busan_beach()
input_features = data.columns.tolist()[0:-1]
output_features = data.columns.tolist()[-1:]
class MyTransformationExperiments(TransformationExperiments):
def update_paras(self, **kwargs):
y_transformation = kwargs.pop('y_transformation')
if y_transformation == "none":
y_transformation = None
return {
'model': {"XGBRegressor": kwargs},
'y_transformation': y_transformation
}
cases = {
'model_None': {'y_transformation': 'none'},
'model_minmax': {'y_transformation': 'minmax'},
'model_zscore': {'y_transformation': 'zscore'},
'model_center': {'y_transformation': 'center'},
'model_scale': {'y_transformation': 'scale'},
'model_robust': {'y_transformation': 'robust'},
'model_quantile': {'y_transformation': 'quantile'},
'model_box_cox': {'y_transformation': {'method': 'box-cox', 'treat_negatives': True, 'replace_zeros': True}},
'model_yeo-johnson': {'y_transformation': 'yeo-johnson'},
'model_sqrt': {'y_transformation': 'sqrt'},
'model_log': {'y_transformation': {'method':'log', 'treat_negatives': True, 'replace_zeros': True}},
'model_log10': {'y_transformation': {'method':'log10', 'treat_negatives': True, 'replace_zeros': True}},
"model_pareto": {"y_transformation": "pareto"},
"model_vast": {"y_transformation": "vast"},
"model_mmad": {"y_transformation": "mmad"}
}
num_samples=10
search_space = [
# maximum number of trees that can be built
Integer(low=10, high=30, name='iterations', num_samples=num_samples),
# Used for reducing the gradient step.
Real(low=0.09, high=0.3, prior='log-uniform', name='learning_rate', num_samples=num_samples),
# Coefficient at the L2 regularization term of the cost function.
Real(low=0.5, high=5.0, name='l2_leaf_reg', num_samples=num_samples),
# arger the value, the smaller the model size.
Real(low=0.1, high=10, name='model_size_reg', num_samples=num_samples),
# percentage of features to use at each split selection, when features are selected over again at random.
Real(low=0.1, high=0.5, name='rsm', num_samples=num_samples),
# number of splits for numerical features
Integer(low=32, high=50, name='border_count', num_samples=num_samples),
# The quantization mode for numerical features. The quantization mode for numerical features.
Categorical(categories=['Median', 'Uniform', 'UniformAndQuantiles',
'MaxLogSum', 'MinEntropy', 'GreedyLogSum'], name='feature_border_type')
]
x0 = [10, 0.11, 1.0, 1.0, 0.2, 45, "Uniform"]
experiment = MyTransformationExperiments(
cases=cases,
input_features=input_features,
output_features = output_features,
param_space=search_space,
x0=x0,
verbosity=0,
split_random=True,
exp_name = f"xgb_y_exp_{dateandtime_now()}",
save=False
)
experiment.fit(data = data, run_type='dry_run')
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
running None model
[02:19:51] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running minmax model
[02:19:54] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running zscore model
[02:19:56] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running center model
[02:19:59] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running scale model
[02:20:01] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running robust model
[02:20:04] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running quantile model
[02:20:06] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running box_cox model
[02:20:09] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running yeo-johnson model
[02:20:12] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running sqrt model
[02:20:14] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running log model
[02:20:17] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running log10 model
[02:20:19] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
running pareto model
[02:20:22] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running vast model
[02:20:25] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
running mmad model
[02:20:27] WARNING: ../src/learner.cc:627:
Parameters: { "border_count", "feature_border_type", "iterations", "l2_leaf_reg", "model_size_reg", "rsm" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
/home/docs/checkouts/readthedocs.org/user_builds/ai4water-experiments/envs/latest/lib/python3.7/site-packages/scipy/stats/stats.py:283: RuntimeWarning: invalid value encountered in log
log_a = np.log(a)
experiment.compare_errors('rmse', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.compare_errors('r2', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.compare_errors('r2_score', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.compare_errors('nrmse', data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.taylor_plot(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
<Figure size 900x700 with 2 Axes>
experiment.compare_edf_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.compare_regression_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
experiment.compare_residual_plots(data=data)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
********** Removing Examples with nan in labels **********
***** Training *****
input_x shape: (121, 13)
target shape: (121, 1)
********** Removing Examples with nan in labels **********
***** Validation *****
input_x shape: (31, 13)
target shape: (31, 1)
********** Removing Examples with nan in labels **********
***** Test *****
input_x shape: (66, 13)
target shape: (66, 1)
<Figure size 640x480 with 16 Axes>
Total running time of the script: ( 0 minutes 52.032 seconds)