Hyperparameter Tuning¶

This notebook demonstrates how to automatically find optimal aggregation parameters using find_optimal_combination.

Instead of manually choosing the number of periods and segments, you can specify a target data reduction and let tsam find the best combination.

In [1]:

%load_ext autoreload
%autoreload 2

import pandas as pd
import plotly.express as px
import plotly.io as pio

import tsam
from tsam.tuning import find_optimal_combination

pio.renderers.default = "notebook_connected"

%load_ext autoreload %autoreload 2 import pandas as pd import plotly.express as px import plotly.io as pio import tsam from tsam.tuning import find_optimal_combination pio.renderers.default = "notebook_connected"

Load test data¶

In [2]:

raw = pd.read_csv("testdata.csv", index_col=0, parse_dates=True)
print(f"Shape: {raw.shape}")
print(f"Timesteps: {len(raw)}")
raw.head()

raw = pd.read_csv("testdata.csv", index_col=0, parse_dates=True) print(f"Shape: {raw.shape}") print(f"Timesteps: {len(raw)}") raw.head()

Shape: (8760, 4)
Timesteps: 8760

Out[2]:

	GHI	T	Wind	Load
2009-12-31 23:30:00	0	-2.1	7.1	375.478394
2010-01-01 00:30:00	0	-2.8	8.6	364.541326
2010-01-01 01:30:00	0	-3.3	9.7	357.416844
2010-01-01 02:30:00	0	-3.2	9.8	350.191306
2010-01-01 03:30:00	0	-3.2	9.4	345.161449

Find optimal combination for 2% data reduction¶

The find_optimal_combination function searches for the best period/segment combination that achieves the target data reduction while minimizing RMSE.

Use n_jobs=-1 to utilize all available CPUs for faster search.

In [3]:

result = find_optimal_combination(
    raw,
    data_reduction=0.02,  # Target: 2% of original timesteps
    period_duration=24,
    n_jobs=-1,  # Use all CPUs
    show_progress=True,
)

print("\nOptimal configuration:")
print(f"  Periods: {result.n_clusters}")
print(f"  Segments: {result.n_segments}")
print(f"  RMSE: {result.rmse:.4f}")
print(f"  Timesteps: {result.n_clusters * result.n_segments}")
print(f"  Reduction: {result.n_clusters * result.n_segments / len(raw) * 100:.2f}%")

result = find_optimal_combination( raw, data_reduction=0.02, # Target: 2% of original timesteps period_duration=24, n_jobs=-1, # Use all CPUs show_progress=True, ) print("\nOptimal configuration:") print(f" Periods: {result.n_clusters}") print(f" Segments: {result.n_segments}") print(f" RMSE: {result.rmse:.4f}") print(f" Timesteps: {result.n_clusters * result.n_segments}") print(f" Reduction: {result.n_clusters * result.n_segments / len(raw) * 100:.2f}%")

Searching configurations (2 workers):   0%|          | 0/19 [00:00<?, ?it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):   5%|▌         | 1/19 [00:01<00:19,  1.06s/it]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  16%|█▌        | 3/19 [00:01<00:05,  2.78it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  21%|██        | 4/19 [00:01<00:04,  3.54it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  26%|██▋       | 5/19 [00:01<00:03,  4.00it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  37%|███▋      | 7/19 [00:01<00:02,  5.20it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  47%|████▋     | 9/19 [00:02<00:01,  6.36it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  58%|█████▊    | 11/19 [00:02<00:01,  7.41it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  68%|██████▊   | 13/19 [00:02<00:00,  8.37it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  79%|███████▉  | 15/19 [00:02<00:00,  9.36it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers):  89%|████████▉ | 17/19 [00:02<00:00, 10.23it/s]

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

Searching configurations (2 workers): 100%|██████████| 19/19 [00:02<00:00, 11.88it/s]

Searching configurations (2 workers): 100%|██████████| 19/19 [00:02<00:00,  6.58it/s]

Optimal configuration:
  Periods: 35
  Segments: 5
  RMSE: 0.0899
  Timesteps: 175
  Reduction: 2.00%

View the search history¶

The tuning result includes the history of all tested configurations.

In [4]:

history_df = pd.DataFrame(result.history)
history_df.sort_values("rmse")

history_df = pd.DataFrame(result.history) history_df.sort_values("rmse")

Out[4]:

	n_clusters	n_segments	rmse
4	35	5	0.089913
2	58	3	0.090464
3	43	4	0.090869
5	29	6	0.092497
6	25	7	0.094422
7	21	8	0.096284
8	19	9	0.097095
9	17	10	0.099079
11	14	12	0.100057
10	15	11	0.100222
12	13	13	0.101080
13	12	14	0.101607
14	11	15	0.103531
15	10	17	0.104613
16	9	19	0.106700
17	8	21	0.109790
18	7	24	0.111982
1	87	2	0.113877
0	175	1	0.133896

Use the optimal result¶

The best_result attribute contains the full AggregationResult for the optimal configuration.

In [5]:

best = result.best_result

print(f"Typical periods shape: {best.cluster_representatives.shape}")
print("\nAccuracy metrics:")
print(best.accuracy)

best = result.best_result print(f"Typical periods shape: {best.cluster_representatives.shape}") print("\nAccuracy metrics:") print(best.accuracy)

Typical periods shape: (175, 4)

Accuracy metrics:
AccuracyMetrics(
  rmse=0.0899 (weighted),
  mae=0.0623 (weighted),
  rmse_duration=0.0218 (weighted)
)

In [6]:

reconstructed = best.reconstructed

unstacked = tsam.unstack_to_periods(reconstructed, period_duration=24)
px.imshow(
    unstacked["T"].values.T,
    labels={"x": "Day", "y": "Hour", "color": "Temperature"},
    title=f"Optimal: {result.n_clusters} periods x {result.n_segments} segments",
    aspect="auto",
)

reconstructed = best.reconstructed unstacked = tsam.unstack_to_periods(reconstructed, period_duration=24) px.imshow( unstacked["T"].values.T, labels={"x": "Day", "y": "Hour", "color": "Temperature"}, title=f"Optimal: {result.n_clusters} periods x {result.n_segments} segments", aspect="auto", )

Compare different reduction targets¶

Let's see how the optimal configuration changes with different data reduction targets.

In [7]:

reductions = [0.01, 0.02, 0.05, 0.10]
results_comparison = {}

for reduction in reductions:
    r = find_optimal_combination(
        raw,
        data_reduction=reduction,
        period_duration=24,
        n_jobs=-1,
        show_progress=False,
    )
    results_comparison[f"{int(reduction * 100)}%"] = r
    print(
        f"{int(reduction * 100)}% reduction: {r.n_clusters} periods x {r.n_segments} segments, RMSE={r.rmse:.4f}"
    )

reductions = [0.01, 0.02, 0.05, 0.10] results_comparison = {} for reduction in reductions: r = find_optimal_combination( raw, data_reduction=reduction, period_duration=24, n_jobs=-1, show_progress=False, ) results_comparison[f"{int(reduction * 100)}%"] = r print( f"{int(reduction * 100)}% reduction: {r.n_clusters} periods x {r.n_segments} segments, RMSE={r.rmse:.4f}" )

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

1% reduction: 29 periods x 3 segments, RMSE=0.0989

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

2% reduction: 35 periods x 5 segments, RMSE=0.0899

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

5% reduction: 87 periods x 5 segments, RMSE=0.0768

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

/home/docs/checkouts/readthedocs.org/user_builds/tsam/checkouts/latest/src/tsam/tuning.py:86: FutureWarning: aggregate() result columns are sorted alphabetically in v3 but will follow the input DataFrame's order in v4; your columns are not alphabetical, so this output will change. To keep the v3 order, sort before (aggregate(data.sort_index(axis=1), ...)) or after (result.cluster_representatives.sort_index(axis=1)); to adopt v4 now, index results by column name, not position. To silence this warning: warnings.filterwarnings('ignore', category=FutureWarning, message='.*sorted alphabetically.*').
  result = aggregate(

10% reduction: 175 periods x 5 segments, RMSE=0.0637

In [8]:

comparison_data = {"Original": raw}
for label, r in results_comparison.items():
    comparison_data[label] = r.best_result.reconstructed

# Duration curve comparison using plotly express
frames = []
for name, df in comparison_data.items():
    sorted_vals = df["Load"].sort_values(ascending=False).reset_index(drop=True)
    frames.append(
        pd.DataFrame(
            {"Hour": range(len(sorted_vals)), "Load": sorted_vals, "Method": name}
        )
    )
long_df = pd.concat(frames, ignore_index=True)

px.line(
    long_df,
    x="Hour",
    y="Load",
    color="Method",
    title="Duration Curve Comparison - Different Reduction Targets",
)

comparison_data = {"Original": raw} for label, r in results_comparison.items(): comparison_data[label] = r.best_result.reconstructed # Duration curve comparison using plotly express frames = [] for name, df in comparison_data.items(): sorted_vals = df["Load"].sort_values(ascending=False).reset_index(drop=True) frames.append( pd.DataFrame( {"Hour": range(len(sorted_vals)), "Load": sorted_vals, "Method": name} ) ) long_df = pd.concat(frames, ignore_index=True) px.line( long_df, x="Hour", y="Load", color="Method", title="Duration Curve Comparison - Different Reduction Targets", )

Helper functions¶

Use find_clusters_for_reduction and find_segments_for_reduction to calculate parameters for a specific reduction target.

In [9]:

from tsam.tuning import find_clusters_for_reduction, find_segments_for_reduction

n_timesteps = len(raw)
target_reduction = 0.01  # 1% of original

# How many periods can we have with 24 segments?
max_periods = find_clusters_for_reduction(
    n_timesteps, n_segments=24, data_reduction=target_reduction
)
print(f"With 24 segments: max {max_periods} periods for 1% reduction")

# How many segments can we have with 8 periods?
max_segments = find_segments_for_reduction(
    n_timesteps, n_clusters=8, data_reduction=target_reduction
)
print(f"With 8 periods: max {max_segments} segments for 1% reduction")

from tsam.tuning import find_clusters_for_reduction, find_segments_for_reduction n_timesteps = len(raw) target_reduction = 0.01 # 1% of original # How many periods can we have with 24 segments? max_periods = find_clusters_for_reduction( n_timesteps, n_segments=24, data_reduction=target_reduction ) print(f"With 24 segments: max {max_periods} periods for 1% reduction") # How many segments can we have with 8 periods? max_segments = find_segments_for_reduction( n_timesteps, n_clusters=8, data_reduction=target_reduction ) print(f"With 8 periods: max {max_segments} segments for 1% reduction")

With 24 segments: max 3 periods for 1% reduction
With 8 periods: max 10 segments for 1% reduction