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[DOC] - Reduce code blocks in capabilties #339

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merged 11 commits into from
May 10, 2024

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marcopeix
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@marcopeix marcopeix commented May 6, 2024

Less code blocks in capabilities notebooks
Includes links to more detailed tutorials in the docu.

Number of code blocks cannot be reduced further because the CI blocks code cells with imports and code within the same cell.

Add a detailed tutorial on anomaly detection. Tutorial is compatible with Google Colab.

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github-actions bot commented May 6, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 2.5662 2.476 0.0083 0.0047

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 2.0919 2.0586 0.0057 0.0051

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 142.394 196.363 269.23 1331.02
mape 0.0203 0.0234 0.0304 0.1692
mse 63464.7 123119 213677 4.68961e+06
total_time 2.3357 3.5732 0.008 0.0071

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 522.427 353.528 398.956 1119.26
mape 0.069 0.0454 0.0512 0.1583
mse 966294 422332 656723 3.17316e+06
total_time 3.3826 2.8775 0.0076 0.0071

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 478.362 361.033 602.926 1340.95
mape 0.0622 0.046 0.0787 0.17
mse 805039 441118 1.61572e+06 6.04619e+06
total_time 5.3687 5.8545 0.0078 0.0076

Plot:

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github-actions bot commented May 7, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 16.1315 17.651 0.0087 0.0047

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 12.6748 22.2726 0.0058 0.0047

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 142.394 196.363 269.23 1331.02
mape 0.0203 0.0234 0.0304 0.1692
mse 63464.7 123119 213677 4.68961e+06
total_time 22.5465 24.8094 0.0078 0.0068

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 522.427 353.528 398.956 1119.26
mape 0.069 0.0454 0.0512 0.1583
mse 966294 422332 656723 3.17316e+06
total_time 22.4827 24.428 0.0074 0.007

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 478.362 361.033 602.926 1340.95
mape 0.0622 0.046 0.0787 0.17
mse 805039 441118 1.61572e+06 6.04619e+06
total_time 22.9467 20.4144 0.0075 0.007

Plot:

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github-actions bot commented May 7, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 18.2121 18.1816 0.0089 0.0049

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.22 4110.79 5928.17 18859.2
total_time 22.7999 23.12 0.0057 0.0049

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 142.394 196.363 269.23 1331.02
mape 0.0203 0.0234 0.0304 0.1692
mse 63464.7 123119 213677 4.68961e+06
total_time 24.6667 26.7074 0.0086 0.008

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 522.427 353.528 398.956 1119.26
mape 0.069 0.0454 0.0512 0.1583
mse 966295 422332 656723 3.17316e+06
total_time 27.8528 26.8094 0.0076 0.0071

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 478.362 361.033 602.926 1340.95
mape 0.0622 0.046 0.0787 0.17
mse 805038 441118 1.61572e+06 6.04619e+06
total_time 27.3092 26.2293 0.0078 0.0072

Plot:

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github-actions bot commented May 7, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.935 199.132 2571.33 10604.2
total_time 4.6568 4.8198 0.0085 0.0047

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.22 4110.79 5928.17 18859.2
total_time 5.2316 4.9375 0.0055 0.0046

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 142.394 196.363 269.23 1331.02
mape 0.0203 0.0234 0.0304 0.1692
mse 63464.8 123119 213677 4.68961e+06
total_time 3.8572 7.3237 0.0075 0.0067

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 522.427 353.528 398.956 1119.26
mape 0.069 0.0454 0.0512 0.1583
mse 966295 422332 656723 3.17316e+06
total_time 4.7836 4.4969 0.0073 0.0066

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 478.362 361.033 602.926 1340.95
mape 0.0622 0.046 0.0787 0.17
mse 805039 441118 1.61572e+06 6.04619e+06
total_time 6.6679 3.3262 0.0075 0.007

Plot:

@marcopeix marcopeix marked this pull request as ready for review May 7, 2024 20:21
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github-actions bot commented May 8, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.935 199.132 2571.33 10604.2
total_time 6.0181 2.9598 0.0089 0.0049

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 4.0561 2.9032 0.006 0.005

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 178.293 196.363 269.23 1331.02
mape 0.0234 0.0234 0.0304 0.1692
mse 121588 123119 213677 4.68961e+06
total_time 3.8415 4.5314 0.0079 0.0068

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 465.532 353.528 398.956 1119.26
mape 0.062 0.0454 0.0512 0.1583
mse 835120 422332 656723 3.17316e+06
total_time 4.9564 5.373 0.0073 0.0069

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 558.649 361.033 602.926 1340.95
mape 0.0697 0.046 0.0787 0.17
mse 1.22721e+06 441118 1.61572e+06 6.04619e+06
total_time 6.6671 3.6 0.0076 0.0073

Plot:

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github-actions bot commented May 8, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.935 199.132 2571.33 10604.2
total_time 2.8949 2.9388 0.0088 0.0049

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.22 4110.79 5928.17 18859.2
total_time 2.7975 2.0017 0.0061 0.0051

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 178.293 196.363 269.23 1331.02
mape 0.0234 0.0234 0.0304 0.1692
mse 121588 123119 213677 4.68961e+06
total_time 3.0009 3.5506 0.0082 0.0071

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 465.532 353.528 398.956 1119.26
mape 0.062 0.0454 0.0512 0.1583
mse 835120 422332 656723 3.17316e+06
total_time 5.4371 2.7377 0.0077 0.007

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 558.649 361.033 602.926 1340.95
mape 0.0697 0.046 0.0787 0.17
mse 1.22721e+06 441118 1.61572e+06 6.04619e+06
total_time 4.9077 4.7565 0.0079 0.0071

Plot:

@@ -11,7 +11,7 @@
"cell_type": "markdown",
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@AzulGarza AzulGarza May 8, 2024

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let's make sure all the nbs have similar headers, to maintain the same across nbs, eg

nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb does not have the initial text as header.


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Hello Azul! I don't know why in reviewNB the little text blurb is shown as a header. In the code, you see that it's just simple markdown with no "#". So, right now, all notebooks are consistent, in the sense that we have the header in the first cell, then we have a little blurb as normal text in the second cell. Not sure why it appears like this here. I'll rerun everything. It should look like in nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb

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Fixed now!

@@ -11,7 +11,11 @@
"cell_type": "markdown",
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this should be a header?


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No, just a little blurb to guide the users. The idea was to remove headers so that I could combine code blocks together and have less code blocks to copy/paste, as Max suggested.

@@ -11,7 +11,14 @@
"cell_type": "markdown",
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first line as header.


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My plan was to keep it as a normal text. I will fix the other notebooks that show headers instead.

nbs/docs/tutorials/20_anomaly_detection.ipynb Outdated Show resolved Hide resolved
@AzulGarza AzulGarza self-requested a review May 8, 2024 21:51
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small comments regarding typos

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github-actions bot commented May 9, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 2.971 2.2022 0.008 0.0044

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 3.2998 2.52 0.0052 0.0044

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 178.293 196.363 269.23 1331.02
mape 0.0234 0.0234 0.0304 0.1692
mse 121588 123119 213677 4.68961e+06
total_time 1.9254 3.5996 0.0071 0.0062

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 465.532 353.528 398.956 1119.26
mape 0.062 0.0454 0.0512 0.1583
mse 835120 422332 656723 3.17316e+06
total_time 3.4247 3.5047 0.0067 0.0063

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 558.649 361.033 602.926 1340.95
mape 0.0697 0.046 0.0787 0.17
mse 1.22721e+06 441118 1.61572e+06 6.04619e+06
total_time 4.1364 2.7115 0.0069 0.0064

Plot:

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github-actions bot commented May 9, 2024

Experiment Results

Experiment 1: air-passengers

Description:

variable experiment
h 12
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 12.6793 11.0623 47.8333 76
mape 0.027 0.0232 0.0999 0.1425
mse 213.936 199.132 2571.33 10604.2
total_time 2.5864 2.1696 0.0083 0.0043

Plot:

Experiment 2: air-passengers

Description:

variable experiment
h 24
season_length 12
freq MS
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 58.1031 58.4587 71.25 115.25
mape 0.1257 0.1267 0.1552 0.2358
mse 4040.21 4110.79 5928.17 18859.2
total_time 2.2631 2.3232 0.0051 0.0043

Plot:

Experiment 3: electricity-multiple-series

Description:

variable experiment
h 24
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 178.293 196.363 269.23 1331.02
mape 0.0234 0.0234 0.0304 0.1692
mse 121588 123119 213677 4.68961e+06
total_time 2.3803 2.6258 0.0072 0.0063

Plot:

Experiment 4: electricity-multiple-series

Description:

variable experiment
h 168
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 465.532 353.528 398.956 1119.26
mape 0.062 0.0454 0.0512 0.1583
mse 835120 422332 656723 3.17316e+06
total_time 3.6174 2.5013 0.0069 0.0063

Plot:

Experiment 5: electricity-multiple-series

Description:

variable experiment
h 336
season_length 24
freq H
level None
n_windows 1

Results:

metric timegpt-1 timegpt-1-long-horizon SeasonalNaive Naive
mae 558.649 361.033 602.926 1340.95
mape 0.0697 0.046 0.0787 0.17
mse 1.22721e+06 441118 1.61572e+06 6.04619e+06
total_time 4.3772 2.8162 0.007 0.0064

Plot:

@AzulGarza AzulGarza self-requested a review May 10, 2024 03:06
@AzulGarza AzulGarza merged commit e9d01e6 into main May 10, 2024
14 checks passed
@AzulGarza AzulGarza deleted the hotfix/capabilities-less-code-blocks branch May 10, 2024 03:07
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