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modified metadata of feature_analysis module, fix bugs in primitive_tests

master
lhenry15 4 years ago
parent
a942786c91
commit
4573e5bb56
34 changed files with 522 additions and 746 deletions
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  1. +1
    -1
      examples/axolotl_interface/example_pipelines/autoencoder_pipeline.json
  2. +3
    -3
      primitive_tests/feature_analysis/TruncatedSVD_pipeline.py
  3. +3
    -2
      primitive_tests/test.sh
  4. +9
    -5
      tods/feature_analysis/AutoCorrelation.py
  5. +11
    -6
      tods/feature_analysis/BKFilter.py
  6. +7
    -12
      tods/feature_analysis/DiscreteCosineTransform.py
  7. +9
    -15
      tods/feature_analysis/FastFourierTransform.py
  8. +11
    -6
      tods/feature_analysis/HPFilter.py
  9. +16
    -22
      tods/feature_analysis/NonNegativeMatrixFactorization.py
  10. +15
    -10
      tods/feature_analysis/SKTruncatedSVD.py
  11. +19
    -30
      tods/feature_analysis/SpectralResidualTransform.py
  12. +19
    -29
      tods/feature_analysis/StatisticalAbsEnergy.py
  13. +18
    -30
      tods/feature_analysis/StatisticalAbsSum.py
  14. +18
    -31
      tods/feature_analysis/StatisticalGmean.py
  15. +19
    -29
      tods/feature_analysis/StatisticalHmean.py
  16. +18
    -30
      tods/feature_analysis/StatisticalKurtosis.py
  17. +18
    -29
      tods/feature_analysis/StatisticalMaximum.py
  18. +19
    -30
      tods/feature_analysis/StatisticalMean.py
  19. +18
    -30
      tods/feature_analysis/StatisticalMeanAbs.py
  20. +19
    -30
      tods/feature_analysis/StatisticalMeanAbsTemporalDerivative.py
  21. +19
    -30
      tods/feature_analysis/StatisticalMeanTemporalDerivative.py
  22. +19
    -30
      tods/feature_analysis/StatisticalMedian.py
  23. +19
    -30
      tods/feature_analysis/StatisticalMedianAbsoluteDeviation.py
  24. +19
    -30
      tods/feature_analysis/StatisticalMinimum.py
  25. +19
    -30
      tods/feature_analysis/StatisticalSkew.py
  26. +19
    -30
      tods/feature_analysis/StatisticalStd.py
  27. +18
    -30
      tods/feature_analysis/StatisticalVar.py
  28. +20
    -30
      tods/feature_analysis/StatisticalVariation.py
  29. +19
    -30
      tods/feature_analysis/StatisticalVecSum.py
  30. +19
    -30
      tods/feature_analysis/StatisticalWillisonAmplitude.py
  31. +18
    -29
      tods/feature_analysis/StatisticalZeroCrossing.py
  32. +15
    -10
      tods/feature_analysis/TRMF.py
  33. +15
    -13
      tods/feature_analysis/WaveletTransform.py
  34. +14
    -14
      tods/timeseries_processing/HoltSmoothing.py

+ 1
- 1
examples/axolotl_interface/example_pipelines/autoencoder_pipeline.json View File

@@ -1 +1 @@
{"id": "5478db87-2eea-45c7-b0c1-f6a2fb180a61", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2021-02-04T06:35:44.477042Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.6.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.dataset_to_dataframe", "name": "Extract a DataFrame from a Dataset", "digest": "f817673b67b0bf1fad5efb694e44a59b9c15931520b419f3a852f79152f58bb7"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7", "version": "0.6.0", "python_path": "d3m.primitives.tods.data_processing.column_parser", "name": "Parses strings into their types", "digest": "6aea6b48ddcd847030b423ebf2cac62e67b2935d93f75d10fa0712ea019b2739"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "4503a4c6-42f7-45a1-a1d4-ed69699cf5e1", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type", "digest": "e165d114bca8e1e47f349fffbbf2cf8872f0222328287e24acd8ac8c1cf2511c"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/Attribute"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "4503a4c6-42f7-45a1-a1d4-ed69699cf5e1", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type", "digest": "e165d114bca8e1e47f349fffbbf2cf8872f0222328287e24acd8ac8c1cf2511c"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/TrueTarget"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "642de2e7-5590-3cab-9266-2a53c326c461", "version": "0.0.1", "python_path": "d3m.primitives.tods.timeseries_processing.transformation.axiswise_scaler", "name": "Axis_wise_scale"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "67e7fcdf-d645-3417-9aa4-85cd369487d9", "version": "0.0.1", "python_path": "d3m.primitives.tods.detection_algorithm.pyod_ae", "name": "TODS.anomaly_detection_primitives.AutoEncoder"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.4.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.construct_predictions", "name": "Construct pipeline predictions output", "digest": "c8a5cb30cc5b6742dbf024cbd54d5283937864c5d5dd9f3d0fb242fa406b1736"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.5.produce"}, "reference": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "aa2c6d9f9a56d76f5f2e8bb29ad5b21b43970a2acb7a7a7695e057bfcd1fdabd"}
{"id": "bfd8aedf-36be-4dad-af8a-c324a03db5f9", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2021-02-13T17:02:35.500457Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.6.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "c78138d9-9377-31dc-aee8-83d9df049c60", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.dataset_to_dataframe", "name": "Extract a DataFrame from a Dataset"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "81235c29-aeb9-3828-911a-1b25319b6998", "version": "0.6.0", "python_path": "d3m.primitives.tods.data_processing.column_parser", "name": "Parses strings into their types"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "a996cd89-ddf0-367f-8e7f-8c013cbc2891", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/Attribute"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "a996cd89-ddf0-367f-8e7f-8c013cbc2891", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/TrueTarget"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "642de2e7-5590-3cab-9266-2a53c326c461", "version": "0.0.1", "python_path": "d3m.primitives.tods.timeseries_processing.transformation.axiswise_scaler", "name": "Axis_wise_scale"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "67e7fcdf-d645-3417-9aa4-85cd369487d9", "version": "0.0.1", "python_path": "d3m.primitives.tods.detection_algorithm.pyod_ae", "name": "TODS.anomaly_detection_primitives.AutoEncoder"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.4.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "2530840a-07d4-3874-b7d8-9eb5e4ae2bf3", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.construct_predictions", "name": "Construct pipeline predictions output"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.5.produce"}, "reference": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "01ad8ccf817150186ca15157a4f02ee1f738582137321a8a5a4a3252832ce555"}

+ 3
- 3
primitive_tests/feature_analysis/TruncatedSVD_pipeline.py View File

@@ -29,12 +29,12 @@ pipeline_description.add_step(step_2)

# Step 3: TruncatedSVD
step_3 = PrimitiveStep(primitive=index.get_primitive('d3m.primitives.tods.feature_analysis.truncated_svd'))
step_3.add_argument(name='inputs', argument_type=ArgumentType.CONTAINER, data_reference='steps.3.produce')
step_3.add_output('produce')
step_3.add_hyperparameter(name = 'n_components', argument_type=ArgumentType.VALUE, data = 3)
step_3.add_hyperparameter(name = 'use_columns', argument_type=ArgumentType.VALUE, data = (2, 3, 4, 5))
step_3.add_hyperparameter(name = 'return_result', argument_type=ArgumentType.VALUE, data = 'append')
step_3.add_hyperparameter(name = 'use_semantic_types', argument_type=ArgumentType.VALUE, data = True)
step_3.add_argument(name='inputs', argument_type=ArgumentType.CONTAINER, data_reference='steps.2.produce')
step_3.add_output('produce')
pipeline_description.add_step(step_3)

# Final Output
@@ -44,4 +44,4 @@ pipeline_description.add_output(name='output predictions', data_reference='steps
data = pipeline_description.to_json()
with open('example_pipeline.json', 'w') as f:
f.write(data)
print(data)
print(data)

+ 3
- 2
primitive_tests/test.sh View File

@@ -1,12 +1,13 @@
#!/bin/bash

#modules="data_processing timeseries_processing feature_analysis detection_algorithms reinforcement"
modules="data_processing timeseries_processing"
#modules="data_processing timeseries_processing"
modules="feature_analysis"
#test_scripts=$(ls primitive_tests | grep -v -f tested_file.txt)

for module in $modules
do
test_scripts=$(ls $module)
test_scripts=$(ls $module | grep -v -f tested_file.txt)

for file in $test_scripts
do


+ 9
- 5
tods/feature_analysis/AutoCorrelation.py View File

@@ -220,13 +220,17 @@ class AutoCorrelationPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outp
'__author__': "DATA Lab @Texas A&M University",
'name': "AutoCorrelation of values",
'python_path': 'd3m.primitives.tods.feature_analysis.auto_correlation',
'source': {'name': "DATALAB @Taxes A&M University", 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods/-/blob/Yile/anomaly-primitives/anomaly_primitives/AutoCorrelation.py']},
'algorithm_types': [metadata_base.PrimitiveAlgorithmType.AUTOCORRELATION,],
'source': {
'name': "DATALAB @Taxes A&M University",
'contact': 'mailto:khlai037@tamu.edu',
},
'version': '0.0.2',
'hyperparams_to_tune': ['unbiased', 'nlags', 'qstat', 'fft', 'alpha', 'missing'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'AutocorrelationPrimitive')),
'hyperparams_to_tune': ['unbiased', 'nlags', 'qstat', 'fft', 'alpha', 'missing'],
'version': '0.0.2',
})

def __init__(self, *,


+ 11
- 6
tods/feature_analysis/BKFilter.py View File

@@ -7,6 +7,7 @@ import sklearn
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -154,17 +155,21 @@ class BKFilterPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outputs, Hy
Decides what semantic type to attach to generated attributes'
"""

__author__: "DATA Lab at Texas A&M University"
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab at Texas A&M University",
"name": "Baxter-King Filter Primitive",
"python_path": "d3m.primitives.tods.feature_analysis.bk_filter",
"source": {'name': 'DATA Lab at Texas A&M University', 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods.git', 'https://gitlab.com/lhenry15/tods/-/blob/Junjie/anomaly-primitives/anomaly_primitives/DuplicationValidation.py']},
"algorithm_types": [metadata_base.PrimitiveAlgorithmType.BK_FILTER,],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
"id": "b2bfadc5-dbca-482c-b188-8585e5f245c4",
"source": {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"hyperparams_to_tune": ['low', 'high', 'K'],
"version": "0.0.1",
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'BKFilterPrimitive')),
})




+ 7
- 12
tods/feature_analysis/DiscreteCosineTransform.py View File

@@ -7,6 +7,7 @@ from d3m import container, utils
from d3m.base import utils as base_utils
from d3m.metadata import base as metadata_base, hyperparams
from d3m.primitive_interfaces import base, transformer
import uuid

import logging
import math
@@ -212,27 +213,21 @@ class DiscreteCosineTransformPrimitive(transformer.TransformerPrimitiveBase[Inpu

"""

__author__ = "Data Lab"
metadata = metadata_base.PrimitiveMetadata(
{
"__author__ " : "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata({
"__author__ " : "DATA Lab @ Texas A&M University",
'name': "Discrete Cosine Transform",
'python_path': 'd3m.primitives.tods.feature_analysis.discrete_cosine_transform',
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
'uris': [
'https://gitlab.com/lhenry15/tods.git',
'https://gitlab.com/lhenry15/tods/-/blob/purav/anomaly-primitives/anomaly_primitives/DiscreteCosineTransform.py',
],
},
'hyperparameters_to_tune':['n','norm','axis','type_'],
'version': '0.0.1',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DISCRETE_COSINE_TRANSFORM,
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': '584fa7d5-39cc-4cf8-8d5b-5f3a2648f767',
'hyperparameters_to_tune':['n','norm','axis','type_'],
'version': '0.0.1',
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'DiscreteCosineTransformPrimitive')),
},
)



+ 9
- 15
tods/feature_analysis/FastFourierTransform.py View File

@@ -7,6 +7,7 @@ from d3m import container, utils
from d3m.base import utils as base_utils
from d3m.metadata import base as metadata_base, hyperparams
from d3m.primitive_interfaces import base, transformer
import uuid

import logging
from cmath import polar
@@ -204,29 +205,22 @@ class FastFourierTransformPrimitive(transformer.TransformerPrimitiveBase[Inputs,
Decides what semantic type to attach to generated attributes'
"""
__author__ = "Data Lab"
metadata = metadata_base.PrimitiveMetadata(
{
'__author__' : "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata({
'__author__' : "DATA Lab @ Texas A&M University",
'name': "Fast Fourier Transform",
'python_path': 'd3m.primitives.tods.feature_analysis.fast_fourier_transform',
'source': {
'name': 'DATA Lab at Texas A&M University',
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
'uris': [
'https://gitlab.com/lhenry15/tods.git',
'https://gitlab.com/lhenry15/tods/-/blob/purav/anomaly-primitives/anomaly_primitives/FastFourierTransform.py',
],
},
'hyperparameters_to_tune':['n','norm','axis'],
'version': '0.0.1',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.FAST_FOURIER_TRANSFORM,
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': '7bd269bc-de7e-47b8-8d6c-0bd46594d3cb',
'hyperparameters_to_tune':['n','norm','axis'],
'version': '0.0.1',
},
)
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'FastFourierTransformPrimitive')),
})

def __init__(self, *, hyperparams: Hyperparams) -> None:
super().__init__(hyperparams=hyperparams)


+ 11
- 6
tods/feature_analysis/HPFilter.py View File

@@ -7,6 +7,7 @@ import sklearn
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -131,17 +132,21 @@ class HPFilterPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outputs, Hy
Decides what semantic type to attach to generated attributes'
"""

__author__: "DATA Lab at Texas A&M University"
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab at Texas A&M University",
"name": "Hodrick-Prescott filter Primitive",
"python_path": "d3m.primitives.tods.feature_analysis.hp_filter",
"source": {'name': 'DATA Lab at Texas A&M University', 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods.git', 'https://gitlab.com/lhenry15/tods/-/blob/Junjie/anomaly-primitives/anomaly_primitives/DuplicationValidation.py']},
"algorithm_types": [metadata_base.PrimitiveAlgorithmType.HP_FILTER,],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
"id": "3af1be06-e45e-4ead-8523-4373264598e4",
"source": {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"hyperparams_to_tune": ['lamb'],
"version": "0.0.1",
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'HPFilterPrimitive')),
})




+ 16
- 22
tods/feature_analysis/NonNegativeMatrixFactorization.py View File

@@ -7,6 +7,7 @@ from d3m.primitive_interfaces.base import CallResult, DockerContainer
from typing import cast, Dict, List, Union, Sequence, Optional, Tuple
from collections import OrderedDict
from scipy import sparse
import uuid

import nimfa
import pandas as pd
@@ -266,29 +267,22 @@ class NonNegativeMatrixFactorizationPrimitive(transformer.TransformerPrimitiveBa



__author__ = "Data Lab"
metadata = metadata_base.PrimitiveMetadata(
{
'__author__' : "DATA Lab at Texas A&M University",
'name': "Fast Fourier Transform",
'python_path': 'd3m.primitives.tods.feature_analysis.non_negative_matrix_factorization',
'source': {
'name': 'DATA Lab at Texas A&M University',
metadata = metadata_base.PrimitiveMetadata({
'__author__' : "DATA Lab @ Texas A&M University",
'name': "Fast Fourier Transform",
'python_path': 'd3m.primitives.tods.feature_analysis.non_negative_matrix_factorization',
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
'uris': [
'https://gitlab.com/lhenry15/tods.git',
'https://gitlab.com/lhenry15/tods/-/blob/purav/anomaly-primitives/anomaly_primitives/NonNegativeMatrixFactorization.py',
],
},
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.NON_NEGATIVE_MATRIX_FACTORIZATION,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': 'c7259da6-7ce6-42ad-83c6-15238679f5fa',
'hyperparameters_to_tune':['rank','update','objective','max_iter','learning_rate'],
'version': '0.0.1',
},
)
},
'hyperparameters_to_tune':['rank','update','objective','max_iter','learning_rate'],
'version': '0.0.1',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'NonNegativeMatrixFactorizationPrimitive')),
})

def __init__(self, *, hyperparams: Hyperparams) -> None:
super().__init__(hyperparams=hyperparams)


+ 15
- 10
tods/feature_analysis/SKTruncatedSVD.py View File

@@ -7,6 +7,7 @@ import sklearn
import numpy
import typing
import time
import uuid

# Custom import commands if any
from sklearn.decomposition.truncated_svd import TruncatedSVD
@@ -156,17 +157,21 @@ class SKTruncatedSVDPrimitive(UnsupervisedLearnerPrimitiveBase[Inputs, Outputs,
Decides what semantic type to attach to generated attributes'
"""

__author__: "DATA Lab at Texas A&M University"
metadata = metadata_base.PrimitiveMetadata({
"name": "Truncated SVD",
"python_path": "d3m.primitives.tods.feature_analysis.truncated_svd",
"source": {'name': 'DATA Lab at Texas A&M University', 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods.git', 'https://gitlab.com/lhenry15/tods/-/blob/Junjie/anomaly-primitives/anomaly_primitives/SKTruncatedSVD.py']},
"algorithm_types": [metadata_base.PrimitiveAlgorithmType.SINGULAR_VALUE_DECOMPOSITION, ],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
"id": "9231fde3-7322-3c41-b4cf-d00a93558c44",
"hyperparams_to_tune": ['n_components', 'algorithm', 'use_columns', 'exclude_columns', 'return_result', 'use_semantic_types', 'add_index_columns', 'error_on_no_input', 'return_semantic_type'],
"version": "0.0.1",
"__author__": "DATA Lab at Texas A&M University",
"name": "Truncated SVD",
"python_path": "d3m.primitives.tods.feature_analysis.truncated_svd",
"source": {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"hyperparams_to_tune": ['n_components', 'algorithm', 'use_columns', 'exclude_columns', 'return_result', 'use_semantic_types', 'add_index_columns', 'error_on_no_input', 'return_semantic_type'],
"version": "0.0.1",
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'SKTruncatedSVDPrimitive')),
})

def __init__(self, *,


+ 19
- 30
tods/feature_analysis/SpectralResidualTransform.py View File

@@ -9,6 +9,7 @@ from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import uuid

import numpy
import typing
@@ -90,36 +91,24 @@ class SpectralResidualTransformPrimitive(transformer.TransformerPrimitiveBase[In
"""
Primitive to find Spectral Residual Transform of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '88dda04b-090b-49a5-8035-279eb3be9cd9',
'version': '0.1.0',
'name': 'Time Series Spectral Residual',
'python_path': 'd3m.primitives.tods.feature_analysis.spectral_residual_transform',
'keywords': ['Time Series','FFT'],
"hyperparams_to_tune": ['avg_filter_dimension'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/SpectralResidualTransform.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Spectral Residual',
'python_path': 'd3m.primitives.tods.feature_analysis.spectral_residual_transform',
'keywords': ['Time Series','FFT'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'

},
"hyperparams_to_tune": ['avg_filter_dimension'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'SpectralResidualTransformPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 29
tods/feature_analysis/StatisticalAbsEnergy.py View File

@@ -9,6 +9,7 @@ from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import uuid

import numpy
import typing
@@ -92,35 +93,24 @@ class StatisticalAbsEnergyPrimitive(transformer.TransformerPrimitiveBase[Inputs,
"""

__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '73299ffe-d8bb-43c6-a6cc-9261f5e17a5e',
'version': '0.1.0',
'name': 'Time Series Statistical Abs Energy',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_abs_energy',
'keywords': ['Time Series','AbsEnergy'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalAbsEnergy.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Statistical Abs Energy',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_abs_energy',
'keywords': ['Time Series','AbsEnergy'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
"hyperparams_to_tune": ['window_size'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalAbsEnergyPrimitive')),

})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 30
tods/feature_analysis/StatisticalAbsSum.py View File

@@ -9,6 +9,7 @@ from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import uuid

import numpy
import typing
@@ -90,36 +91,23 @@ class StatisticalAbsSumPrimitive(transformer.TransformerPrimitiveBase[Inputs, Ou
"""
Primitive to find abs_sum of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'fbc10e6f-d75b-4815-b4c8-5ad4f2f577db',
'version': '0.1.0',
'name': 'Time Series Absolute Sum',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_abs_sum',
'keywords': ['Time Series','AbsSum'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalAbsSum.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Absolute Sum',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_abs_sum',
'keywords': ['Time Series','AbsSum'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
"hyperparams_to_tune": ['window_size'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalAbsSumPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 31
tods/feature_analysis/StatisticalGmean.py View File

@@ -10,7 +10,7 @@ from collections import OrderedDict
from scipy import sparse
import os
from scipy import stats
import uuid
import numpy
import typing
import time
@@ -93,36 +93,23 @@ class StatisticalGmeanPrimitive(transformer.TransformerPrimitiveBase[Inputs, Out
Primitive to find gmean of time series .
Will only take positive values as inputs .
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '6be88a7d-e72d-45c6-bd3b-3191d4eff623',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_g_mean',
'keywords': ['Time Series','Gmean'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalGmean.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_g_mean',
'keywords': ['Time Series','Gmean'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
"hyperparams_to_tune": ['window_size'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalGmeanPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 29
tods/feature_analysis/StatisticalHmean.py View File

@@ -10,6 +10,7 @@ from collections import OrderedDict
from scipy import sparse
import os
from scipy import stats
import uuid

import numpy
import typing
@@ -93,35 +94,24 @@ class StatisticalHmeanPrimitive(transformer.TransformerPrimitiveBase[Inputs, Out
Harmonic mean only defined if all elements greater than or equal to zero
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '7c4bf669-26f4-4756-8e00-c3e5e89fa43c',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_h_mean',
'keywords': ['Time Series','Hmean'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalHmean.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_h_mean',
'keywords': ['Time Series','Hmean'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'

},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalHmeanPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 30
tods/feature_analysis/StatisticalKurtosis.py View File

@@ -10,6 +10,7 @@ from collections import OrderedDict
from scipy import sparse
import os
from scipy import stats
import uuid

import numpy
import typing
@@ -91,36 +92,23 @@ class StatisticalKurtosisPrimitive(transformer.TransformerPrimitiveBase[Inputs,
"""
Primitive to find kurtosis of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'c86af521-05b6-4f7c-a7b9-929318d944fc',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_kurtosis',
'keywords': ['Time Series','Kurtosis'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalKurtosis.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_kurtosis',
'keywords': ['Time Series','Kurtosis'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalKurtosisPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 29
tods/feature_analysis/StatisticalMaximum.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -91,35 +92,23 @@ class StatisticalMaximumPrimitive(transformer.TransformerPrimitiveBase[Inputs, O
Primitive to find maximum of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '3b448057-ac26-4f1b-96b6-141782f16a54',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_maximum',
'keywords': ['Time Series','Maximum'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMaximum.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_maximum',
'keywords': ['Time Series','Maximum'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
"hyperparams_to_tune": ['window_size'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMaximumPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMean.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalMeanPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outp
"""
Primitive to find mean of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'eaff2f35-978c-4530-a12e-061a5f0beacd',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean',
'keywords': ['Time Series','Mean'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMean.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean',
'keywords': ['Time Series','Mean'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMeanPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 30
tods/feature_analysis/StatisticalMeanAbs.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,23 @@ class StatisticalMeanAbsPrimitive(transformer.TransformerPrimitiveBase[Inputs, O
"""
Primitive to find mean_abs of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'c397f0b2-45da-4263-8cca-b4e1a9502918',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_abs',
'keywords': ['Time Series','MeanAbs'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMeanAbs.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_abs',
'keywords': ['Time Series','MeanAbs'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMeanAbsPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMeanAbsTemporalDerivative.py View File

@@ -9,6 +9,7 @@ from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import uuid

import numpy
import typing
@@ -90,36 +91,24 @@ class StatisticalMeanAbsTemporalDerivativePrimitive(transformer.TransformerPrimi
"""
Primitive to find mean_abs_temporal_derivative of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'eb571238-6229-4fe4-94b3-684f043e4dbf',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_abs_temporal_derivative',
'keywords': ['Time Series','MeanAbsTemporalDerivative'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMeanAbsTemporalDerivative.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_abs_temporal_derivative',
'keywords': ['Time Series','MeanAbsTemporalDerivative'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMeanAbsTemporalDerivativePrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMeanTemporalDerivative.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalMeanTemporalDerivativePrimitive(transformer.TransformerPrimitiv
"""
Primitive to find mean_temporal_derivative of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'bc051fbb-836b-414e-ad3e-5bf29c9f78f1',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_temporal_derivative',
'keywords': ['Time Series','MeanTemporalDerivative'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMeanTemporalDerivative.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_mean_temporal_derivative',
'keywords': ['Time Series','MeanTemporalDerivative'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMeanTemporalDerivativePrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMedian.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalMedianPrimitive(transformer.TransformerPrimitiveBase[Inputs, Ou
"""
Primitive to find median of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '9f05a450-c1f0-49f6-971b-dcc3789174d0',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_median',
'keywords': ['Time Series','Median'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMedian.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_median',
'keywords': ['Time Series','Median'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
"hyperparams_to_tune": ['window_size'],
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMedianPrimitive')),

})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMedianAbsoluteDeviation.py View File

@@ -14,6 +14,7 @@ from scipy import stats
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -91,36 +92,24 @@ class StatisticalMedianAbsoluteDeviationPrimitive(transformer.TransformerPrimiti
"""
Primitive to find median_absolute_deviation of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '36e7d739-72c3-4e6e-91b8-b2b64cbe4e12',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_median_abs_deviation',
'keywords': ['Time Series','MedianAbsoluteDeviation'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMedianAbsoluteDeviation.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_median_abs_deviation',
'keywords': ['Time Series','MedianAbsoluteDeviation'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMedianAbsoluteDeviationPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalMinimum.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalMinimumPrimitive(transformer.TransformerPrimitiveBase[Inputs, O
"""
Primitive to find minimum of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '255955d0-1d64-433b-b9f0-e2a1b679be45',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_minimum',
'keywords': ['Time Series','Minimum'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalMinimum.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_minimum',
'keywords': ['Time Series','Minimum'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalMinimumPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalSkew.py View File

@@ -14,6 +14,7 @@ from scipy import stats
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -91,36 +92,24 @@ class StatisticalSkewPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outp
"""
Primitive to find skew of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'cd154af5-8f98-480a-8a72-6a22365c3c6f',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_skew',
'keywords': ['Time Series','Skew'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalSkew.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_skew',
'keywords': ['Time Series','Skew'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalSkewPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalStd.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalStdPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outpu
"""
Primitive to find std of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '652fc98a-8bd9-45a2-8005-dc781bf0c136',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_std',
'keywords': ['Time Series','Std'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalStd.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_std',
'keywords': ['Time Series','Std'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalStdPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 30
tods/feature_analysis/StatisticalVar.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,23 @@ class StatisticalVarPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outpu
"""
Primitive to find var of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '9b237f3f-c638-44f4-adb1-f3f24a173711',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_var',
'keywords': ['Time Series','Var'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalVar.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_var',
'keywords': ['Time Series','Var'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalVarPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 20
- 30
tods/feature_analysis/StatisticalVariation.py View File

@@ -14,6 +14,7 @@ from scipy import stats
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -91,36 +92,25 @@ class StatisticalVariationPrimitive(transformer.TransformerPrimitiveBase[Inputs,
"""
Primitive to find variation of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'ea6e852f-164b-4245-b5e6-02fde55c5491',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_variation',
'keywords': ['Time Series','Variation'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalVariation.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_variation',
'keywords': ['Time Series','Variation'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalVariationPrimitive')),

})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalVecSum.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -90,36 +91,24 @@ class StatisticalVecSumPrimitive(transformer.TransformerPrimitiveBase[Inputs, Ou
"""
Primitive to find vec_sum of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'a5ff2fc8-657e-4c4f-8a4e-6949dd37bf9c',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_vec_sum',
'keywords': ['Time Series','VecSum'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalVecSum.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_vec_sum',
'keywords': ['Time Series','VecSum'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalVecSumPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 19
- 30
tods/feature_analysis/StatisticalWillisonAmplitude.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -94,36 +95,24 @@ class StatisticalWillisonAmplitudePrimitive(transformer.TransformerPrimitiveBase
"""
Primitive to find willison amplitude of time series
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': 'f1dee9fb-7e3b-499d-a559-7979fa4a2e1c',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_willison_amplitude',
'keywords': ['Time Series','WillisonAmplitude'],
"hyperparams_to_tune": ['window_size'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalWillisonAmplitude.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_willison_amplitude',
'keywords': ['Time Series','WillisonAmplitude'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
"hyperparams_to_tune": ['window_size'],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalWillisonAmplitudePrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 18
- 29
tods/feature_analysis/StatisticalZeroCrossing.py View File

@@ -13,6 +13,7 @@ import os
import numpy
import typing
import time
import uuid

from d3m import container
from d3m.primitive_interfaces import base, transformer
@@ -86,35 +87,23 @@ class StatisticalZeroCrossingPrimitive(transformer.TransformerPrimitiveBase[Inpu
"""
Primitive to find zero_crossing of time series. A column indicating zero crossing on ith row . 1 indicates crossing 0 is for normal
"""
__author__ = "DATA Lab at Texas A&M University",
metadata = metadata_base.PrimitiveMetadata(
{
'id': '1064c78f-37e2-45a1-94a3-401a6726c220',
'version': '0.1.0',
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_zero_crossing',
'keywords': ['Time Series','ZeroCrossing'],
'source': {
'name': 'DATA Lab at Texas A&M University',
'uris': ['https://gitlab.com/lhenry15/tods.git','https://gitlab.com/lhenry15/tods/-/blob/devesh/tods/feature_analysis/StatisticalZeroCrossing.py'],
'contact': 'mailto:khlai037@tamu.edu'

},
'installation': [
{'type': metadata_base.PrimitiveInstallationType.PIP,
'package_uri': 'git+https://gitlab.com/lhenry15/tods.git@{git_commit}#egg=TODS'.format(
git_commit=d3m_utils.current_git_commit(os.path.dirname(__file__)),
),
}

],
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.DATA_PROFILING,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,

}
)

metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
'name': 'Time Series Decompostional',
'python_path': 'd3m.primitives.tods.feature_analysis.statistical_zero_crossing',
'keywords': ['Time Series','ZeroCrossing'],
'source': {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu'
},
'version': '0.1.0',
'algorithm_types': [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
'primitive_family': metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'StatisticalZeroCrossingPrimitive')),
})

def produce(self, *, inputs: Inputs, timeout: float = None, iterations: int = None) -> base.CallResult[Outputs]:
"""


+ 15
- 10
tods/feature_analysis/TRMF.py View File

@@ -7,6 +7,7 @@ import sklearn
import numpy as np
import typing
import time
import uuid

# Custom import commands if any
from sklearn.decomposition.truncated_svd import TruncatedSVD
@@ -222,17 +223,21 @@ class TRMFPrimitive(transformer.TransformerPrimitiveBase[Inputs, Outputs, Hyperp
Which can be found there: http://www.cs.utexas.edu/~rofuyu/papers/tr-mf-nips.pdf
"""

__author__: "DATA Lab at Texas A&M University"
metadata = metadata_base.PrimitiveMetadata({
"name": "Temporal Regularized Matrix Factorization Primitive",
"python_path": "d3m.primitives.tods.feature_analysis.trmf",
"source": {'name': 'DATA Lab at Texas A&M University', 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods.git', 'https://gitlab.com/lhenry15/tods/-/blob/Junjie/anomaly-primitives/anomaly_primitives/TRMF.py']},
"algorithm_types": [metadata_base.PrimitiveAlgorithmType.TEMPORAL_REGULARIZED_MATRIX_FACTORIZATION, ],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
"id": "d6be6941-61d0-4cbd-85ef-a10c86aa40b1",
"hyperparams_to_tune": ['lags', 'K', 'lambda_f', 'lambda_x', 'lambda_w', 'alpha', 'eta', 'max_iter', 'F_step', 'X_step', 'W_step'],
"version": "0.0.1",
"__author__": "DATA Lab @ Texas A&M University",
"name": "Temporal Regularized Matrix Factorization Primitive",
"python_path": "d3m.primitives.tods.feature_analysis.trmf",
"source": {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"version": "0.0.1",
"hyperparams_to_tune": ['lags', 'K', 'lambda_f', 'lambda_x', 'lambda_w', 'alpha', 'eta', 'max_iter', 'F_step', 'X_step', 'W_step'],
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_CONSTRUCTION,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'TRMFPrimitive')),
})



+ 15
- 13
tods/feature_analysis/WaveletTransform.py View File

@@ -174,20 +174,22 @@ class WaveletTransformPrimitive(transformer.TransformerPrimitiveBase[Inputs, Out
None
"""

__author__ = "DATALAB @Taxes A&M University"
metadata = metadata_base.PrimitiveMetadata(
{
"name": "Wavelet_transformation",
"python_path": "d3m.primitives.tods.feature_analysis.wavelet_transform",
"source": {'name': "DATALAB @Taxes A&M University", 'contact': 'mailto:khlai037@tamu.edu',
'uris': ['https://gitlab.com/lhenry15/tods.git']},
"algorithm_types": [metadata_base.PrimitiveAlgorithmType.FREQUENCY_TRANSFORM, ],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_EXTRACTION,
"version": "0.0.1",
"hyperparams_to_tune": ['wavelet', 'mode', 'axis', 'level'],
"id": str(uuid.uuid3(uuid.NAMESPACE_DNS, 'WaveletTransformer')),
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
"name": "Wavelet_transformation",
"python_path": "d3m.primitives.tods.feature_analysis.wavelet_transform",
"source": {
'name': "DATA Lab @ Taxes A&M University",
'contact': 'mailto:khlai037@tamu.edu',
},
)
"version": "0.0.1",
"hyperparams_to_tune": ['wavelet', 'mode', 'axis', 'level'],
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.FEATURE_EXTRACTION,
"id": str(uuid.uuid3(uuid.NAMESPACE_DNS, 'WaveletTransformer')),
})

def __init__(self, *, hyperparams: Hyperparams) -> None:
super().__init__(hyperparams=hyperparams) # , random_seed=random_seed, docker_containers=docker_containers)


+ 14
- 14
tods/timeseries_processing/HoltSmoothing.py View File

@@ -112,20 +112,20 @@ class HoltSmoothingPrimitive(UnsupervisedLearnerPrimitiveBase[Inputs, Outputs, P
"""
metadata = metadata_base.PrimitiveMetadata({
"__author__": "DATA Lab @ Texas A&M University",
"name": "statsmodels.preprocessing.HoltSmoothing",
"python_path": "d3m.primitives.tods.timeseries_processing.transformation.holt_smoothing",
"source": {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"version": "0.0.1",
"hyperparams_to_tune": ['endog','use_columns'],
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.DATA_PREPROCESSING,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'HoltSmoothingPrimitive')),
"__author__": "DATA Lab @ Texas A&M University",
"name": "statsmodels.preprocessing.HoltSmoothing",
"python_path": "d3m.primitives.tods.timeseries_processing.transformation.holt_smoothing",
"source": {
'name': 'DATA Lab @ Texas A&M University',
'contact': 'mailto:khlai037@tamu.edu',
},
"version": "0.0.1",
"hyperparams_to_tune": ['endog','use_columns'],
"algorithm_types": [
metadata_base.PrimitiveAlgorithmType.TODS_PRIMITIVE,
],
"primitive_family": metadata_base.PrimitiveFamily.DATA_PREPROCESSING,
'id': str(uuid.uuid3(uuid.NAMESPACE_DNS, 'HoltSmoothingPrimitive')),
})

def __init__(self, *,


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