Python process_dataset示例

示例#1

文件： test_artificial_1024_Quantization_PolyTrend_0__20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="PolyTrend",
                    cycle_length=0,
                    transform="Quantization",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#2

文件： test_artificial_32_RelativeDifference_Lag1Trend_7_12_20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="Lag1Trend",
                    cycle_length=7,
                    transform="RelativeDifference",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=12)

示例#3

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingAverage",
                    cycle_length=7,
                    transform="Logit",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=12)

示例#4

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingMedian",
                    cycle_length=30,
                    transform="BoxCox",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=12)

示例#5

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="PolyTrend",
                    cycle_length=12,
                    transform="None",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#6

文件： test_artificial_1024_Logit_LinearTrend_0_12_20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="LinearTrend",
                    cycle_length=0,
                    transform="Logit",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=12)

示例#7

文件： test_artificial_128_None_LinearTrend_5__0.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="LinearTrend",
                    cycle_length=5,
                    transform="None",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=0)

示例#8

文件： test_artificial_1024__poly_7__20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="poly",
                    cycle_length=7,
                    transform="None",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#9

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingAverage",
                    cycle_length=5,
                    transform="BoxCox",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=12)

示例#10

文件： test_artificial_32_RelativeDifference_MovingAverage_0__20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingAverage",
                    cycle_length=0,
                    transform="RelativeDifference",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#11

文件： test_artificial_1024_inv_constant_30__20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="constant",
                    cycle_length=30,
                    transform="inv",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#12

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 1024 , FREQ = 'D', seed = 0, trendtype = "LinearTrend", cycle_length = 7, transform = "Anscombe", sigma = 0.0, exog_count = 0, ar_order = 0);

示例#13

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingAverage",
                    cycle_length=30,
                    transform="Quantization",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=0)

示例#14

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 32 , FREQ = 'D', seed = 0, trendtype = "MovingAverage", cycle_length = 12, transform = "Fisher", sigma = 0.0, exog_count = 100, ar_order = 12);

示例#15

文件： test_artificial_128_RelativeDifference_PolyTrend_0__0.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="PolyTrend",
                    cycle_length=0,
                    transform="RelativeDifference",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=0)

示例#16

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingMedian",
                    cycle_length=7,
                    transform="None",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=0)

示例#17

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 128 , FREQ = 'D', seed = 0, trendtype = "MovingMedian", cycle_length = 30, transform = "Anscombe", sigma = 0.0, exog_count = 0, ar_order = 0);

示例#18

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="Lag1Trend",
                    cycle_length=30,
                    transform="BoxCox",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=0)

示例#19

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="ConstantTrend",
                    cycle_length=12,
                    transform="BoxCox",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=0)

示例#20

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 128 , FREQ = 'D', seed = 0, trendtype = "Lag1Trend", cycle_length = 12, transform = "Integration", sigma = 0.0, exog_count = 100, ar_order = 0);

示例#21

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="Lag1Trend",
                    cycle_length=30,
                    transform="Anscombe",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=0)

示例#22

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="ConstantTrend",
                    cycle_length=0,
                    transform="Difference",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=0)

示例#23

文件： test_artificial_1024_RelativeDifference_MovingMedian_5__0.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=1024,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingMedian",
                    cycle_length=5,
                    transform="RelativeDifference",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=0)

示例#24

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="MovingMedian",
                    cycle_length=7,
                    transform="Quantization",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=12)

示例#25

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 128 , FREQ = 'D', seed = 0, trendtype = "MovingAverage", cycle_length = 7, transform = "Integration", sigma = 0.0, exog_count = 20, ar_order = 0);

示例#26

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art




art.process_dataset(N = 128 , FREQ = 'D', seed = 0, trendtype = "PolyTrend", cycle_length = 5, transform = "BoxCox", sigma = 0.0, exog_count = 0, ar_order = 0);

示例#27

文件： test_artificial_128_Integration_PolyTrend_30_12_0.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="PolyTrend",
                    cycle_length=30,
                    transform="Integration",
                    sigma=0.0,
                    exog_count=0,
                    ar_order=12)

示例#28

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=128,
                    FREQ='D',
                    seed=0,
                    trendtype="Lag1Trend",
                    cycle_length=7,
                    transform="Fisher",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=12)

示例#29

文件： test_artificial_32_Integration_ConstantTrend_0__100.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="ConstantTrend",
                    cycle_length=0,
                    transform="Integration",
                    sigma=0.0,
                    exog_count=100,
                    ar_order=0)

示例#30

文件： test_artificial_32_Quantization_LinearTrend_5_12_20.py 项目： olivier2311/pyaf

import pyaf.Bench.TS_datasets as tsds
import tests.artificial.process_artificial_dataset as art

art.process_dataset(N=32,
                    FREQ='D',
                    seed=0,
                    trendtype="LinearTrend",
                    cycle_length=5,
                    transform="Quantization",
                    sigma=0.0,
                    exog_count=20,
                    ar_order=12)