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Commit 6f6039fd authored by dlandre2's avatar dlandre2
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maj

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characterizationUseCase.py
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#### **Seasonal study of user demand and IT system usage in datacenters artifact**
**Brief presentation:**
This directory contains the data and python files used to obtain the results of the study on the characterization of the seasonality of different time series from 6 HPC workloads and from the Wikipedia workload. The directory consists of the following elements:
......@@ -10,6 +12,8 @@ This directory contains the data and python files used to obtain the results of
- The "characterizationUseCase.py" file allows you to run and obtain the results of the characterization use case example.
Python files were run using python 3.
**Packages needed:**
......@@ -23,7 +27,7 @@ This directory contains the data and python files used to obtain the results of
- sktime (to use the TBATS forecasting method)
- scipy (to use the periodogram, the Kruskal-Wallis test and the gaussian_kde method)
- scikit_posthocs (to use the Conover-Iman test)
- statsmodels (to use the ADF test, the KPSS test and the lowess, MSTL and STL methods)
- statsmodels (to use the ADF test, the KPSS test and the LOWESS, MSTL and STL methods)
......
......@@ -60,9 +60,6 @@ m = Prophet(seasonality_mode = 'additive',
daily_seasonality=True,
weekly_seasonality=True,
yearly_seasonality=False)
# m.add_country_holidays(country_name = 'US') # Vacances du pays dans lequel a tourné le workload
# m.add_seasonality(name = 'monthly', period = 84, fourier_order = results[0][1]) # Autre saisonnalité
m.fit(df[:-steps])
future = m.make_future_dataframe(periods = steps, freq = 'H')
future['floor'] = 0
......
File added
......@@ -2,120 +2,120 @@ import json
### Maximum number of allocated cores by the system
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemAnlIntrepid.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemAnlIntrepid.json"
with open(filename, 'r') as file:
AllocatedCoresSystemAnlIntrepid = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemCiematEuler.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemCiematEuler.json"
with open(filename, 'r') as file:
AllocatedCoresSystemCiematEuler = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemMetacentrum.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemMetacentrum.json"
with open(filename, 'r') as file:
AllocatedCoresSystemMetacentrum = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemMetacentrumFiltered.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemMetacentrumFiltered.json"
with open(filename, 'r') as file:
AllocatedCoresSystemMetacentrumFiltered = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemPIKIPLEX.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemPIKIPLEX.json"
with open(filename, 'r') as file:
AllocatedCoresSystemPIKIPLEX = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemRICC.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemRICC.json"
with open(filename, 'r') as file:
AllocatedCoresSystemRICC = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemUniLuGaia.json"
filename = "time_series_json_hpc_data/AllocatedCoresSystemUniLuGaia.json"
with open(filename, 'r') as file:
AllocatedCoresSystemUniLuGaia = json.load(file)
### Maximum number of requested cores by the users
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresAnlIntrepid.json"
filename = "time_series_json_hpc_data/AllocatedCoresAnlIntrepid.json"
with open(filename, 'r') as file:
AllocatedCoresAnlIntrepid = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresCiematEuler.json"
filename = "time_series_json_hpc_data/AllocatedCoresCiematEuler.json"
with open(filename, 'r') as file:
AllocatedCoresCiematEuler = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresMetacentrum.json"
filename = "time_series_json_hpc_data/AllocatedCoresMetacentrum.json"
with open(filename, 'r') as file:
AllocatedCoresMetacentrum = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresMetacentrumFiltered.json"
filename = "time_series_json_hpc_data/AllocatedCoresMetacentrumFiltered.json"
with open(filename, 'r') as file:
AllocatedCoresMetacentrumFiltered = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresPIKIPLEX.json"
filename = "time_series_json_hpc_data/AllocatedCoresPIKIPLEX.json"
with open(filename, 'r') as file:
AllocatedCoresPIKIPLEX = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresRICC.json"
filename = "time_series_json_hpc_data/AllocatedCoresRICC.json"
with open(filename, 'r') as file:
AllocatedCoresRICC = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresUniLuGaia.json"
filename = "time_series_json_hpc_data/AllocatedCoresUniLuGaia.json"
with open(filename, 'r') as file:
AllocatedCoresUniLuGaia = json.load(file)
### Workload mass
filename = "hpc_case/time_series_json_hpc_data/MassJobsAnlIntrepid.json"
filename = "time_series_json_hpc_data/MassJobsAnlIntrepid.json"
with open(filename, 'r') as file:
MassJobsAnlIntrepid = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsCiematEuler.json"
filename = "time_series_json_hpc_data/MassJobsCiematEuler.json"
with open(filename, 'r') as file:
MassJobsCiematEuler = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsMetacentrum.json"
filename = "time_series_json_hpc_data/MassJobsMetacentrum.json"
with open(filename, 'r') as file:
MassJobsMetacentrum = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsMetacentrumFiltered.json"
filename = "time_series_json_hpc_data/MassJobsMetacentrumFiltered.json"
with open(filename, 'r') as file:
MassJobsMetacentrumFiltered = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsPIKIPLEX.json"
filename = "time_series_json_hpc_data/MassJobsPIKIPLEX.json"
with open(filename, 'r') as file:
MassJobsPIKIPLEX = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsRICC.json"
filename = "time_series_json_hpc_data/MassJobsRICC.json"
with open(filename, 'r') as file:
MassJobsRICC = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/MassJobsUniLuGaia.json"
filename = "time_series_json_hpc_data/MassJobsUniLuGaia.json"
with open(filename, 'r') as file:
MassJobsUniLuGaia = json.load(file)
### Number of jobs
filename = "hpc_case/time_series_json_hpc_data/NumberJobsAnlIntrepid.json"
filename = "time_series_json_hpc_data/NumberJobsAnlIntrepid.json"
with open(filename, 'r') as file:
NumberJobsAnlIntrepid = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsCiematEuler.json"
filename = "time_series_json_hpc_data/NumberJobsCiematEuler.json"
with open(filename, 'r') as file:
NumberJobsCiematEuler = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsMetacentrum.json"
filename = "time_series_json_hpc_data/NumberJobsMetacentrum.json"
with open(filename, 'r') as file:
NumberJobsMetacentrum = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsMetacentrumFiltered.json"
filename = "time_series_json_hpc_data/NumberJobsMetacentrumFiltered.json"
with open(filename, 'r') as file:
NumberJobsMetacentrumFiltered = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsPIKIPLEX.json"
filename = "time_series_json_hpc_data/NumberJobsPIKIPLEX.json"
with open(filename, 'r') as file:
NumberJobsPIKIPLEX = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsRICC.json"
filename = "time_series_json_hpc_data/NumberJobsRICC.json"
with open(filename, 'r') as file:
NumberJobsRICC = json.load(file)
filename = "hpc_case/time_series_json_hpc_data/NumberJobsUniLuGaia.json"
filename = "time_series_json_hpc_data/NumberJobsUniLuGaia.json"
with open(filename, 'r') as file:
NumberJobsUniLuGaia = json.load(file)
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