Workspace

class comokit4py.Workspace(gama: comokit4py.Gama, explorationPlan: comokit4py.GamaExploration, workspaceDirectory: str, rebuildWorkspace: bool = False)

Bases: object

Constructor for Workspace object

Parameters

• gama (Gama) – Gama object for launching exploration

• explorationPlan (GamaExploration) – GamaExploration object to know what to launch

• workspaceDirectory (str) – Directory path when everything will be store

• _edf (bool) – (Optional) toto

• _sbatch (dict) – (Generated) toto

• _processedOutputVariable (dict) – (Generated) toto

Returns

Workspace object

__init__(gama: comokit4py.Gama, explorationPlan: comokit4py.GamaExploration, workspaceDirectory: str, rebuildWorkspace: bool = False)

Constructor for Workspace object

Parameters

• gama (Gama) – Gama object for launching exploration

• explorationPlan (GamaExploration) – GamaExploration object to know what to launch

• workspaceDirectory (str) – Directory path when everything will be store

• rebuildWorkspace (bool) – (Optional) Destroy and rebuild folder architecture [Default: False]

Returns

Workspace object

generateCsv(output: Optional[list] = None, outputCsvFileName: str = 'out') → bool

Turn COMOKIT’s raw output CSV into compiled csv file

Parameters

• output (list) – (Optional) Output list of raw processed data [Default re-process data]

• outputCsvFileName (str) – (Optional) Name of the png file name (extension automatic) [Default = ‘out’]

Returns

Bool if csv file saved

generateNeededForExploration() → None

Create all XML files for running GAMA headless

Returns

None

generatePng(title: str = '', output: Optional[list] = None, outputPngFileName: list = 'out') → bool

Turn COMOKIT’s raw output CSV into a png graphs

Parameters

• title (str) – (Optional) Output in png title [Default Disable]

• output (list) – (Optional) Output list of raw processed data [Default re-process data]

• outputPngFileName (list) – (Optional) Name of the png file name (extension automatic) [Default = ‘out’]

Returns

Bool if png file saved

getEdfBool() → bool

prepareProcessedOutput(displayStep: int = 24, median: bool = False, quartile: bool = False, startDate: Optional[list] = None, startPolicyDate: Optional[list] = None, endPolicyDate: Optional[list] = None, cores: int = 2, stepTo: int = 1, output_name: list = ['Susceptible', 'Recovered', 'Presymptomatic', 'Asymptomatic', 'Symptomatic', 'Need hospital', 'Need ICU', 'Death'], output_color: list = ['g', 'b', 'olive', 'lightgreen', 'y', 'orange', 'r', 'm']) → None

Prepare private variables for following functions generating CSV or PNG output files

Parameters

• displayStep (int) – (Optional) Output list of raw processed data [Default re-process data]

• median (bool) – (Optional) Display median curve in graph [Default False]

• quartile (bool) – (Optional) Display quartile curves in graph (override median option) [Default False]

• startDate (list[3]) – (Optional) Set starting real date in PNG x axis [Default None]

• startPolicyDate (list[3]) – (Optional) Set starting policy grey area in PNG (needs startDate and endPolicyDate) [Default None]

• endPolicyDate (list[3]) – (Optional) Set starting policy grey area in PNG (needs –startDate and –startPolicy) [Default toto]

• cores (int) – (Optional) Number of core to use [Default Max number of cores available]

• stepTo (int) – (Optional) Compile several steps in one [Default 1 => Disable]

• output_name (list) – (Optional) List of outputed graphs [Default [“Susceptible”, “Recovered”, “Presymptomatic”, “Asymptomatic”, “Symptomatic”, “Need hospital”, “Need ICU”, “Death”] ]

• output_color (list) – (Optional) Colors of outputed graphs [Default [“g”, “b”, “olive”, “lightgreen”, “y”, “orange”, “r”, “m”]]

Warning

Date parameter should follow this form : [YYYY, MM, DD] (list of int)

⚠️ Changing value of output_name and output_color may break following self.generateCsv() and self.generatePng() functions ⚠️

Returns

None

prepareSBatch(jobTimeout: int, core: int, nodes: int = 1, submission: int = 1, maxSubmission: int = 6, delay: int = 0) → None

Create all needed structures and files to launch SLURM sbatch job

Parameters

• jobTimeout (int) – Limit hour for SLURM job

• core (int) – Number of cores used per node

• nodes (int) – (Optional) Number of nodes used by SLURM [Default = 1]

• submission (int) – (Optional) Total of submission on SLURM [Default = 1]

• maxSubmission (int) – (Optional) Max number of active submission on SLURM [Default = 6]

• delay (int) – (Optional) Delay in between launching headless (ex. 2s, 3m, 4h, 5d) [Default = 0]

Returns

None

rawOutputProcessing() → list

Compiled COMOKIT’s raw output CSV into saveable list

Returns

Python list of post-processed COMOKIT explored data

rebuildWorkspace() → None

Destroy and rebuild folder architecture

Returns

None

runGamaHeadless(log: bool = True, logFileName: str = 'out.log', cores: int = 1) → None

Create all needed structures and files to launch SLURM sbatch job

Parameters

• log (bool) – (Optional) Log slurm output in file [Default = True]

• logFileName (str) – (Optional) Name of the log file [Default = ‘out.log’]

• core (int) – (Optional) Number of cores allowed to GAMA [Default = 1]

Returns

None

runSlurm(log: bool = True, logFileName: str = 'out.log') → None

Create all needed structures and files to launch SLURM sbatch job

Parameters

• log (bool) – (Optional) Log slurm output in file [Default = True]

• logFileName (str) – (Optional) Name of the log file [Default = ‘out.log’]

Returns

None

setEdfBool(edf: bool) → None

toggleEdfBool() → None

verifyAll(slurm: bool = False) → bool

Check if everything (GAMA, Java, Slurm?) is installed and usable

Parameters

slurm (bool) – (Optional) Check also for SLURM

Returns

Bool if everything is ready

verifyGama() → bool

Check if GAMA is ready to use in this workspace

Returns

Bool if everything is ready

verifyJavaVersion() → bool

Check if the good Java is installed and usable

Returns

Bool if everything is ready

verifySlurm() → bool

Check if the slurm is installed and usable

Returns

Bool if everything is ready