m4.type package

m4.type.accelerometers_data module

Authors
    1. Selmi: written in 2021
class m4.type.accelerometers_data.AccelerometersData

Bases: object

Class used to manage accelerometer data

HOW TO USE IT:

from m4.type.accelerometers_data import AccelerometersData
acc = AccelerometersData()
or
acc = AccelerometersData.loadInfoFromAccTtFolder()
convertAndSaveData(start, final_destination)
Parameters:
  • start (string) – path containing the initial data
  • final_destination (string) – path to save final data
counts_to_ms2(vec)
Parameters:vec (numpy array) – data vector in accelerometers plc units
Returns:cal_vec – data vector in m/s*2
Return type:numpy array
static loadInfoFromAccTtFolder(tt)

Creates the object using information about path measurements

Parameters:tt (string) – measurement tracking number
Returns:theObject – acceleremoters data type class object
Return type:object
power_spectrum()
Returns:
  • spe_list (list) – list containing the spectrum of vectors composing the matrix z
  • freq_list (list) – list containing the frequencies of vectors composing the matrix z
read_data()
Returns:_datah5 – measurements data
Return type:numpy array

m4.type.commandHistory module

Authors
    1. Selmi: written in 2019
class m4.type.commandHistory.CmdHistory(nActs)

Bases: object

Class to create and manage the command history matrix

HOW TO USE IT:

from m4.type.commandHistory import CmdHistory
cmdH = CmdHistory()
getCommandHistory()
Returns:ccmdHToApply – command history matrix to apply
Return type:numpy array
getIndexingList()
Returns:indexingList – list of modes/actuators used to create the command history matrix
Return type:list
static load(tt, fits_or_h5=0)

Creates the object from the info.fits file located in tt

Parameters:tt (string) – tracking number
Returns:theObject – command history class object
Return type:object
saveInfo(fits_or_h5)

Save the data in fits format

Returns:tt – tracking number
Return type:string
shuffleCommandHistoryMaker(mode_vector, amp_vector, cmd_matrix, n_push_pull, template=None)
Parameters:
  • modesVector (numpy array) – Mode or actuator index vector to apply
  • ampVector (numpy array) – amplitude mode vector
  • cmdMatrix (numpy array [nActs x nModes]) – mode command matrix diagonal matrix in case of zonal commands
  • n_push_pull (int) – number of push pull for actuatores
Other Parameters:
 

template (numpy array , optional) – vector composed by 1 and -1 (es. np.array([1, -1, 1]))
Returns:

  • matrixToApply (numpy array [nAct, nModes x nPushPusll x 2]) – shuffle command history
  • tt (string) – tracking number
tidyCommandHistoryMaker(mode_vector, amp_vector, cmd_matrix, n_push_pull, template=None)
Parameters:
  • modesVector (numpy array) – Mode or actuator index vector to apply
  • ampVector (numpy array) – amplitude mode vector
  • cmdMatrix (numpy array [nActs x nModes]) – mode command matrix diagonal matrix in case of zonal commands
  • n_push_pull (int) – number of push pull for actuatores
Other Parameters:
 

template (numpy array , optional) – vector composed by 1 and -1 (es. np.array([1, -1, 1]))
Returns:

  • matrixToApply (numpy array [nAct, nModes x nPushPusll x 2]) – tidy command history
  • tt (string) – tracking number

m4.type.modalAmplitude module

Autors
    1. Selmi: written in 2019
class m4.type.modalAmplitude.ModalAmplitude

Bases: object

Class to create and manage the modal amplitude

HOW TO USE IT:

from m4.type.modalAmplitude import ModalAmplitude
ma = ModalAmplitude()
getFitsFileName()
Returns:fitsfilename – path fits file name
Return type:string
getModalAmplitude()
Returns:modalAmplitude – vector of modal amplitude
Return type:numpy array
getTag()
Returns:tag – modal ampplitude tag
Return type:string
static loadFromFits(fits_file_name)

Creates the object

Parameters:fits_file_name (string) – modal amplitude path
Returns:theObject – ModalAmplitude class object
Return type:object
static loadFromH5(filename)

Creates the object

Parameters:filename (string) – modal amplitude path
Returns:theObject – ModalAmplitude class object
Return type:object
saveAsFits(tag, modal_amplitude)

Save the data in fits format

Parameters:
  • tag (string) – file name to save
  • modal_amplitude (numpy array) – vector of amplitude
saveAsH5(tag, modal_amplitude)

Save the data in h5 format

Parameters:
  • tag (string) – file name to save
  • modal_amplitude (numpy array) – vector of amplitude

m4.type.modalBase module

@author: cs

class m4.type.modalBase.ModalBase

Bases: object

Class to create and manage the modal base

HOW TO USE IT:

from m4.type.modalBase import ModalBase
mb = ModalBase()
getFitsFileName()
Returns:fitsfilename – path fits file name
Return type:string
getModalBase()
Returns:modalBase – vector of modal base
Return type:numpy array
getTag()
Returns:tag – modal base tag
Return type:string
static loadFromFits(fits_file_name)

Creates the object

Parameters:fits_file_name (string) – modal amplitude path
Returns:theObject – ModalBase class object
Return type:object
static loadFromH5(filename)

Creates the object

Parameters:filename (string) – modal amplitude path
Returns:theObject – ModalBase class object
Return type:object
saveAsFits(tag, modal_base)

Save the data in fits format

Parameters:
  • tag (string) – file name to save
  • modal_base (numpy array [nActs x nModes]) – command matrix
saveAsH5(tag, modal_base)

Save the data in h5 format

Parameters:
  • tag (string) – file name to save
  • modal_bace (numpy array) – vector of modal base

m4.type.modesVector module

@author: cs

class m4.type.modesVector.ModesVector

Bases: object

Class to create and manage the mode vector

HOW TO USE IT:

from m4.type.modesVector import ModesVestor
mv = ModesVector()
getFitsFileName()
Returns:fitsfilename – path fits file name
Return type:string
getModesVector()
Returns:modesVector – vector of modes
Return type:numpy array
getTag()
Returns:tag – mode vector tag
Return type:string
static loadFromFits(fits_file_name)

Creates the object

Parameters:fits_file_name (string) – modal amplitude path
Returns:theObject – ModaesVector class object
Return type:object
static loadFromH5(filename)

Creates the object

Parameters:filename (string) – modal amplitude path
Returns:theObject – ModesVector class object
Return type:object
saveAsFits(tag, modes_vector)

Save the data in fits format

Parameters:
  • tag (string) – file name to save
  • modes_vector (numpy array) – vector of selected modes
saveAsH5(tag, modes_vector)

Save the data in h5 format

Parameters:
  • tag (string) – file name to save
  • modes_vector (numpy array) – vector of selectred modes

m4.type.temperature_sensors module

Authors
    1. Selmi: written in 2020

    HOW TO USE IT:

    from m4.type import temperature_sensor as ts
folder = ts.PT_calibration(n_meas)
ts.analyzer_PT_meas(tt)
m4.type.temperature_sensors.PT_calibration(n_meas)
Parameters:n_meas (int) – number of measurement to store
Returns:dove – data file path of measurement
Return type:string
m4.type.temperature_sensors.analyzer_PT_meas(tt)
Parameters:tt (string) – tracking number folder

Module contents