m4.ground package¶

m4.ground.geo module¶

Autors

1. Briguglio: created on Mon Mar 16 11:00:08 2020
F Miceli: add functionality on march 2022

m4.ground.geo.draw_mask(img, cx, cy, r, out=0)¶

Function to create circular mask Created by Runa

Parameters:	img (numpy array) – image to mask cx (int [pixel]) – center x of the mask cy (int [pixel]) – center y of the mask r (int [pixel]) – radius of the mask
Returns:	img1 – start image mask whit circular new mask
Return type:	numpy array

m4.ground.geo.qpupil(mask, xx=None, yy=None, nocircle=0)¶

Function for…. created by Runa

Parameters:	mask (numpy array) –
Returns:	x0 y0 r xx (numpy array) – grid of coordinates of the same size as input mask yy (numpy array) – grid of coordinates of the same size as input mask

m4.ground.geo.qpupil_circle(image, pixel_dir=0)¶

Function for… Created by Federico NOTA: la funzione usa come standard la direzione y per determinare la dimensione dei pixel

pixel_dir: int: indicates which direction to use for counting the number of pixels in the image. Y direction as standard

m4.ground.geo.qpupil_ellipse(image, pixel_dir=0)¶: Function for… Created by Federico NOTA: la funzione usa come standard la direzione y per determinare la dimensione dei pixel

m4.ground.geo.rotate(img, angle)¶

Function to rotate the image Created by Runa

Parameters:	image (numpy array) – The input array angle (float) – The rotation angle in degrees
Returns:	img1 – The rotated input
Return type:	numpy array

m4.ground.GUI module¶

m4.ground.logger_set_up module¶

Autors

1. Selmi: written in September 2020

Function to start the log:

from m4.ground import logger_set_up
logger_set_up.set_up_logger(file_path, logging_level)

m4.ground.logger_set_up.set_up_logger(file_path, logging_level)¶

Set up logger for the application

Parameters:	file_path (string) – file path and log name (txt) where to create the log logging_level (int) – Warning = 30, Info = 20, Debug = 10, Notset = 0

m4.ground.ottInformation module¶

Authors

1. Selmi: written in 2021

class m4.ground.ottInformation.OttInformation(ott, interf)¶

Bases: object

HOW TO USE IT:

from m4.configuration import start
ott, interf = start.create_ott('../M4/Data/SYSCONFData/Config.yaml')
from m4.ground.ottInformation import OttInformation
info = OttInformation(ott, interf)

acquireAndLogOttPositions()¶: Function for reading and logging of current test tower positions

interferogramTimeHistory(n_measure, delay_in_seconds)¶

Parameters:	n_measure (int) – number of measurements to acquire delay_in_seconds (int [s]) – time in seconds for delay between the measurements
Returns:	cube – meauserements cube
Return type:	numpy masked array [pixel, pixel, n_measure]

temperatureTimeHistory(n_measure, delay_in_seconds)¶

Parameters:	n_measure (int) – number of measurements to acquire delay_in_seconds (int [s]) – time in seconds for delay between the measurements
Returns:	temp_matrix – meauserements matrix
Return type:	numpy array [n_measure, num_PT_sensor]

m4.ground.read_data module¶

Authors

1. Selmi: written in 2019

Function for reading file fits:

from m4.ground import read_data
numpy_array_data = read_data.readFits_object(fits_file_path)
or
numpy_masked_array_data = read_data.readFits_maskedImage(fits_file_path)
or
amplitude, mode_vector, cmd_matrix = read_data.readTypeFromFitsName(
                            'ampName.fits', 'mvec.fits', 'cmdMatrix.fits')

class m4.ground.read_data.InterferometerConverter¶

Bases: object

Class to use to convert H5 files to masked array

static fromFakeInterf(filename)¶

Function for fake interferometer :param file: path name for data :type file: string

Returns:	ima – masked array image
Return type:	numpy masked array

static fromI4DToSimplerData(i4dname, folder, h5name)¶

Function for converting files from 4d 6110 files to H5 files :param i4dname: file name path of 4d data :type i4dname: string :param folder: folder path for new data :type folder: string :param h5name: name for h5 data :type h5name: string

Returns:	file_name – finale path name
Return type:	string

static fromPhaseCam4020(h5filename)¶

Function for PhaseCam4020 :param h5filename: path of h5 file to convert :type h5filename: string

Returns:	ima – masked array image
Return type:	numpy masked array

static fromPhaseCam6110(i4dfilename)¶

Function for PhaseCam6110 :param h5filename: path of h5 file to convert :type h5filename: string

Returns:	ima – masked array image
Return type:	numpy masked array

m4.ground.read_data.readFitsSlimImage(fits_file_path)¶

Parameters:	fits_file_path (string) – fits file path of masked array to read
Returns:	immagine
Return type:	numpy masked array

m4.ground.read_data.readFits_data(fits_file_path)¶

Parameters:	fits_file_path (string) – fits file path of numpy array to read
Returns:	object
Return type:	numpy array

m4.ground.read_data.readFits_maskedImage(fits_file_path)¶

Parameters:	fits_file_path (string) – fits file path of masked array to read
Returns:	masked_array
Return type:	numpy masked array

m4.ground.read_data.readTypeFromFitsName(amplitude_fits_file_name, mode_vector_fits_file_name, cmd_matrix_fits_file_name)¶

Parameters:

amplitude_fits_file_name (string) – vector with mode amplitude fits file name
mode_vector_fits_file_name (string) – mode or actuator index vector to be applied fits file name
cmd_matrix_fits_file_name (string) – matrix of mode commands fits file name

Returns:

amplitude (numpy array) – vector with mode amplitude
modesVector (numpy array) – mode or actuator index vector to be applied
cmd_matrix (numpy array [nActs x nModes]) – matrix of mode commands diagonal matrix in case of zonal commands

m4.ground.read_data.read_phasemap(file_path)¶: per leggere i tre formati di dati interferometrici

m4.ground.rebinner module¶

Authors

1. Selmi: written in April 2020

m4.ground.rebinner.rebin(a, *args)¶

rebin ndarray data into a smaller ndarray of the same rank whose dimensions are factors of the original dimensions. eg. An array with 6 columns and 4 rows can be reduced to have 6,3,2 or 1 columns and 4,2 or 1 rows. example usages: >>> a=rand(6,4); b=rebin(a,3,2) >>> a=rand(6); b=rebin(a,2)

Parameters:	a (numpy array) – vector for rebin args (int*) – new dimension for vector

m4.ground.rebinner.rebin2(a, shape)¶

m4.ground.rebinner.rebin2DArray(a, new_shape, sample=False)¶

Replacement of IDL’s rebin() function for 2d arrays. Resizes a 2d array by averaging or repeating elements. New dimensions must be integral factors of original dimensions, otherwise a ValueError exception will be raised. :param a: Input array. :type a: ndarray :param new_shape: Shape of the output array :type new_shape: 2-elements sequence :param sample: if True, when reducing the array side elements are set

using a nearest-neighbor algorithm instead of averaging. This parameter has no effect when enlarging the array.

Returns:	rebinned_array – If the new shape is smaller of the input array the data are averaged, unless the sample parameter is set. If the new shape is bigger array elements are repeated.
Return type:	ndarray
Raises:	`ValueError` – in the following cases: new_shape is not a sequence of 2 values that can be converted to int new dimensions are not an integral factor of original dimensions `NotImplementedError` – - one dimension requires an upsampling while the other requires a downsampling

Examples

>>> a = np.array([[0, 1], [2, 3]])
>>> b = rebin(a, (4, 6)) #upsize
>>> b
array([[0, 0, 0, 1, 1, 1],
       [0, 0, 0, 1, 1, 1],
       [2, 2, 2, 3, 3, 3],
       [2, 2, 2, 3, 3, 3]])
>>> rebin(b, (2, 3)) #downsize
array([[0. , 0.5, 1. ],
       [2. , 2.5, 3. ]])
>>> rebin(b, (2, 3), sample=True) #downsize
array([[0, 0, 1],
       [2, 2, 3]])

m4.ground.smooth_function module¶

Autors

1. Selmi: written in 2020

Function for data smoothing:

form m4.ground import smooth_function
ss = smooth_function.smooth(data, WSZ)

m4.ground.smooth_function.smooth(a, WSZ)¶

‘

Parameters:	a (NumPy 1-D array) – containing the data to be smoothed WSZ (int) – smoothing window size needs, which must be odd number, as in the original MATLAB implementation
Returns:	smooth – smoothd data
Return type:	numpy array

m4.ground.timestamp module¶

HOW TO USE IT:

from m4.ground.timestamp import Timestamp
now = Timestamp.now()
today = Timestamp.today()
or
ts = Timestamp()
now = ts.asNowString()
today = ts.asTodayString()

class m4.ground.timestamp.Timestamp¶

Bases: object

Class for tracking numbers generation

asNowString()¶

Returns:	now – yearMonthDay_hoursMinutesSeconds
Return type:	string

asTodayString()¶

Returns:	today – year month day
Return type:	string

static now()¶

Returns:	now – yearMonthDay_hoursMinutesSeconds
Return type:	string

static today()¶

Returns:	today – year month day
Return type:	string

m4.ground.tracking_number_folder module¶

Authors

1. Selmi: written in 2019
  
  modified in July 2021

HOW TO USE IT:

from m4.ground import tracking_numbers_folder as tnf
path, tt = tnf.createFolderToStoreMeasurements(store_in_folder)
or
path = tnf.findTrackingNumberPath(tt)

m4.ground.tracking_number_folder.createFolderToStoreMeasurements(store_in_folder)¶

Create a new folder using the generation of the tracking number

Parameters:	store_in_folder (string) – path where to create new fold
Returns:	dove (string) – all path generated tt (string) – only tracking number

m4.ground.tracking_number_folder.findTrackingNumberPath(tt)¶

Function to find the entire path from tracking number

Parameters:	tt (string) – tracking number
Returns:	final_path – total path
Return type:	string

m4.ground.zabbix module¶

m4.ground.zernike module¶

@file zernike.py @brief Zernike generation library @author M.Xompero @url - @date 20200202

This file is licensed under the Creative Commons Attribution-Share Alike license versions 3.0 or higher, see http://creativecommons.org/licenses/by-sa/3.0/

HOW TO USE IT:

from m4.ground import zernike
coeff, mat = zernike.zernikeFit(img, zernike_index_vector)
surf_image = zernike.zernikeSurface(img, coef, mat)

m4.ground.zernike.zernikeFit(img, zernike_index_vector, qpupil=True)¶

Parameters:

img (numpy masked array) – image for zernike fit
zernike_index_vector (numpy array) – vector containing the index of Zernike modes to be fitted starting from 1

Returns:

coeff (numpy array [m]) – vector of zernike coefficients
mat (numpy array)

m4.ground.zernike.zernikeFitAuxmask(img, auxmask, zernike_index_vector)¶

Parameters:

img (numpy masked array) – image for zernike fit
auxmask (numpy array) – zero for masked point
zernike_index_vector (numpy array) – vector containing the index of Zernike modes to be fitted starting from 1

Returns:

coeff (numpy array [m]) – vector of zernike coefficients
mat (numpy array)

m4.ground.zernike.zernikeSurface(img, coef, mat)¶

Parameters:	img (numpy masked array) – image for zernike fit coeff (numpy array [m]) – vector of zernike coefficients mat (numpy array) –
Returns:	surf – zernike surface generate by coeff
Return type:	numpy masked array

m4.ground package¶

m4.ground.geo module¶

m4.ground.GUI module¶

m4.ground.logger_set_up module¶

m4.ground.ottInformation module¶

m4.ground.read_data module¶

m4.ground.rebinner module¶

m4.ground.smooth_function module¶

m4.ground.timestamp module¶

m4.ground.tracking_number_folder module¶

m4.ground.zabbix module¶

m4.ground.zernike module¶

Table of Contents

Previous topic

Next topic

This Page