Welcome to Tapy

Let's fire up

Eventually you can hack the functions.py in order to tune or create functionts that suit your purpose better



In [53]:

    
%matplotlib inline
from functions import read_data,cropped,createIm,normalization,saveIm,binning,oscillation,createIm_fft

Data folders

Open Beam data path:



In [54]:

    
path_ob = 'yokeFolder/data/spin_ON'

Sample data path:



In [55]:

    
path_im = 'yokeFolder/data/spin_OFF'

Dark current data path:



In [56]:

    
path_dc = 'yokeFolder/data/dc'

Setting parameters

Binning:



In [57]:

    
bin_fac = None

ROI for normalization:



In [58]:

    
norm_param = [590,170,70,295]

ROI for cropping:



In [59]:

    
crop_param = [150,150,665,600]

ROI for pixels intensity oscillation as a function of the step:



In [60]:

    
oscillationParam = [540,540,20,20]

Number of periods in the phase scan:



In [61]:

    
numberPeriods = 1

Data processing

Loading:



In [62]:

    
im,ob = read_data(path_im,path_ob,path_dc)









    



WARNING: VerifyWarning: Error validating header for HDU #0 (note: Astropy uses zero-based indexing).
    'ascii' codec can't decode byte 0xb0 in position 1573: ordinal not in range(128)
There may be extra bytes after the last HDU or the file is corrupted. [astropy.io.fits.hdu.hdulist]

Cropping:



In [63]:

    
im,ob = cropped(im,ob,*crop_param)









    



(1024, 1024)
19931.882376 -9229.96852066

Normalizing:



In [64]:

    
im,ob=normalization(im,ob,*norm_param)









    



23513.5389308 -6537.28324959



In [65]:

    
oscillation(im,ob,*oscillationParam,repeatedPeriod=False)

Binning:



In [66]:

    
im, ob = binning(im,ob,bin_fac)

Creating:



In [67]:

    
ti, dpci, dfi, vis_map = createIm(im,ob,numberPeriods)

Saving the images

Save folder:



In [68]:

    
folder='yokeFolder/recIm'

Images label:



In [69]:

    
name='SquareYoke45deg'



In [70]:

    
saveIm(ti, dpci, dfi, vis_map,name=name,folder=folder,overWrite=True)









    



files saved in folder:  yokeFolder/recIm

Let's customize

DPCI units conversion

Some packages:



In [71]:

    
import scipy
import numpy as np
from astropy.io import fits 
import scipy.signal as signal

Create my dpci conversion function:



In [72]:

    
def pixelWiseDPC(dpci,p2um=4,d1cm=1.94,lambdaAmstr=4.1):
    
    dphi_over_dxPixel = (p2um*1e-3)/(lambdaAmstr*1e-7*d1cm*10)*dpci
    dphi_over_dxPixel /= 2
    
    return dphi_over_dxPixel

def pixelWisePC(dpciUnit,pixelConversion=0.11):
    
    dphi_over_dxPixel = np.array([scipy.integrate.cumtrapz(line*pixelConversion,initial=0) for line in dpciUnit])
    dphi_over_dxPixelREV = np.fliplr(np.array([scipy.integrate.cumtrapz(line*pixelConversion,initial=0) for line in np.fliplr(dpciUnit)]))

    return (np.abs(dphi_over_dxPixel)+np.abs(dphi_over_dxPixelREV))/2

Apply my new function:



In [73]:

    
pCim = pixelWisePC(dpci)
fits.writeto(folder+'/pci_'+name+'.fits',pCim,clobber=True)
radius = 15
pCim = signal.medfilt2d(pCim,radius)
fits.writeto(folder+'/pci_'+name+'.fits',pCim,clobber=True)