remove some underscore in imports

maoppy/psfmodel.py

@@ -7,11 +7,11 @@ Created on Mon May 27 17:31:18 2019
 """
 
 import numpy as _np
-from scipy.optimize import least_squares as _least_squares
-from astropy.io import fits as _fits
-import time as _time
-import numpy.fft as _fft
-import sys as _sys
+from numpy.fft import fft2, ifft2, fftshift
+from scipy.optimize import least_squares
+from astropy.io import fits
+import time
+import sys
 from maoppy.utils import binning as _binning
 
 
@@ -20,7 +20,7 @@ __all__ = ["oversample", "lsq_flux_bck", "psffit", "reduced_coord",
            "Gaussian", "ParametricPSFfromPSD", "Turbulent", "Psfao"]
 
 # Value to compute finite differences
-_EPSILON = _np.sqrt(_sys.float_info.epsilon)
+_EPSILON = _np.sqrt(sys.float_info.epsilon)
 
 #%% FUNCTIONS
 def oversample(samp, fixed_k = None):
@@ -194,7 +194,7 @@ def psffit(psf,Model,x0,weights=None,dxdy=(0.,0.),flux_bck=(True,True),
         b_up = _np.concatenate((b_up,[_np.inf,_np.inf]))
         return (b_low,b_up)
     
-    result = _least_squares(cost, input2mini(x0,dxdy), bounds=get_bound(Model_inst))
+    result = least_squares(cost, input2mini(x0,dxdy), bounds=get_bound(Model_inst))
     
     print("") #finish line of "-"
     
@@ -363,7 +363,7 @@ class ParametricPSF(object):
     def otf(self,*args,**kwargs):
         """Return the Optical Transfer Function (OTF)"""
         psf = self.__call__(args,kwargs)
-        return _fft.fftshift(_fft.fft2(psf))
+        return fftshift(fft2(psf))
     
     def mtf(self,*args,**kwargs):
         """Return the Modulation Transfer Function (MTF)"""
@@ -372,7 +372,7 @@ class ParametricPSF(object):
     def tofits(self,param,filename,*args,keys=None,keys_comment=None,**kwargs):
         psf = self.__call__(param,*args,**kwargs)
         hdr = self._getfitshdr(param,keys=keys,keys_comment=keys_comment)
-        hdu = _fits.PrimaryHDU(psf, hdr)
+        hdu = fits.PrimaryHDU(psf, hdr)
         hdu.writeto(filename, overwrite=True)
         
     def _getfitshdr(self,param,keys=None,keys_comment=None):
@@ -380,10 +380,10 @@ class ParametricPSF(object):
         if len(keys)!=len(param): raise ValueError("When defined, `keys` must be same size as `param`")
         if keys_comment is not None:
             if len(keys_comment)!=len(param): raise ValueError("When defined, `keys_comment` must be same size as `param`")
-        hdr = _fits.Header()
+        hdr = fits.Header()
         
         hdr["HIERARCH ORIGIN"] = "MAOPPY automatic header"
-        hdr["HIERARCH CREATION"] = (_time.ctime(),"Date of file creation")
+        hdr["HIERARCH CREATION"] = (time.ctime(),"Date of file creation")
         for i in range(len(param)):
             if keys_comment is None:
                 hdr["HIERARCH PARAM "+keys[i]] = param[i]
@@ -601,17 +601,17 @@ class ParametricPSFfromPSD(ParametricPSF):
         else:
             PSD,integral = self.psd(x0,grad=False)
             
-        Bphi = _np.real(_fft.fft2(_fft.fftshift(PSD))) / L**2
-        #Bphi = _fft.fftshift(Bphi[0, 0] - Bphi) # normalized on the numerical FoV 
-        Bphi = _fft.fftshift(integral - Bphi) # normalized up to infinity
+        Bphi = _np.real(fft2(fftshift(PSD))) / L**2
+        #Bphi = fftshift(Bphi[0, 0] - Bphi) # normalized on the numerical FoV 
+        Bphi = fftshift(integral - Bphi) # normalized up to infinity
         otf = _np.exp(-Bphi)
         
         if grad:
             g2 = _np.zeros(g.shape,dtype=complex) # I cannot override 'g' here due to float to complex type
             for i in range(len(x0)):
-                Bphi = _np.real(_fft.fft2(_fft.fftshift(g[i,...]))) / L**2
-                #Bphi = _fft.fftshift(Bphi[0, 0] - Bphi) # normalized on the numerical FoV
-                Bphi = _fft.fftshift(integral_g[i] - Bphi) # normalized up to infinity
+                Bphi = _np.real(fft2(fftshift(g[i,...]))) / L**2
+                #Bphi = fftshift(Bphi[0, 0] - Bphi) # normalized on the numerical FoV
+                Bphi = fftshift(integral_g[i] - Bphi) # normalized up to infinity
                 g2[i,...] = -Bphi*otf
             return otf, g2
         return otf
@@ -622,7 +622,7 @@ class ParametricPSFfromPSD(ParametricPSF):
         NpupY = _np.ceil(ny/self._samp_over)
         tab = _np.zeros((nx, ny), dtype=complex)
         tab[0:int(NpupX), 0:int(NpupY)] = self.system.pupil((NpupX,NpupY),samp=self._samp_over)
-        self._otfDiffraction = _fft.fftshift(_np.abs(_fft.ifft2(_np.abs(_fft.fft2(tab)) ** 2)) / _np.sum(tab))
+        self._otfDiffraction = fftshift(_np.abs(ifft2(_np.abs(fft2(tab)) ** 2)) / _np.sum(tab))
     
     def _otfShift(self,dx,dy):
         Y, X = self._fxfy/self._pix2freq # so it is just an array of pixels
@@ -650,11 +650,11 @@ class ParametricPSFfromPSD(ParametricPSF):
         if grad:
             otf,g = self.otf(x0,dx=dx,dy=dy,_caller='self',grad=True)
             for i in range(len(x0)):
-                g[i,...] = _np.real(_fft.fftshift(_fft.ifft2(_fft.fftshift(g[i,...]))))
+                g[i,...] = _np.real(fftshift(ifft2(fftshift(g[i,...]))))
         else:
             otf = self.otf(x0,dx=dx,dy=dy,_caller='self',grad=False)
         
-        psf = _np.real(_fft.fftshift(_fft.ifft2(_fft.fftshift(otf))))
+        psf = _np.real(fftshift(ifft2(fftshift(otf))))
             
         k = int(self._k)
         if k==1:
@@ -911,5 +911,5 @@ class Psfao(ParametricPSFfromPSD):
         hdr["HIERARCH SAMP"] = (self.samp,"Sampling (eg. 2 for Shannon)")
         hdr["HIERARCH LEXT"] = (self.Lext,"Von-Karman outer scale")
         
-        hdu = _fits.PrimaryHDU(psf, hdr)
+        hdu = fits.PrimaryHDU(psf, hdr)
         hdu.writeto(filename, overwrite=overwrite)