Dynamically defined Instruments as attributes

maoppy/example/create_muse_psf.py

@@ -13,16 +13,14 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 from maoppy.psfmodel import Psfao
-from maoppy.instrument import load
+from maoppy.instrument import muse_nfm
 
 Npix = 128 # pixel size of PSF
 wvl = 600*1e-9 # wavelength [m]
 
-MUSE_NFM = load('muse_nfm')
-
 #%% Initialize PSF model
-samp = MUSE_NFM.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
-Pmodel = Psfao((Npix,Npix),system=MUSE_NFM,samp=samp)
+samp = muse_nfm.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
+Pmodel = Psfao((Npix,Npix),system=muse_nfm,samp=samp)
 
 #%% Choose parameters and compute PSF
 r0 = 0.15 # Fried parameter [m]

maoppy/example/fit_muse_simulated_psf.py

@@ -18,20 +18,18 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 from maoppy.psfmodel import Psfao, psffit, rmserror
-from maoppy.instrument import load
-
-MUSE_NFM = load('muse_nfm')
+from maoppy.instrument import muse_nfm
 
 npix = 128 # pixel size of PSF
 wvl = 600*1e-9 # wavelength [m]
 
 flux = 1e5
-ron = MUSE_NFM.ron
+ron = muse_nfm.ron
 bckgd = 1.0
 
 #%% Initialize PSF model
-samp = MUSE_NFM.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
-Pmodel = Psfao((npix,npix),system=MUSE_NFM,samp=samp)
+samp = muse_nfm.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
+Pmodel = Psfao((npix,npix),system=muse_nfm,samp=samp)
 
 #%% Generate a MUSE-NFM PSF
 r0 = 0.15 # Fried parameter [m]
@@ -54,7 +52,7 @@ guess = [0.145,2e-7,1.2,0.08,ratio,theta,1.5]
 w = np.ones_like(image)/ron**2.0
 fixed = [False,False,False,False,True,True,False]
 
-out = psffit(image,Psfao,guess,weights=w,system=MUSE_NFM,samp=samp,fixed=fixed)
+out = psffit(image,Psfao,guess,weights=w,system=muse_nfm,samp=samp,fixed=fixed)
 
 flux_fit, bck_fit = out.flux_bck
 fitao = flux_fit*out.psf + bck_fit

maoppy/example/fit_muse_simulated_psf_small_fov.py

@@ -8,7 +8,7 @@ Show the possibility of fitting a PSF with Psfao on a small field of view
 and to retrieve the PSF shape on an increased field of view.
 --------------
 This script is a more complex version of 'fit_muse_simulated_psf.py'
-The other one should be run first.
+The other one should be run first for better understanding.
 --------------
 
 Generate an observation of a star with MUSE-NFM, at a given wavelength
@@ -26,20 +26,18 @@ from matplotlib.patches import Rectangle
 import numpy as np
 
 from maoppy.psfmodel import Psfao, psffit, rmserror
-from maoppy.instrument import load
-
-MUSE_NFM = load('muse_nfm')
+from maoppy.instrument import muse_nfm
 
 npix = 128 # pixel size of PSF
 wvl = 600*1e-9 # wavelength [m]
 
 flux = 1e6
-ron = MUSE_NFM.ron
+ron = muse_nfm.ron
 bckgd = 1.0
 
 #%% Initialize PSF model
-samp = MUSE_NFM.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
-Pmodel = Psfao((npix,npix),system=MUSE_NFM,samp=samp)
+samp = muse_nfm.samp(wvl) # sampling (2.0 for Shannon-Nyquist)
+Pmodel = Psfao((npix,npix),system=muse_nfm,samp=samp)
 
 #%% Generate a MUSE-NFM PSF
 r0 = 0.15 # Fried parameter [m]
@@ -68,7 +66,7 @@ w = np.ones_like(im_crop)/ron**2.0
 fixed = [False,False,False,False,True,True,False]
 
 out = psffit(im_crop,Psfao,guess,weights=w,fixed=fixed,npixfit=npix, # fit keywords
-                                 system=MUSE_NFM,samp=samp) # Psfao keywords
+                                 system=muse_nfm,samp=samp) # Psfao keywords
 
 flux_fit, bck_fit = out.flux_bck
 fitao = flux_fit*out.psf + bck_fit

maoppy/example/fit_zimpol_psf.py

@@ -15,13 +15,11 @@ import numpy as np
 
 from maoppy.utils import imcenter, circavgplt
 from maoppy.psfmodel import psffit, Psfao
-from maoppy.instrument import load
-
-ZIMPOL = load('zimpol')
+from maoppy.instrument import zimpol
 
 # %% PARAMETERS TO MODIFY
 psf_path = "path/to/your/zimpol_psf.fits" # set the path to your PSF *.fits file
-filt = ZIMPOL.filters["N_R"]  # ZIMPOL filter
+filt = zimpol.filters["N_R"]  # ZIMPOL filter
 Npix = 512 # size of PSF for fitting [pixels]. The larger the better
 
 r0 = 0.18 # Fried parameter [m]
@@ -37,11 +35,11 @@ fitsPSF = fits.open(psf_path)
 hdr = fitsPSF[0].header
 psf = fitsPSF[0].data
 
-psf = imcenter(psf, (Npix, Npix), maxi=True) * ZIMPOL.gain
+psf = imcenter(psf, (Npix, Npix), maxi=True) * zimpol.gain
 
 # %% FIT PSFAO model
 wvl = filt[0]
-samp = ZIMPOL.samp(wvl)
+samp = zimpol.samp(wvl)
 
 x0 = [r0,moff_C,moff_A,moff_alpha,moff_ratio,moff_theta,moff_beta]
 fixed = [False,False,False,False,True,True,False]
@@ -49,7 +47,7 @@ fixed = [False,False,False,False,True,True,False]
 weights = np.ones_like(psf)
 
 print("PSFAO fitting (please wait)")
-out = psffit(psf,Psfao,x0,weights=weights,system=ZIMPOL,samp=samp,fixed=fixed)
+out = psffit(psf,Psfao,x0,weights=weights,system=zimpol,samp=samp,fixed=fixed)
 
 out.x[5] = out.x[5]%np.pi # make angle between 0 and PI
 

maoppy/instrument.py

@@ -6,31 +6,34 @@ Created on Mon May 27 17:30:51 2019
 @author: rfetick
 """
 
-from maoppy.utils import circarr, RAD2ARCSEC
-import yaml
-import os
-from astropy.io import fits
-import numpy as np
-from scipy.interpolate import interp2d
+from maoppy.utils import circarr as _circarr
+from maoppy.utils import RAD2ARCSEC as _RAD2ARCSEC
+
+import sys as _sys
+import yaml as _yaml
+import os as _os
+from astropy.io import fits as _fits
+import numpy as _np
+from scipy.interpolate import interp2d as _interp2d
 
 
 def _get_data_folder():
-    folder = os.path.abspath(__file__)
-    folder = os.sep.join(folder.split(os.sep)[0:-1])+os.sep+'data'+os.sep
+    folder = _os.path.abspath(__file__)
+    folder = _os.sep.join(folder.split(_os.sep)[0:-1])+_os.sep+'data'+_os.sep
     return folder
 
-def load(name):
-    """Load an instrument saved in the `data` folder of MAOPPY"""
-    folder = _get_data_folder()
-    with open(folder+name.lower()+".yml",'r') as f:
-        d = yaml.full_load(f)
-    instru = Instrument(D=d['d'],occ=d['occ'],res=d['res'],gain=d['gain'],ron=d['ron'],Nact=d['nact'])
-    instru.name = d['name']
-    instru.fullname = d['fullname']
-    instru.filters = d['filters']
-    instru.phasemask_path = d['phasemask_path']
-    instru.phasemask_shift = d['phasemask_shift']
-    return instru
+#def load(name):
+#    """Load an instrument saved in the `data` folder of MAOPPY"""
+#    folder = _get_data_folder()
+#    with open(folder+name.lower()+".yml",'r') as f:
+#        d = _yaml.full_load(f)
+#    instru = Instrument(D=d['d'],occ=d['occ'],res=d['res'],gain=d['gain'],ron=d['ron'],Nact=d['nact'])
+#    instru.name = d['name']
+#    instru.fullname = d['fullname']
+#    instru.filters = d['filters']
+#    instru.phasemask_path = d['phasemask_path']
+#    instru.phasemask_shift = d['phasemask_shift']
+#    return instru
 
 #%% INSTRUMENT CLASS
 class Instrument(object):
@@ -106,25 +109,25 @@ class Instrument(object):
     
     @property
     def resolution_mas(self):
-        return self.resolution_rad * RAD2ARCSEC * 1e3
+        return self.resolution_rad * _RAD2ARCSEC * 1e3
     
     def pupil(self,Npix,wvl=None,samp=None):
         """Returns the 2D array of the pupil transmission function (complex data)"""
         Dpix = min(Npix)/2
-        pup = circarr(Npix)
+        pup = _circarr(Npix)
         if self.phasemask_enable:
             if self._phasemask is None:
                 if self.phasemask_path is None: raise ValueError('phasemask_path must be defined')
-                p = fits.open(self.phasemask_path)[0].data * 1e-9 # fits data in nm, converted here to meter
-                x = np.arange(p.shape[0])/p.shape[0]
-                y = np.arange(p.shape[1])/p.shape[1]
-                self._phasemask = interp2d(x,y,p)
+                p = _fits.open(self.phasemask_path)[0].data * 1e-9 # fits data in nm, converted here to meter
+                x = _np.arange(p.shape[0])/p.shape[0]
+                y = _np.arange(p.shape[1])/p.shape[1]
+                self._phasemask = _interp2d(x,y,p)
             cx,cy = self.phasemask_shift
-            x = np.arange(Npix[0])/Npix[0] - cx/Npix[0]
-            y = np.arange(Npix[1])/Npix[1] - cy/Npix[1]
+            x = _np.arange(Npix[0])/Npix[0] - cx/Npix[0]
+            y = _np.arange(Npix[1])/Npix[1] - cy/Npix[1]
             wf = self._phasemask(x,y)
             if wvl is None: wvl = self.wvl(samp) # samp must be defined if wvl is None
-            wf = np.exp(2j*np.pi/wvl*wf)
+            wf = _np.exp(2j*_np.pi/wvl*wf)
         else:
             wf = 1.0 + 0j # complex type for output array, even if real data
         return (pup < Dpix) * (pup >= Dpix*self.occ) * wf
@@ -151,18 +154,23 @@ class Instrument(object):
         data['filters'] = self.filters
         data['phasemask_path'] = self.phasemask_path
         data['phasemask_shift'] = self.phasemask_shift
-        with open(filename,'w') as f: yaml.dump(data,f)
-        
+        with open(filename,'w') as f: _yaml.dump(data,f)
 
-#%% OLD WAY to LOAD INSTRUMENTS (now use the `load` function)
+#%% LOAD INSTRUMENT INSTANCES (make them attributes of this module)
+_this_module = _sys.modules[__name__]
+_d = _get_data_folder()
+_l = [_f for _f in _os.listdir(_d) if _f.endswith('.yml')]
+for _f in _l:
+    with open(_d+_f,'r') as _fi:
+        _i = _yaml.full_load(_fi)
+    _instru = Instrument(D=_i['d'],occ=_i['occ'],res=_i['res'],gain=_i['gain'],ron=_i['ron'],Nact=_i['nact'])
+    _instru.name = _i['name']
+    _instru.fullname = _i['fullname']
+    _instru.filters = _i['filters']
+    _instru.phasemask_path = _i['phasemask_path']
+    _instru.phasemask_shift = _i['phasemask_shift']
+    _n = _i['name'].lower().replace(" ","_") # format name
+    setattr(_this_module,_n,_instru)
+    
+del _this_module, _d, _l, _f, _instru, _fi, _i, _n
 
-#ZIMPOL = Instrument(D=8.,occ=0.14,res=30*1e-6/1768.,gain=10.5,ron=20.,Nact=40)
-#ZIMPOL.filters["V"] = (554*1e-9, 80.6*1e-9)
-#ZIMPOL.filters["N_R"] = (645.9*1e-9, 56.7*1e-9)
-#ZIMPOL.name = "ZIMPOL"
-#ZIMPOL.fullname = "VLT SPHERE/ZIMPOL"
-#
-#
-#MUSE_NFM = Instrument(D=8.,occ=0.14,res=237.15*1e-6/1980.,gain=5.,ron=15.,Nact=39)
-#MUSE_NFM.name = "MUSE_NFM"
-#MUSE_NFM.fullname = "VLT MUSE (NFM)"

maoppy/test/test_psfmodel.py

@@ -9,7 +9,7 @@ Created on Fri May  8 20:21:20 2020
 import unittest
 import numpy as np
 from maoppy.psfmodel import lsq_flux_bck, moffat, gauss, Psfao
-from maoppy.instrument import load
+from maoppy.instrument import zimpol, muse_nfm
 
 class TestLsqFluxBck(unittest.TestCase):
     def test_fluxbck(self):
@@ -55,7 +55,7 @@ class TestPsfao(unittest.TestCase):
     def test_oversampling(self):
         npix = 100
         samp = 0.3
-        P = Psfao((npix,npix),system=load('muse_nfm'),samp=samp)
+        P = Psfao((npix,npix),system=muse_nfm,samp=samp)
         self.assertEqual(samp,P.samp)
         self.assertGreaterEqual(P._samp_over,2.0)
         self.assertEqual(P._k%1,0)
@@ -63,14 +63,14 @@ class TestPsfao(unittest.TestCase):
     def test_bounds_length(self):
         npix = 100
         samp = 0.3
-        P = Psfao((npix,npix),system=load('muse_nfm'),samp=samp)
+        P = Psfao((npix,npix),system=muse_nfm,samp=samp)
         self.assertEqual(len(P.bounds[0]),7)
         self.assertEqual(len(P.bounds[1]),7)
         
     def test_psd_integral(self):
         npix = 1024
         samp = 2.0
-        P = Psfao((npix,npix),system=load('zimpol'),samp=samp)
+        P = Psfao((npix,npix),system=zimpol,samp=samp)
         fao = P.system.Nact/(2.0*P.system.D)
         df = 1.0/(P.system.D*P._samp_over)
         
@@ -104,7 +104,7 @@ class TestPsfao(unittest.TestCase):
     def test_otf_max(self):
         npix = 1024
         samp = 2.0
-        P = Psfao((npix,npix),system=load('zimpol'),samp=samp)
+        P = Psfao((npix,npix),system=zimpol,samp=samp)
         r0 = 0.25
         C = 1e-4
         A = 1.0