diff options
Diffstat (limited to 'distortion/mutil.py')
| -rw-r--r-- | distortion/mutil.py | 62 |
1 files changed, 31 insertions, 31 deletions
diff --git a/distortion/mutil.py b/distortion/mutil.py index 5f17be9..44b46cd 100644 --- a/distortion/mutil.py +++ b/distortion/mutil.py @@ -1,7 +1,7 @@ from __future__ import division # confidence high from pytools import fileutil -import numpy as N +import numpy as np import string import calendar @@ -90,8 +90,8 @@ def readIDCtab (tabname, chip=1, date=None, direction='forward', else: order = norder - fx = N.zeros(shape=(order+1,order+1),dtype=N.float64) - fy = N.zeros(shape=(order+1,order+1),dtype=N.float64) + fx = np.zeros(shape=(order+1,order+1),dtype=np.float64) + fy = np.zeros(shape=(order+1,order+1),dtype=np.float64) #Determine row from which to get the coefficients. # How many rows do we have in the table... @@ -342,21 +342,21 @@ def readWCSCoeffs(header): _yorder = header['b_order'] order = max(max(_xorder,_yorder),3) - fx = N.zeros(shape=(order+1,order+1),dtype=N.float64) - fy = N.zeros(shape=(order+1,order+1),dtype=N.float64) + fx = np.zeros(shape=(order+1,order+1),dtype=np.float64) + fy = np.zeros(shape=(order+1,order+1),dtype=np.float64) # Read in CD matrix _cd11 = header['cd1_1'] _cd12 = header['cd1_2'] _cd21 = header['cd2_1'] _cd22 = header['cd2_2'] - _cdmat = N.array([[_cd11,_cd12],[_cd21,_cd22]]) - _theta = N.arctan2(-_cd12,_cd22) - _rotmat = N.array([[N.cos(_theta),N.sin(_theta)], - [-N.sin(_theta),N.cos(_theta)]]) - _rCD = N.dot(_rotmat,_cdmat) - _skew = N.arcsin(-_rCD[1][0] / _rCD[0][0]) - _scale = _rCD[0][0] * N.cos(_skew) * 3600. + _cdmat = np.array([[_cd11,_cd12],[_cd21,_cd22]]) + _theta = np.arctan2(-_cd12,_cd22) + _rotmat = np.array([[np.cos(_theta),np.sin(_theta)], + [-np.sin(_theta),np.cos(_theta)]]) + _rCD = np.dot(_rotmat,_cdmat) + _skew = np.arcsin(-_rCD[1][0] / _rCD[0][0]) + _scale = _rCD[0][0] * np.cos(_skew) * 3600. _scale2 = _rCD[1][1] * 3600. # Set up refpix @@ -440,17 +440,17 @@ def readTraugerTable(idcfile,wavelength): # Now, convert the coefficients into a Numeric array # with the right coefficients in the right place. # Populate output values now... - fx = N.zeros(shape=(order+1,order+1),dtype=N.float64) - fy = N.zeros(shape=(order+1,order+1),dtype=N.float64) + fx = np.zeros(shape=(order+1,order+1),dtype=np.float64) + fy = np.zeros(shape=(order+1,order+1),dtype=np.float64) # Assign the coefficients to their array positions fx[0,0] = 0. - fx[1] = N.array([a_coeffs[2],a_coeffs[1],0.,0.],dtype=N.float64) - fx[2] = N.array([a_coeffs[5],a_coeffs[4],a_coeffs[3],0.],dtype=N.float64) - fx[3] = N.array([a_coeffs[9],a_coeffs[8],a_coeffs[7],a_coeffs[6]],dtype=N.float64) + fx[1] = np.array([a_coeffs[2],a_coeffs[1],0.,0.],dtype=np.float64) + fx[2] = np.array([a_coeffs[5],a_coeffs[4],a_coeffs[3],0.],dtype=np.float64) + fx[3] = np.array([a_coeffs[9],a_coeffs[8],a_coeffs[7],a_coeffs[6]],dtype=np.float64) fy[0,0] = 0. - fy[1] = N.array([b_coeffs[2],b_coeffs[1],0.,0.],dtype=N.float64) - fy[2] = N.array([b_coeffs[5],b_coeffs[4],b_coeffs[3],0.],dtype=N.float64) - fy[3] = N.array([b_coeffs[9],b_coeffs[8],b_coeffs[7],b_coeffs[6]],dtype=N.float64) + fy[1] = np.array([b_coeffs[2],b_coeffs[1],0.,0.],dtype=np.float64) + fy[2] = np.array([b_coeffs[5],b_coeffs[4],b_coeffs[3],0.],dtype=np.float64) + fy[3] = np.array([b_coeffs[9],b_coeffs[8],b_coeffs[7],b_coeffs[6]],dtype=np.float64) # Used in Pattern.computeOffsets() refpix = {} @@ -517,17 +517,17 @@ def readCubicTable(idcfile): # Now, convert the coefficients into a Numeric array # with the right coefficients in the right place. # Populate output values now... - fx = N.zeros(shape=(order+1,order+1),dtype=N.float64) - fy = N.zeros(shape=(order+1,order+1),dtype=N.float64) + fx = np.zeros(shape=(order+1,order+1),dtype=np.float64) + fy = np.zeros(shape=(order+1,order+1),dtype=np.float64) # Assign the coefficients to their array positions fx[0,0] = 0. - fx[1] = N.array([a_coeffs[2],a_coeffs[1],0.,0.],dtype=N.float64) - fx[2] = N.array([a_coeffs[5],a_coeffs[4],a_coeffs[3],0.],dtype=N.float64) - fx[3] = N.array([a_coeffs[9],a_coeffs[8],a_coeffs[7],a_coeffs[6]],dtype=N.float64) + fx[1] = np.array([a_coeffs[2],a_coeffs[1],0.,0.],dtype=np.float64) + fx[2] = np.array([a_coeffs[5],a_coeffs[4],a_coeffs[3],0.],dtype=np.float64) + fx[3] = np.array([a_coeffs[9],a_coeffs[8],a_coeffs[7],a_coeffs[6]],dtype=np.float64) fy[0,0] = 0. - fy[1] = N.array([b_coeffs[2],b_coeffs[1],0.,0.],dtype=N.float64) - fy[2] = N.array([b_coeffs[5],b_coeffs[4],b_coeffs[3],0.],dtype=N.float64) - fy[3] = N.array([b_coeffs[9],b_coeffs[8],b_coeffs[7],b_coeffs[6]],dtype=N.float64) + fy[1] = np.array([b_coeffs[2],b_coeffs[1],0.,0.],dtype=np.float64) + fy[2] = np.array([b_coeffs[5],b_coeffs[4],b_coeffs[3],0.],dtype=np.float64) + fy[3] = np.array([b_coeffs[9],b_coeffs[8],b_coeffs[7],b_coeffs[6]],dtype=np.float64) # Used in Pattern.computeOffsets() refpix = {} @@ -561,8 +561,8 @@ def defaultModel(): """ order = 3 - fx = N.zeros(shape=(order+1,order+1),dtype=N.float64) - fy = N.zeros(shape=(order+1,order+1),dtype=N.float64) + fx = np.zeros(shape=(order+1,order+1),dtype=np.float64) + fy = np.zeros(shape=(order+1,order+1),dtype=np.float64) fx[1,1] = 1. fy[1,0] = 1. @@ -588,7 +588,7 @@ def defaultModel(): # the specified wavelength for use with Trauger coefficients def _MgF2(lam): _sig = pow((1.0e7/lam),2) - return N.sqrt(1.0 + 2.590355e10/(5.312993e10-_sig) + + return np.sqrt(1.0 + 2.590355e10/(5.312993e10-_sig) + 4.4543708e9/(11.17083e9-_sig) + 4.0838897e5/(1.766361e5-_sig)) |