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-rw-r--r--distortion/models.py8
-rw-r--r--distortion/mutil.py62
-rw-r--r--updatewcs/corrections.py20
-rw-r--r--updatewcs/dgeo.py2
4 files changed, 46 insertions, 46 deletions
diff --git a/distortion/models.py b/distortion/models.py
index d4651fa..96d5d72 100644
--- a/distortion/models.py
+++ b/distortion/models.py
@@ -3,7 +3,7 @@ from __future__ import division # confidence high
import types
# Import PyDrizzle utility modules
import mutil
-import numpy as N
+import numpy as np
import mutil
from mutil import combin
@@ -72,8 +72,8 @@ class GeometryModel:
to the reference position of the chip.
"""
- _cxs = N.zeros(shape=cx.shape,dtype=cx.dtype)
- _cys = N.zeros(shape=cy.shape,dtype=cy.dtype)
+ _cxs = np.zeros(shape=cx.shape,dtype=cx.dtype)
+ _cys = np.zeros(shape=cy.shape,dtype=cy.dtype)
_k = self.norder + 1
# loop over each input coefficient
for m in xrange(_k):
@@ -219,7 +219,7 @@ class GeometryModel:
_cy[0,0] = 0.
if isinstance(_p,types.ListType) or isinstance(_p,types.TupleType):
- _p = N.array(_p,dtype=N.float64)
+ _p = np.array(_p,dtype=np.float64)
_convert = yes
dxy = _p - (self.refpix['XREF'],self.refpix['YREF'])
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))
diff --git a/updatewcs/corrections.py b/updatewcs/corrections.py
index 6709664..b20fc3f 100644
--- a/updatewcs/corrections.py
+++ b/updatewcs/corrections.py
@@ -1,7 +1,7 @@
from __future__ import division # confidence high
import datetime
-import numpy
+import numpy as np
from numpy import linalg
from pytools import fileutil
from stwcs.utils import diff_angles
@@ -56,11 +56,11 @@ class TDDCorr(object):
theta_v2v3 = 2.234529
mrotp = fileutil.buildRotMatrix(theta_v2v3)
mrotn = fileutil.buildRotMatrix(-theta_v2v3)
- tdd_mat = numpy.array([[1+(beta/2048.), alpha/2048.],[alpha/2048.,1-(beta/2048.)]],numpy.float64)
- abmat1 = numpy.dot(tdd_mat, mrotn)
- abmat2 = numpy.dot(mrotp,abmat1)
+ tdd_mat = np.array([[1+(beta/2048.), alpha/2048.],[alpha/2048.,1-(beta/2048.)]],np.float64)
+ abmat1 = np.dot(tdd_mat, mrotn)
+ abmat2 = np.dot(mrotp,abmat1)
xshape, yshape = hwcs.idcmodel.cx.shape, hwcs.idcmodel.cy.shape
- icxy = numpy.dot(abmat2,[hwcs.idcmodel.cx.ravel(), hwcs.idcmodel.cy.ravel()])
+ icxy = np.dot(abmat2,[hwcs.idcmodel.cx.ravel(), hwcs.idcmodel.cy.ravel()])
hwcs.idcmodel.cx = icxy[0]
hwcs.idcmodel.cy = icxy[1]
hwcs.idcmodel.cx.shape = xshape
@@ -127,15 +127,15 @@ class CompSIP(object):
cx = ext_wcs.idcmodel.cx
cy = ext_wcs.idcmodel.cy
- matr = numpy.array([[cx[1,1],cx[1,0]], [cy[1,1],cy[1,0]]], dtype=numpy.float)
+ matr = np.array([[cx[1,1],cx[1,0]], [cy[1,1],cy[1,0]]], dtype=np.float)
imatr = linalg.inv(matr)
- akeys1 = numpy.zeros((order+1,order+1), dtype=numpy.float)
- bkeys1 = numpy.zeros((order+1,order+1), dtype=numpy.float)
+ akeys1 = np.zeros((order+1,order+1), dtype=np.float)
+ bkeys1 = np.zeros((order+1,order+1), dtype=np.float)
for n in range(order+1):
for m in range(order+1):
if n >= m and n>=2:
- idcval = numpy.array([[cx[n,m]],[cy[n,m]]])
- sipval = numpy.dot(imatr, idcval)
+ idcval = np.array([[cx[n,m]],[cy[n,m]]])
+ sipval = np.dot(imatr, idcval)
akeys1[m,n-m] = sipval[0]
bkeys1[m,n-m] = sipval[1]
Akey="A_%d_%d" % (m,n-m)
diff --git a/updatewcs/dgeo.py b/updatewcs/dgeo.py
index bed3191..11562ef 100644
--- a/updatewcs/dgeo.py
+++ b/updatewcs/dgeo.py
@@ -130,7 +130,7 @@ class DGEOCorr(object):
values = {cperror: 0.0, cpdis: 'Lookup', dpext: wdvarr_ver, dpnaxes: 2,
dpaxis1: 1, dpaxis2: 2}
- comments = {cperror: 'Maximum error of dgeo correction for axis %s' % (wdvarr_ver//2 + 1),
+ comments = {cperror: 'Maximum error of dgeo correction for axis %s' % j,
cpdis: 'Prior distortion funcion type',
dpext: 'Version number of WCSDVARR extension containing lookup distortion table',
dpnaxes: 'Number of independent variables in distortion function',
generated by cgit (git 2.34.1) at 2025-05-04 02:18:45 -0400