from __future__ import absolute_import, division, print_function import numpy as np from . import mutil from .mutil import combin ################# # # # Geometry/Distortion Classes # # ################# class GeometryModel: """ Base class for Distortion model. There will be a separate class for each type of model/filetype used with drizzle, i.e., IDCModel and DrizzleModel. Each class will know how to apply the distortion to a single point and how to convert coefficients to an input table suitable for the drizzle task. Coefficients will be stored in CX,CY arrays. """ # # # # # # # NORDER = 3 def __init__(self): " This will open the given file and determine its type and norder." # Method to read in coefficients from given table and # populate the n arrays 'cx' and 'cy'. # This will be different for each type of input file, # IDCTAB vs. drizzle table. # Set these up here for all sub-classes to use... # But, calculate norder and cx,cy arrays in detector specific classes. self.cx = None self.cy = None self.refpix = None self.norder = self.NORDER # Keep track of computed zero-point for distortion coeffs self.x0 = None self.y0 = None # default values for these attributes self.direction = 'forward' self.pscale = 1.0 def shift(self, xs, ys): """ Shift reference position of coefficients to new center where (xs,ys) = old-reference-position - subarray/image center. This will support creating coeffs files for drizzle which will be applied relative to the center of the image, rather than relative to the reference position of the chip. """ _cxs = np.zeros(shape=self.cx.shape, dtype=self.cx.dtype) _cys = np.zeros(shape=self.cy.shape, dtype=self.cy.dtype) _k = self.norder + 1 # loop over each input coefficient for m in range(_k): for n in range(_k): if m >= n: # For this coefficient, shift by xs/ys. _ilist = list(range(m, _k)) # sum from m to k for i in _ilist: _jlist = list(range(n, i - (m - n) + 1)) # sum from n to i-(m-n) for j in _jlist: _cxs[m, n] += self.cx[i, j] * combin(j, n) * combin((i - j), (m - n)) * \ pow(xs, (j - n)) * pow(ys, ((i - j) - (m - n))) _cys[m, n] += self.cy[i, j] * combin(j, n) * combin((i - j), (m - n)) * \ pow(xs, (j - n)) * pow(ys, ((i - j) - (m - n))) self.cx = _cxs.copy() self.cy = _cys.copy() def convert(self, tmpname, xref=None, yref=None, delta=True): """ Open up an ASCII file, output coefficients in drizzle format after converting them as necessary. First, normalize these coefficients to what drizzle expects Normalize the coefficients by the MODEL/output plate scale. 16-May-2002: Revised to work with higher order polynomials by John Blakeslee. 27-June-2002: Added ability to shift coefficients to new center for support of subarrays. """ cx = self.cx / self.pscale cy = self.cy / self.pscale x0 = self.refpix['XDELTA'] + cx[0, 0] y0 = self.refpix['YDELTA'] + cy[0, 0] xr = self.refpix['CHIP_XREF'] yr = self.refpix['CHIP_YREF'] self.x0 = x0 self.y0 = y0 # Now, write out the coefficients into an ASCII # file in 'drizzle' format. lines = [] lines.append('# Polynomial distortion coefficients\n') lines.append('# Extracted from "%s" \n' % self.name) lines.append('refpix %f %f \n' % (xr, yr)) if self.norder == 3: lines.append('cubic\n') elif self.norder == 4: lines.append('quartic\n') elif self.norder == 5: lines.append('quintic\n') else: raise ValueError("Drizzle cannot handle poly distortions of order %d" % self.norder) str = '%16.8f %16.8g %16.8g %16.8g %16.8g \n' % (x0, cx[1, 1], cx[1, 0], cx[2, 2], cx[2, 1]) lines.append(str) str = '%16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cx[2, 0], cx[3, 3], cx[3, 2], cx[3, 1], cx[3, 0]) lines.append(str) if self.norder > 3: str = '%16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cx[4, 4], cx[4, 3], cx[4, 2], cx[4, 1], cx[4, 0]) lines.append(str) if self.norder > 4: str = '%16.8g %16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cx[5, 5], cx[5, 4], cx[5, 3], cx[5, 2], cx[5, 1], cx[5, 0]) lines.append(str) lines.append("\n") str = '%16.8f %16.8g %16.8g %16.8g %16.8g \n' % (y0, cy[1, 1], cy[1, 0], cy[2, 2], cy[2, 1]) lines.append(str) str = '%16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cy[2, 0], cy[3, 3], cy[3, 2], cy[3, 1], cy[3, 0]) lines.append(str) if self.norder > 3: str = '%16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cy[4, 4], cy[4, 3], cy[4, 2], cy[4, 1], cy[4, 0]) lines.append(str) if self.norder > 4: str = '%16.8g %16.8g %16.8g %16.8g %16.8g %16.8g \n' % (cy[5, 5], cy[5, 4], cy[5, 3], cy[5, 2], cy[5, 1], cy[5, 0]) lines.append(str) output = open(tmpname, 'w') output.writelines(lines) output.close() def apply(self, pixpos, scale=1.0, order=None): """ Apply coefficients to a pixel position or a list of positions. This should be the same for all coefficients tables. Return the geometrically-adjusted position in arcseconds from the reference position as a tuple (x,y). Compute delta from reference position """ """ scale actually is a ratio of pscale/self.model.pscale what is pscale? """ if self.cx is None: return pixpos[:, 0], pixpos[:, 1] if order is None: order = self.norder # Apply in the same way that 'drizzle' would... _cx = self.cx / (self.pscale * scale) _cy = self.cy / (self.pscale * scale) _convert = False _p = pixpos # Do NOT include any zero-point terms in CX,CY here # as they should not be scaled by plate-scale like rest # of coeffs... This makes the computations consistent # with 'drizzle'. WJH 17-Feb-2004 _cx[0, 0] = 0. _cy[0, 0] = 0. if isinstance(_p, list) or isinstance(_p, tuple): _p = np.array(_p, dtype=np.float64) _convert = True dxy = _p - (self.refpix['XREF'], self.refpix['YREF']) # Apply coefficients from distortion model here... c = _p * 0. for i in range(order + 1): for j in range(i + 1): c[:, 0] = c[:, 0] + _cx[i][j] * pow(dxy[:, 0], j) * pow(dxy[:, 1], (i - j)) c[:, 1] = c[:, 1] + _cy[i][j] * pow(dxy[:, 0], j) * pow(dxy[:, 1], (i - j)) xc = c[:, 0] yc = c[:, 1] # Convert results back to same form as original input if _convert: xc = xc.tolist() yc = yc.tolist() # If a single tuple was input, return just a single tuple if len(xc) == 1: xc = xc[0] yc = yc[0] return xc, yc def setPScaleCoeffs(self, pscale): self.cx[1, 1] = pscale self.cy[1, 0] = pscale self.refpix['PSCALE'] = pscale self.pscale = pscale class IDCModel(GeometryModel): """ This class will open the IDCTAB, select proper row based on chip/direction and populate cx,cy arrays. We also need to read in SCALE, XCOM,YCOM, XREF,YREF as well. """ def __init__(self, idcfile, date=None, chip=1, direction='forward', filter1='CLEAR1', filter2='CLEAR2', offtab=None, binned=1): GeometryModel.__init__(self) # # Norder must be derived from the coeffs file itself, # then the arrays can be setup. Thus, it needs to be # done in the sub-class, not in the base class. # Read in table. # Populate cx,cy,scale, and other variables here. # self.name = idcfile self.cx, self.cy, self.refpix, self.norder = mutil.readIDCtab(idcfile, chip=chip, direction=direction, filter1=filter1, filter2=filter2, date=date, offtab=offtab) if 'empty_model' in self.refpix and self.refpix['empty_model']: pass else: self.refpix['PSCALE'] = self.refpix['PSCALE'] * binned self.cx = self.cx * binned self.cy = self.cy * binned self.refpix['XREF'] = self.refpix['XREF'] / binned self.refpix['YREF'] = self.refpix['YREF'] / binned self.refpix['XSIZE'] = self.refpix['XSIZE'] / binned self.refpix['YSIZE'] = self.refpix['YSIZE'] / binned self.pscale = self.refpix['PSCALE'] class WCSModel(GeometryModel): """ This class sets up a distortion model based on coefficients found in the image header. """ def __init__(self, header, rootname): GeometryModel.__init__(self) if 'rootname' in header: self.name = header['rootname'] else: self.name = rootname # Initialize all necessary distortion arrays with # default model... # self.cx,self.cy,self.refpix,self.order = mutil.defaultModel() # Read in values from header, and update distortion arrays. self.cx, self.cy, self.refpix, self.norder = mutil.readWCSCoeffs(header) self.pscale = self.refpix['PSCALE'] class DrizzleModel(GeometryModel): """ This class will read in an ASCII Cubic drizzle coeffs file and populate the cx,cy arrays. """ def __init__(self, idcfile, scale=None): GeometryModel.__init__(self) # # We now need to read in the file, populate cx,cy, and # other variables as necessary. # self.name = idcfile self.cx, self.cy, self.refpix, self.norder = mutil.readCubicTable(idcfile) # scale is the ratio wcs.pscale/model.pscale. # model.pscale for WFPC2 is passed from REFDATA. # This is needed for WFPC2 binned data. if scale is not None: self.pscale = scale else: self.pscale = self.refpix['PSCALE'] class TraugerModel(GeometryModel): """ This class will read in the ASCII Trauger coeffs file, convert them to SIAF coefficients, then populate the cx,cy arrays. """ NORDER = 3 def __init__(self, idcfile, lam): GeometryModel.__init__(self) self.name = idcfile self.cx, self.cy, self.refpix, self.norder = mutil.readTraugerTable(idcfile, lam) self.pscale = self.refpix['PSCALE']