diff options
Diffstat (limited to 'updatewcs/corrections.py')
| -rw-r--r-- | updatewcs/corrections.py | 48 |
1 files changed, 39 insertions, 9 deletions
diff --git a/updatewcs/corrections.py b/updatewcs/corrections.py index f296c10..eac4b6e 100644 --- a/updatewcs/corrections.py +++ b/updatewcs/corrections.py @@ -70,18 +70,48 @@ class TDDCorr(object): def compute_alpha_beta(cls, ext_wcs): """ - Compute the time dependent distortion skew terms - default date of 2004.5 = 2004-7-1 - """ - dday = 2004.5 - year,month,day = ext_wcs.date_obs.split('-') - rdate = datetime.datetime(int(year),int(month),int(day)) - rday = float(rdate.strftime("%j"))/365.25 + rdate.year + Compute the ACS time dependent distortion skew terms + as described in ACS ISR 07-08 by J. Anderson. + + Jay's code only computes the alpha/beta values based on a decimal year + with only 3 digits, so this line reproduces that when needed for comparison + with his results. + rday = float(('%0.3f')%rday) + + The zero-point terms account for the skew accumulated between + 2002.0 and 2004.5, when the latest IDCTAB was delivered. alpha = 0.095 + 0.090*(rday-dday)/2.5 beta = -0.029 - 0.030*(rday-dday)/2.5 + """ + skew_coeffs = ext_wcs.idcmodel.refpix['skew_coeffs'] + if skew_coeffs is None: + err_str = "------------------------------------------------------------------------ \n" + err_str += "WARNING: the IDCTAB geometric distortion file specified in the image \n" + err_str += " header did not have the time-dependent distortion coefficients. \n" + err_str += " The pre-SM4 time-dependent skew solution will be used by default.\n" + err_str += " Please update IDCTAB with new reference file from HST archive. \n" + err_str += "------------------------------------------------------------------------ \n" + print err_str + # Using default pre-SM4 coefficients + skew_coeffs = {'TDD_A':[0.095,0.090/2.5], + 'TDD_B':[-0.029,-0.030/2.5], + 'TDD_DATE':2004.5} - return alpha, beta - + if not isinstance(ext_wcs.date_obs,float): + year,month,day = ext_wcs.date_obs.split('-') + rdate = datetime.datetime(int(year),int(month),int(day)) + rday = float(rdate.strftime("%j"))/365.25 + rdate.year + else: + rday = ext_wcs.date_obs + + alpha = 0 + beta = 0 + # Compute skew terms, allowing for non-linear coefficients as well + for c in range(skew_coeffs['TDDORDER']+1): + alpha += skew_coeffs['TDD_A'][c]* np.power((rday-skew_coeffs['TDD_DATE']),c) + beta += skew_coeffs['TDD_B'][c]*np.power((rday-skew_coeffs['TDD_DATE']),c) + + return alpha,beta compute_alpha_beta = classmethod(compute_alpha_beta) |