def xymatch(outfile, filenames, tol=2):
import math
import MOPfiles
import sys
output = {}
files = []
for filename in filenames:
this_file = MOPfiles.read(filename)
## match files based on the 'X' and 'Y' column.
## if those don't exist then skip this file
if not this_file['data'].has_key('X') or not this_file['data'].has_key(
'Y'):
continue
if not output.has_key('data'):
output = this_file
continue
delete_list = []
for keyword in this_file['header']:
if not keyword in output['header']:
output['header'][keyword] = this_file['header'][keyword]
for col in this_file['data'].keys():
if not output['data'].has_key(col):
output['order'].append(col)
output['data'][col] = []
output['order'].append(col)
output['format'].append(this_file['format'][col])
### pad previously values with empties..
for i in range(len(output['data']['X'])):
output['data'][col].append(None)
for i in xrange(len(output['data']['X'])):
x1 = float(output['data']['X'][i])
y1 = float(output['data']['Y'][i])
matched = False
for j in xrange(len(this_file['data']['X'])):
x2 = float(this_file['data']['X'][j])
y2 = float(this_file['data']['Y'][j])
if (((x1 - x2)**2 + (y1 - y2)**2) < tol**2):
for col in this_file['data'].keys():
if output['data'][col][i] is None:
output['data'][col][i] = this_file['data'][col][j]
matched = True
break
if not matched:
delete_list.append(i)
delete_list.sort()
delete_list.reverse()
for i in delete_list:
for col in output['data'].keys():
del output['data'][col][i]
MOPfiles.write(outname, output)
def xymatch(outfile, filenames, tol=2):
import math
import MOPfiles
import sys
output={}
files=[]
for filename in filenames:
this_file=MOPfiles.read(filename)
## match files based on the 'X' and 'Y' column.
## if those don't exist then skip this file
if not this_file['data'].has_key('X') or not this_file['data'].has_key('Y'):
continue
if not output.has_key('data'):
output=this_file
continue
delete_list=[]
for keyword in this_file['header']:
if not keyword in output['header']:
output['header'][keyword]=this_file['header'][keyword]
for col in this_file['data'].keys():
if not output['data'].has_key(col):
output['order'].append(col)
output['data'][col]=[]
output['order'].append(col)
output['format'].append(this_file['format'][col])
### pad previously values with empties..
for i in range(len(output['data']['X'])):
output['data'][col].append(None)
for i in xrange(len(output['data']['X'])):
x1=float(output['data']['X'][i])
y1=float(output['data']['Y'][i])
matched=False
for j in xrange(len(this_file['data']['X'])):
x2=float(this_file['data']['X'][j])
y2=float(this_file['data']['Y'][j])
if ( ((x1-x2)**2+(y1-y2)**2) < tol**2):
for col in this_file['data'].keys():
if output['data'][col][i] is None:
output['data'][col][i]=this_file['data'][col][j]
matched=True
break
if not matched:
delete_list.append(i)
delete_list.sort()
delete_list.reverse()
for i in delete_list:
for col in output['data'].keys():
del output['data'][col][i]
MOPfiles.write(outname,output)
def objIngest(obj_file):
import sys, os, math, re
import pyfits
import MOPfiles
obj = MOPfiles.read(obj_file)
"""
The SQL description of the source table
+-------------+---------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------------+---------+------+-----+---------+----------------+
| sourceID | int(11) | | PRI | NULL | auto_increment |
| x_pix | float | YES | MUL | NULL | |
| y_pix | float | YES | | NULL | |
| iso_flux | float | YES | | NULL | |
| iso_err | float | YES | | NULL | |
| aper_flux | float | YES | | NULL | |
| aper_err | float | YES | | NULL | |
| iso_area | float | YES | | NULL | |
| kron_radius | float | YES | MUL | NULL | |
| elongation | float | YES | | NULL | |
| cxx | float | YES | | NULL | |
| cyy | float | YES | | NULL | |
| cxy | float | YES | | NULL | |
| max_flux | float | YES | | NULL | |
| max_int | float | YES | | NULL | |
| mag_dao | float | YES | MUL | NULL | |
| merr_dao | float | YES | | NULL | |
| sky_cts | float | YES | | NULL | |
| chi2 | float | YES | | NULL | |
| npix | float | YES | | NULL | |
| sharp | float | YES | | NULL | |
| ra_deg | float | YES | MUL | NULL | |
| dec_deg | float | YES | | NULL | |
+-------------+---------+------+-----+---------+----------------+
"""
"""
Columns in the SOURCE table...
## X Y FLUX_ISO FLUXERR_ISO FLUX_APER FLUXERR_APER ISOAREA_IMAGE KRON_RADIUS ELONGATION CXX_IMAGE CYY_IMAGE CXY_IMAGE FLUX_MAX ID MAX_INT FLUX MERR SKY ELON X^2 N_PIX MAG SHARP SIZE
"""
### The mapping
obj['hdu2sql'] = {
'MAX_INT': 'peak',
'FLUX': 'flux',
'MAG': 'mag',
'MERR': 'merr',
'SKY': 'sky',
'ELON': 'elongation',
'X^2': 'chi2',
'N_PIX': 'npix',
'SHARP': 'sharpness',
'Y': 'yPix',
'X': 'xPix',
'SIZE': 'size',
'RA': 'raDeg',
'DEC': 'decDeg',
}
MOPfiles.store(obj)
return
def objIngest(obj_file):
import sys,os,math,re
import pyfits
import MOPfiles
obj=MOPfiles.read(obj_file)
"""
The SQL description of the source table
+-------------+---------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------------+---------+------+-----+---------+----------------+
| sourceID | int(11) | | PRI | NULL | auto_increment |
| x_pix | float | YES | MUL | NULL | |
| y_pix | float | YES | | NULL | |
| iso_flux | float | YES | | NULL | |
| iso_err | float | YES | | NULL | |
| aper_flux | float | YES | | NULL | |
| aper_err | float | YES | | NULL | |
| iso_area | float | YES | | NULL | |
| kron_radius | float | YES | MUL | NULL | |
| elongation | float | YES | | NULL | |
| cxx | float | YES | | NULL | |
| cyy | float | YES | | NULL | |
| cxy | float | YES | | NULL | |
| max_flux | float | YES | | NULL | |
| max_int | float | YES | | NULL | |
| mag_dao | float | YES | MUL | NULL | |
| merr_dao | float | YES | | NULL | |
| sky_cts | float | YES | | NULL | |
| chi2 | float | YES | | NULL | |
| npix | float | YES | | NULL | |
| sharp | float | YES | | NULL | |
| ra_deg | float | YES | MUL | NULL | |
| dec_deg | float | YES | | NULL | |
+-------------+---------+------+-----+---------+----------------+
"""
"""
Columns in the SOURCE table...
## X Y FLUX_ISO FLUXERR_ISO FLUX_APER FLUXERR_APER ISOAREA_IMAGE KRON_RADIUS ELONGATION CXX_IMAGE CYY_IMAGE CXY_IMAGE FLUX_MAX ID MAX_INT FLUX MERR SKY ELON X^2 N_PIX MAG SHARP SIZE
"""
### The mapping
obj['hdu2sql']={'MAX_INT': 'peak',
'FLUX': 'flux',
'MAG': 'mag',
'MERR': 'merr',
'SKY': 'sky',
'ELON': 'elongation',
'X^2': 'chi2',
'N_PIX': 'npix',
'SHARP': 'sharpness',
'Y': 'yPix',
'X': 'xPix',
'SIZE': 'size',
'RA': 'raDeg',
'DEC': 'decDeg',
}
MOPfiles.store(obj)
return