getxyFromFile
Return to directory of Todd's CASA extensions
Gets two columns of data from an ASCII file, as numpy arrays. See also
interpolateTable.
Usage:
au.getxyFromFile(filename, xcol, ycol, delimiter=None, maxLines=None,
startAfter=None, stopAt=None, yhms=False, ydms=False)
Inputs:
- xcol: the column number from which to read x-axis data
- ycol: the column number from which to read y-axis data
- delimiter: the string that delimits columns within a row (default = None which means whitespace)
- startAfter: if defined, then skip all rows up to and including the first one contaning this string
- stopAt: if defined, then skip all remaining rows when this string is seen
- yhms: if True, then read 3 columns starting at ycol as HH MM SS.SSS and convert to deg
- ydms: if True, then read 3 columns starting at ycol as DD MM SS.SSS and convert to deg
If a colon is seen in the xcol & ycol data, and xcol = ycol, then assume both columns are
a sky position in sexagesimal format and convert them to radians. If a colon is seen in only one of them, then assume it is HH:MM[:SS] and
convert it to floating point hours.
Example:
CASA <6>: au.getxyFromFile('random.both',xcol=0,ycol=21)
Skipping row 1 because there are only 1 columns.
Out[6]:
(array([ 79.34, 92.57, 74.23, 73.54, 83.93, 79.78, 77.58, 80.42,
76.14, 84.57, 79.66, 78.12, 93.07, 78.79, 91.85, 76.03,
78.96, 93.6 , 74.51, 72.2 , 74.51, 86.11, 73.1 , 85.24,
92.79, 90.5 , 86.89, 79.84, 72.82, 78.94, 84.36, 84.91,
94.71, 83.97, 73.17, 90.37, 74.49, 76.64, 86.75, 90.5 ,
88.53, 83.21, 87.58, 90.02, 85.57, 80.42, 86.05, 72.67,
90.42, 83.53, 83.91, 93.55, 94.26, 81.86, 72.4 , 80.93,
91.54, 75.01, 85.03, 83.87, 79.56, 94.66, 74.87, 91.26,
89.63, 74.07, 76.6 , 89.67, 88.87, 94.15, 78.1 , 83.7 ,
74.66, 86.14, 84.68, 79.02, 85.66, 94.99, 76.94, 74.02,
83.48, 91.27, 92.29, 83.05, 73.03, 90.78, 85.04, 76.34,
93.39, 75.75, 94.14, 89.52, 79.4 , 85.66, 74.53, 88.73,
76.81, 86.73, 82.16, 74.45, 72.47, 85.09, 86.89, 80.42,
72.96, 78.7 , 79.37, 89.99, 79.98, 82.88, 77.5 , 90.08,
80.71, 86.64, 84.07, 85.8 , 74.73, 80.73, 80.62, 93.18,
77.89, 72.38, 93.13, 89.13, 88.81, 85.48, 82.32, 84.95,
86.97, 77.53, 72.54, 93.63, 85.47, 72.14, 82.41, 82.64,
77.37, 93.16, 86.89, 73.35, 82.7 , 84.48, 80.17, 88.19,
89.07, 91.41, 78.01, 83.29, 92.89, 82.68, 82.88, 73.86,
80.25, 80.14, 80.56, 84.1 , 85.42, 89.95, 91.51, 82.83,
73.94, 88.56, 92.71, 88.66, 87.34, 86.15, 86.31, 76.85,
74.57, 83.83, 84.72, 78.72, 76.93, 85.39, 81.45, 82.82,
76.69, 94.7 , 76.56, 82.54, 84.35, 75.72, 87.65, 86.49,
73.5 , 82.14, 77.58, 91.46, 85.3 , 73.68, 74.77, 87. ,
88.57, 85.96, 72.1 , 91.61, 78.59, 86.99, 72.49, 82.59]),
array([ 26., 17., 18., 18., 19., 20., 47., 14., 23., 17., 15.,
56., 17., 26., 16., 28., 17., 16., 19., 19., 20., 16.,
19., 17., 15., 12., 10., 20., 19., 18., 15., 17., 16.,
17., 18., 16., 18., 17., 14., 13., 24., 18., 12., 18.,
15., 17., 15., 18., 12., 25., 26., 16., 17., 16., 19.,
15., 20., 20., 18., 22., 20., 18., 20., 16., 13., 20.,
17., 14., 15., 16., 50., 17., 19., 15., 14., 19., 18.,
16., 19., 28., 21., 16., 15., 18., 20., 20., 17., 18.,
17., 18., 19., 14., 20., 15., 20., 13., 18., 11., 16.,
20., 25., 16., 14., 18., 18., 18., 22., 19., 16., 21.,
14., 17., 15., 20., 16., 18., 24., 16., 16., 15., 49.,
18., 17., 19., 14., 17., 25., 19., 62., 18., 17., 15.,
16., 19., 18., 15., 15., 17., 12., 20., 18., 14., 19.,
13., 19., 15., 51., 18., 16., 20., 17., 19., 15., 16.,
15., 17., 16., 19., 17., 17., 19., 16., 14., 14., 16.,
14., 16., 17., 18., 15., 14., 20., 16., 17., 15., 18.,
17., 17., 18., 13., 17., 17., 12., 13., 20., 14., 16.,
19., 16., 20., 18., 59., 14., 14., 19., 16., 18., 52.,
19., 20.]))
--
ToddHunter - 2014-01-17