Saving and Reading Dictionaries

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B.5.1 Saving and Reading Dictionaries

To save a simple dictionary to a file:

CASA <13>: dictfile = open(’mydictfile.py’,’w’)
CASA <14>: print >>dictfile,"mydict = ",mydict
CASA <15>: dictfile.close()
CASA <16>: !cat mydictfile.py
IPython system call: cat mydictfile.py
mydict = {’source’: ’0137+331’, ’flux’: 5.4000000000000004}

CASA <17>: mydict = {}
CASA <18>: run mydictfile.py
CASA <19>: mydict
Out[19]: {’flux’: 5.4000000000000004, ’source’: ’0137+331’}

More complex dictionaries, like those produced by imstat that contain NumPy arrays, require a different approach to save. The pickle module lets you save general data structures from Python. For example:

CASA <20>: import pickle
CASA <21>: xstat
  Out[21]:
{’blc’: array([0, 0, 0, 0]),
’blcf’: ’15:24:08.404, +04.31.59.181, I, 1.41281e+09Hz’,
’flux’: array([ 4.0795296]),
’max’: array([ 0.05235516]),
’maxpos’: array([134, 134,   0,  38]),
’maxposf’: ’15:21:53.976, +05.05.29.998, I, 1.41374e+09Hz’,
’mean’: array([  1.60097857e-05]),
’medabsdevmed’: array([ 0.00127436]),
’median’: array([ -1.17422514e-05]),
’min’: array([-0.0104834]),
’minpos’: array([160,   1,   0,  30]),
’minposf’: ’15:21:27.899, +04.32.14.923, I, 1.41354e+09Hz’,
’npts’: array([ 3014656.]),
’quartile’: array([ 0.00254881]),
’rms’: array([ 0.00202226]),
’sigma’: array([ 0.0020222]),
’sum’: array([ 48.26399646]),
’sumsq’: array([ 12.32857318]),
’trc’: array([255, 255,   0,  45]),
’trcf’: ’15:19:52.390, +05.35.44.246, I, 1.41391e+09Hz’}

CASA <22>: mydict
  Out[22]: {’flux’: 5.4000000000000004, ’source’: ’0137+331’}

CASA <23>: pickfile = ’myxstat.pickle’
CASA <24>: f = open(pickfile,’w’)
CASA <25>: p = pickle.Pickler(f)
CASA <26>: p.dump(xstat)
CASA <27>: p.dump(mydict)
CASA <28>: f.close()

The dictionaries are now saved in pickle file myxstat.pickle in the current directory.

To retrieve:

CASA <29>: xstat2 = {}
CASA <30>: mydict2 = {}
CASA <31>: f = open(pickfile)
CASA <32>: u = pickle.Unpickler(f)
CASA <33>: xstat2 = u.load()
CASA <34>: mydict2 = u.load()
CASA <35>: f.close()
CASA <36>: xstat2
  Out[36]:
{’blc’: array([0, 0, 0, 0]),
’blcf’: ’15:24:08.404, +04.31.59.181, I, 1.41281e+09Hz’,
’flux’: array([ 4.0795296]),
’max’: array([ 0.05235516]),
’maxpos’: array([134, 134,   0,  38]),
’maxposf’: ’15:21:53.976, +05.05.29.998, I, 1.41374e+09Hz’,
’mean’: array([  1.60097857e-05]),
’medabsdevmed’: array([ 0.00127436]),
’median’: array([ -1.17422514e-05]),
’min’: array([-0.0104834]),
’minpos’: array([160,   1,   0,  30]),
’minposf’: ’15:21:27.899, +04.32.14.923, I, 1.41354e+09Hz’,
’npts’: array([ 3014656.]),
’quartile’: array([ 0.00254881]),
’rms’: array([ 0.00202226]),
’sigma’: array([ 0.0020222]),
’sum’: array([ 48.26399646]),
’sumsq’: array([ 12.32857318]),
’trc’: array([255, 255,   0,  45]),
’trcf’: ’15:19:52.390, +05.35.44.246, I, 1.41391e+09Hz’}

CASA <37>: mydict2
  Out[37]: {’flux’: 5.4000000000000004, ’source’: ’0137+331’}

Thus, you can make scripts that save information and use it later, like for regressions.

Note that these examples use Python file-handling and IO, as well as importing modules such as pickle. See your friendly Python reference for more on this kind of stuff. Its fairly obvious how it works.

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