Hi,
sorry to bother you with probably plenty of stupid question but I would like
to clarify my mind with dtype.
I have a problem to view a recarray, I'm not sure but I suspect a bug or at
least a problem
I have an array with some data, the array is very big but I have no problem
with numpy.
In [44]: data_end
Out[44]:
array([[ 2.66000000e+02, 5.16300000e+04, 1.00000000e+00, ...,
-1.04130435e+00, 1.47304565e+02, 4.27402449e+00],
[ 2.66000000e+02, 5.16300000e+04, 2.00000000e+00, ...,
-6.52190626e-01, 1.64214981e+02, 1.58334379e+01],
[ 2.66000000e+02, 5.16300000e+04, 4.00000000e+00, ...,
-7.65136838e-01, 1.33340195e+02, 9.84033298e+00],
...,
[ 9.78000000e+02, 5.24310000e+04, 6.32000000e+02, ...,
3.06083832e+01, 6.71210251e+01, 1.18813887e+01],
[ 9.78000000e+02, 5.24310000e+04, 6.36000000e+02, ...,
3.05993423e+01, 1.10403000e+02, 5.81539488e+00],
[ 9.78000000e+02, 5.24310000e+04, 6.40000000e+02, ...,
3.05382938e+01, 1.26916304e+01, 3.25683937e+01]])
In [45]: data_end.shape
Out[45]: (567486, 7)
In [46]: data_end.dtype
Out[46]: dtype('<f8')
I want to have this array with certain dtype so I transform it in recarray (I
have unable ot have different type for each columns in the array but I'm just
beginning to play with dtype.
So I did:
In [47]: fields =
['PLATEID', 'MJD', 'FIBERID', 'RA', 'DEC','V_DISP','V_DISP_ERR']
In [48]:
In [48]: type_descr = numpy.dtype({'names':fields,'formats':
['>i2','>i4','>i2','>f4','>f4','>f4','>f4']})
In [49]: b = numpy.rec.fromarrays(data_end.transpose(),type_descr)
In [50]: b[:1]
Out[50]:
recarray([ (266, 51630, 1, 146.71420288085938, -1.041304349899292,
147.3045654296875, 4.274024486541748)],
dtype=[('PLATEID', '>i2'), ('MJD', '>i4'), ('FIBERID', '>i2'),
('RA', '>f4'), ('DEC', '>f4'), ('V_DISP', '>f4'), ('V_DISP_ERR', '>f4')])
In [51]: b[1]
Out[51]: (266, 51630, 2, 146.74412536621094, -0.65219062566757202,
164.21498107910156, 15.833437919616699)
but I obtain an error when I want to print the recarray b (it's working for
smallest array):
In [54]: b[:10]
Out[54]:
recarray([ (266, 51630, 1, 146.71420288085938, -1.041304349899292,
147.3045654296875, 4.274024486541748),
(266, 51630, 2, 146.74412536621094, -0.65219062566757202,
164.21498107910156, 15.833437919616699),
(266, 51630, 4, 146.62857055664062, -0.76513683795928955,
133.34019470214844, 9.8403329849243164),
(266, 51630, 6, 146.63166809082031, -0.98827779293060303,
146.91035461425781, 30.08709716796875),
(266, 51630, 7, 146.91944885253906, -0.99049174785614014,
152.96893310546875, 12.429832458496094),
(266, 51630, 9, 146.76339721679688, -0.81043314933776855,
347.72918701171875, 41.387767791748047),
(266, 51630, 10, 146.62281799316406, -0.9513852596282959,
162.53567504882812, 24.676788330078125),
(266, 51630, 11, 146.93409729003906, -0.67040395736694336,
266.56011962890625, 10.875675201416016),
(266, 51630, 12, 146.96389770507812, -0.54500257968902588,
92.040328979492188, 18.999214172363281),
(266, 51630, 13, 146.9635009765625, -0.75935173034667969,
72.828048706054688, 13.028598785400391)],
dtype=[('PLATEID', '>i2'), ('MJD', '>i4'), ('FIBERID', '>i2'),
('RA', '>f4'), ('DEC', '>f4'), ('V_DISP', '>f4'), ('V_DISP_ERR', '>f4')])
So I would like to know if it's normal. And another question is it possile to
do, in theory, something like:
b = numpy.array(data_end,dtype=type_descr)
or all individual array element must have the same dtype?
To replace the context, I have a big fits table, I want to use only some
columns from the table so I did:
table = pyfits.getdata('gal_info_dr4_v5_1b.fit') #pyfits can't read, at least
now the gzip file
#the file is a fits table file so we look in the pyfits doc to read it!
fields = ['PLATEID', 'MJD', 'FIBERID', 'RA', 'DEC','V_DISP','V_DISP_ERR']
type_descr = numpy.dtype({'names':fields,'formats':
['<i2','<i4','<i2','<f8','<f8','<f8','<f8']})
data_end = numpy.zeros((table.shape[0],len(fields)))
for i in range(len(fields)):
data_end[:,i] = table[:].field(fields[i])
but I want to keep the type from the fits file for each field perhaps there
are a better way to do it.
Thank you very much.
N.
The error when I try to print the big recarray:
In [53]: b
---------------------------------------------------------------------------
exceptions.TypeError Traceback (most recent
call last)
/home/gruel/Desktop/SDSS/DR4/<ipython console>
/home/gruel/usr/lib/python2.4/site-packages/IPython/Prompts.py in
__call__(self, arg)
514
515 # and now call a possibly user-defined print mechanism
--> 516 manipulated_val = self.display(arg)
517
518 # user display hooks can change the variable to be stored
in
/home/gruel/usr/lib/python2.4/site-packages/IPython/Prompts.py in
_display(self, arg)
538 """
539
--> 540 return self.shell.hooks.result_display(arg)
541
542 # Assign the default display method:
/home/gruel/usr/lib/python2.4/site-packages/IPython/hooks.py in __call__(self,
*args, **kw)
132 #print "prio",prio,"cmd",cmd #dbg
133 try:
--> 134 ret = cmd(*args, **kw)
135 return ret
136 except ipapi.TryNext, exc:
/home/gruel/usr/lib/python2.4/site-packages/IPython/hooks.py in
result_display(self, arg)
153
154 if self.rc.pprint:
--> 155 out = pformat(arg)
156 if '\n' in out:
157 # So that multi-line strings line up with the left column
of
/usr/lib/python2.4/pprint.py in pformat(self, object)
108 def pformat(self, object):
109 sio = _StringIO()
--> 110 self._format(object, sio, 0, 0, {}, 0)
111 return sio.getvalue()
112
/usr/lib/python2.4/pprint.py in _format(self, object, stream, indent,
allowance, context, level)
126 self._readable = False
127 return
--> 128 rep = self._repr(object, context, level - 1)
129 typ = _type(object)
130 sepLines = _len(rep) > (self._width - 1 - indent - allowance)
/usr/lib/python2.4/pprint.py in _repr(self, object, context, level)
192 def _repr(self, object, context, level):
193 repr, readable, recursive = self.format(object,
context.copy(),
--> 194 self._depth, level)
195 if not readable:
196 self._readable = False
/usr/lib/python2.4/pprint.py in format(self, object, context, maxlevels,
level)
204 and whether the object represents a recursive construct.
205 """
--> 206 return _safe_repr(object, context, maxlevels, level)
207
208
/usr/lib/python2.4/pprint.py in _safe_repr(object, context, maxlevels, level)
289 return format % _commajoin(components), readable, recursive
290
--> 291 rep = repr(object)
292 return rep, (rep and not rep.startswith('<')), False
293
/home/gruel/usr/lib/python2.4/site-packages/numpy/core/numeric.py in
array_repr(arr, max_line_width, precision, suppress_small)
389 if arr.size > 0 or arr.shape==(0,):
390 lst = array2string(arr, max_line_width, precision,
suppress_small,
--> 391 ', ', "array(")
392 else: # show zero-length shape unless it is (0,)
393 lst = "[], shape=%s" % (repr(arr.shape),)
/home/gruel/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py in
array2string(a, max_line_width, precision, suppress_small, separator, prefix,
style)
202 else:
203 lst = _array2string(a, max_line_width, precision,
suppress_small,
--> 204 separator, prefix)
205 return lst
206
/home/gruel/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py in
_array2string(a, max_line_width, precision, suppress_small, separator,
prefix)
137 if a.size > _summaryThreshold:
138 summary_insert = "..., "
--> 139 data = _leading_trailing(a)
140 else:
141 summary_insert = ""
/home/gruel/usr/lib/python2.4/site-packages/numpy/core/arrayprint.py in
_leading_trailing(a)
108 if a.ndim == 1:
109 if len(a) > 2*_summaryEdgeItems:
--> 110 b = _gen.concatenate((a[:_summaryEdgeItems],
111 a[-_summaryEdgeItems:]))
112 else:
TypeError: expected a readable buffer object
Out[53]:
-------------------------------------------------------------------------
Using Tomcat but need to do more? Need to support web services, security?
Get stuff done quickly with pre-integrated technology to make your job easier
Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo
http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642
_______________________________________________
Numpy-discussion mailing list
Numpy-discussion@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/numpy-discussion
