def PYTHONPATH(use=False, notuse=False):
'''
$PYTHONHOME
$PYTHONPATH
(1) use=False
NOT append to sys.path
notuse=False
NOT remove from sys.path
(2) use=None
append $PYTHONPATH to sys.path
(3) use=str | [str, str, ...]
append it/them to sys.path
(4) notuse=None
like =False, NOT remove from sys.path
(5) notuse=str | [str, str, ...]
remove it/them from sys.path
return:
Updated sys.path
'''
import sys, os
from jizhipy.Basic import IsType, ShellCmd
#----------------------------------------
if (use is True or use is False): use = []
elif (use is None):
use = ShellCmd('echo $PYTHONPATH')[0].split(':')
elif (IsType.isstr(use)):
use = [use]
elif (IsType.istuple(use)):
use = list(use)
#----------------------------------------
if (notuse is True or notuse is False or notuse is None): notuse = []
elif (IsType.isstr(notuse)): notuse = [notuse]
elif (IsType.istuple(notuse)): notuse = list(notuse)
#----------------------------------------
n = 0
while (n < len(use)):
if (use[n] == ''): use.pop(n)
else:
if (use[n][-1] == '/'):
use[n] = use[n][:-1]
n += 1
if (len(use) > 0): use = [''] + use
#----------------------------------------
here = os.path.abspath('')
notusehere = True if ('' in notuse) else False
for i in range(len(notuse)):
notuse[i] = os.path.abspath(os.path.expanduser(notuse[i]))
if (notusehere): notuse.append('')
#----------------------------------------
sys.path = use + sys.path
for i in range(len(notuse)):
while (notuse[i] in sys.path):
sys.path.remove(notuse[i])
return sys.path[:]
def _Hdf52Fits( dataset, hduname='' ) :
if (hduname in ['', None]) :
name = str(dataset.name)
name = name[name.rfind('/')+1:]
else : name = str(hduname)
attrs = dataset.attrs.items()
data = dataset.value
hdulist = []
try :
if (data.dtype.name[:7] == 'complex') :
hdu = pyfits.ImageHDU( data.real )
hdu.name = name+'REAL'
hdr = hdu.header
for i in range(len(attrs)) :
hdr[str(attrs[i][0])] = attrs[i][1]
hdulist.append(hdu) #@#@
hdu = pyfits.ImageHDU( data.imag )
hdu.name = name+'IMAG'
hdr = hdu.header
for i in range(len(attrs)) :
hdr[str(attrs[i][0])] = attrs[i][1]
hdulist.append(hdu) #@#@
else : raise
except :
if (IsType.isndarray(data) or IsType.islist(data) or IsType.istuple(data)) :
try : hdu = pyfits.ImageHDU( data )
except : hdu = pyfits.ImageHDU( np.array(data, np.float32) )
hdu.name = name
hdr = hdu.header
for i in range(len(attrs)) :
hdr[str(attrs[i][0])[:8]] = attrs[i][1]
hdulist.append(hdu)
else : other.header[name[:8]] = data
return hdulist
def Ymap( self, ymap=None ) :
'''
ymap:
Input y map, must be 2D array/matrix.
y.shape = (nfreq, npix), row nfreq is the number of frequencies, column npix is the number of pixels at its frequency.
(1) y is ndarray
(2) y is list, len(y)==nfreq
'''
import numpy as np
from jizhipy.Basic import Raise, SysFrame, IsType
from jizhipy.Array import Asarray
from jizhipy.Optimize import Smooth
if (ymap is None) :
if (SysFrame(0,2)[-3][-2]!='') :
self.ymap = None
if (self.verbose) : print(' self.y = None')
return
else : return self.ymap
pstr = ' ' if ('ymap' not in self.__dict__.keys())else ' Change: '
if (IsType.islist(ymap) or IsType.istuple(ymap)) :
if (not IsType.isnum(ymap[0])) :
ymap, N = list(ymap), 1e15
for i in range(len(ymap)) :
if (len(ymap) < N) : N = len(ymap)
for i in range(len(ymap)) :
ymap[i]=jp.Smooth(ymap[i], 0,reduceshape=N)
self.ymap = Asarray(ymap, np.float64) # force bit64
if (len(self.ymap.shape) not in [1, 2]) : Raise(Exception, 'jizhipy.PCA: ymap must be 1D/2D, but now ymap.shape='+str(self.ymap.shape))
if (self.verbose) : print(pstr+'self.ymap.shape =', self.ymap.shape)
return self.ymap
def Save( self ) :
'''
Save instance to .hdf5
'''
from jizhipy.Basic import Path, IsType, Raise
import numpy as np
import h5py
self.outname = str(self.outname)
if (self.outname[-5:] !='.hdf5') : self.outname += '.hdf5'
Path.ExistsPath(self.outname, old=True)
if (self.verbose) : print('jizhipy.ClassHdf5: Saveing to "'+self.outname+'"')
fo = h5py.File(self.outname, 'w')
if (self.value is None or self.keys is None): self.Values()
fo['classinstance'] = str(type(self.classinstance))
for i in range(len(self.keys)) :
if (self.values[i] is None) :
fo[self.keys[i]] = '__None__'
fo[self.keys[i]].attrs['type'] = 'is None, not str'
#--------------------------------------------------
elif (IsType.isdtype(self.values[i])) :
fo[self.keys[i]]=np.dtype(self.values[i]).name
fo[self.keys[i]].attrs['type'] = 'numpy.dtype'
#--------------------------------------------------
elif (IsType.ismatrix(self.values[i])) :
fo[self.keys[i]] = np.array(self.values[i])
fo[self.keys[i]].attrs['type'] = 'numpy.matrix'
#--------------------------------------------------
elif (IsType.ismaskedarray(self.values[i])) :
fo[self.keys[i]] = self.values[i].data
fo[self.keys[i]+'.mask'] = self.values[i].mask
fo[self.keys[i]].attrs['type'] = 'numpy.MaskedArray .data'
fo[self.keys[i]+'.mask'].attrs['type'] = 'numpy.MaskedArray .mask'
#--------------------------------------------------
elif (IsType.isdict(self.values[i])) :
self._OperaDict(self.values[i])
try : fo[self.keys[i]] =self.values[i].values()
except : fo[self.keys[i]] = str(self.values[i].values())
fo[self.keys[i]+'.keys'] = self.values[i].keys()
fo[self.keys[i]].attrs['type']='dict .values()'
fo[self.keys[i]+'.keys'].attrs['type']='dict .keys()'
self._OperaDict(self.values[i])
#--------------------------------------------------
else :
# inside list and tuple, must not contain dict
try : fo[self.keys[i]] = self.values[i] # convert to np.ndarray with same dtype, if contains string, will conver to string array
except :
strv = str([self.values[i]])[1:-1]
Raise(Exception, "fo['"+self.keys[i]+"'] = "+strv)
if (IsType.islist(self.values[i])) :
fo[self.keys[i]].attrs['type'] = 'list'
elif (IsType.istuple(self.values[i])) :
fo[self.keys[i]].attrs['type'] = 'tuple'
else : fo[self.keys[i]].attrs['type'] = 'numpy.array'
#--------------------------------------------------
fo.flush()
fo.close()
def Array2FitsImage( arraylist, outname, names=None, keys=None, values=None, comments=None, verbose=False ) :
'''
arraylist:
(1) isndarray
(2) list/tuple of ndarray: [array1, array2, ...]
Otherwise, raise error
Examples:
Array2FitsImage( [1,2,3] ), means there are 3 arrays, array1=1, array2=2, array3=3
FITS can save int/float number to ImageHDU, but will raise error "IOError: Header missing END card." when pyfits.open() it.
You must convert to
Array2FitsImage( np.array([1,2,3]), 'test.fits' )
OR Array2FitsImage( [[1,2,3]], 'test.fits' )
names:
None | Same shape as arraylist
Name of each ImageHDU in fo.info()
keys:
None | Same shape as arraylist
(1) arraylist isndarray: keys=['key1', 'key2', ...], list of str
(2) arraylist is list/tuple of ndarray: [array1, array2, ...], then keys=[arraykey1, arraykey2, ...], arraykey1=['key1', 'key2', ...] (list of list)
values:
Same shape as keys
comments:
None | same shape as keys even though is ''
'''
from jizhipy.Basic import Path, IsType
import pyfits
outname = Path.AbsPath(outname)
if (outname[-5:].lower() != '.fits') : outname += '.fits'
Path.ExistsPath(outname, True)
if (verbose) : print('Saving "'+outname+'"')
#--------------------------------------------------
if (IsType.isstr(keys)) :
keys, values = [keys], [values]
if (comments is not None) : comments = [comments]
else : comments = ['']
#--------------------------------------------------
if (not IsType.islist(arraylist) and not IsType.istuple(arraylist)) :
arraylist = [arraylist]
if (names is not None) : names = [names]
keys = [keys for i in range(len(arraylist))]
values = [values for i in range(len(arraylist))]
comments = [comments for i in range(len(arraylist))]
#--------------------------------------------------
hdulist = pyfits.HDUList()
for i in range(len(arraylist)) :
data = arraylist[i]
try : name = str(names[i])
except : name = 'hdu'+str(i)
if (data.dtype.name[:7] == 'complex') :
hdu = pyfits.ImageHDU( data.real )
hdu.name = name+'REAL'
hdr = hdu.header
for j in range(len(keys[i])) :
key, value = keys[i][j], values[i][j]
try : comment = comments[i][j]
except : comment = ''
hdr.set(key, value, comment)
hdulist.append(hdu) # Real part
hdu = pyfits.ImageHDU( data.imag )
hdu.name = name+'IMAG'
hdr = hdu.header
try :
for j in range(len(keys[i])) :
key, value = keys[i][j], values[i][j]
try : comment = comments[i][j]
except : comment = ''
hdr.set(key, value, comment)
except : pass
hdulist.append(hdu) # Imag part
#--------------------------------------------------
else :
hdu = pyfits.ImageHDU( data )
hdu.name = name
hdr = hdu.header
try :
for j in range(len(keys[i])) :
key, value = keys[i][j], values[i][j]
try : comment = comments[i][j]
except : comment = ''
hdr.set(key, value, comment)
except : pass
hdulist.append(hdu)
#--------------------------------------------------
hdulist.writeto( outname )