# All of the functions allow formats to be a dtype 
__all__ = ['record', 'recarray', 'format_parser']

import numpy.core.numeric as sb
from numpy.core.defchararray import chararray
import numpy.core.numerictypes as nt
import types
import os

ndarray = sb.ndarray

_byteorderconv = {'b':'>',
                  'l':'<',
                  'n':'=',
                  'B':'>',
                  'L':'<',
                  'N':'=',
                  'S':'s',
                  's':'s',
                  '>':'>',
                  '<':'<',
                  '=':'=',
                  '|':'|',
                  'I':'|',
                  'i':'|'}

# formats regular expression
# allows multidimension spec with a tuple syntax in front
# of the letter code '(2,3)f4' and ' (  2 ,  3  )  f4  '
# are equally allowed

numfmt = nt.typeDict
_typestr = nt._typestr

def find_duplicate(list):
    """Find duplication in a list, return a list of duplicated elements"""
    dup = []
    for i in range(len(list)):
        if (list[i] in list[i+1:]):
            if (list[i] not in dup):
                dup.append(list[i])
    return dup

class format_parser:
    def __init__(self, formats, names, titles, aligned=False, byteorder=None):
        self._parseFormats(formats, aligned)
        self._setfieldnames(names, titles)
        self._createdescr(byteorder)

    def _parseFormats(self, formats, aligned=0):
        """ Parse the field formats """

        if formats is None:
            raise ValueError, "Need formats argument"
        if isinstance(formats, list):
            if len(formats) < 2:
                formats.append('')
            formats = ','.join(formats)
        dtype = sb.dtype(formats, aligned)
        fields = dtype.fields
        if fields is None:
            dtype = sb.dtype([('f1', dtype)], aligned)
            fields = dtype.fields
        keys = dtype.names
        self._f_formats = [fields[key][0] for key in keys]
        self._offsets = [fields[key][1] for key in keys]
        self._nfields = len(keys)

    def _setfieldnames(self, names, titles):
        """convert input field names into a list and assign to the _names
        attribute """

        if (names):
            if (type(names) in [types.ListType, types.TupleType]):
                pass
            elif (type(names) == types.StringType):
                names = names.split(',')
            else:
                raise NameError, "illegal input names %s" % `names`

            self._names = [n.strip() for n in names[:self._nfields]]
        else:
            self._names = []

        # if the names are not specified, they will be assigned as
        #  "f0, f1, f2,..."
        # if not enough names are specified, they will be assigned as "f[n],
        # f[n+1],..." etc. where n is the number of specified names..."
        self._names += ['f%d' % i for i in range(len(self._names),
                                                 self._nfields)]
        # check for redundant names
        _dup = find_duplicate(self._names)
        if _dup:
            raise ValueError, "Duplicate field names: %s" % _dup

        if (titles):
            self._titles = [n.strip() for n in titles[:self._nfields]]
        else:
            self._titles = []
            titles = []

        if (self._nfields > len(titles)):
            self._titles += [None]*(self._nfields-len(titles))

    def _createdescr(self, byteorder):
        descr = sb.dtype({'names':self._names,
                          'formats':self._f_formats,
                          'offsets':self._offsets,
                          'titles':self._titles})
        if (byteorder is not None):
            byteorder = _byteorderconv[byteorder[0]]
            descr = descr.newbyteorder(byteorder)
            
        self._descr = descr

class record(nt.void):
    def __repr__(self):
        return self.__str__()

    def __str__(self):
        return str(self.item())

    def __getattribute__(self, attr):
        if attr in ['setfield', 'getfield', 'dtype']:
            return nt.void.__getattribute__(self, attr)
        try:
            return nt.void.__getattribute__(self, attr)
        except AttributeError:
            pass
        fielddict = nt.void.__getattribute__(self, 'dtype').fields
        res = fielddict.get(attr,None)
        if res:            
            obj = self.getfield(*res[:2])
            # if it has fields return a recarray,
            # if it's a string return 'SU' return a chararray
            # otherwise return a normal array
            if obj.dtype.fields:
                return obj.view(recarray)
            if obj.dtype.char in 'SU':
                return obj.view(chararray)
            return obj
        else:
            raise AttributeError, "'record' object has no "\
                  "attribute '%s'" % attr
        

    def __setattr__(self, attr, val):
        if attr in ['setfield', 'getfield', 'dtype']:
            raise AttributeError, "Cannot set '%s' attribute" % attr;
        try:
            return nt.void.__setattr__(self,attr,val)
        except AttributeError:
            pass
        fielddict = nt.void.__getattribute__(self,'dtype').fields
        res = fielddict.get(attr,None)
        if res:
            return self.setfield(val,*res[:2])
        else:
            raise AttributeError, "'record' object has no "\
                  "attribute '%s'" % attr

# The recarray is almost identical to a standard array (which supports
#   named fields already)  The biggest difference is that it can use
#   attribute-lookup to find the fields and it is constructed using
#   a record.

# If byteorder is given it forces a particular byteorder on all
#  the fields (and any subfields)

class recarray(ndarray):
    def __new__(subtype, shape, dtype=None, buf=None, offset=0, strides=None,
                formats=None, names=None, titles=None,
                byteorder=None, aligned=False, heapoffset=0, file=None):
        
        if dtype is not None:
            descr = sb.dtype(dtype)
        else:
            descr = format_parser(formats, names, titles, aligned, byteorder)._descr

        if buf is None:
            self = ndarray.__new__(subtype, shape, (record, descr))
        else:
            self = ndarray.__new__(subtype, shape, (record, descr),
                                      buffer=buf, offset=offset,
                                      strides=strides)
            
        self._heapoffset = heapoffset
        self._file = file
        return self

    def __array_finalize__(self,obj):
        if obj is None:
            return 
        self._heapoffset = obj._heapoffset
        self._file = obj._file

    def __getattribute__(self, attr):
        try:
            return object.__getattribute__(self,attr)
        except AttributeError: # attr must be a fieldname
            pass
        fielddict = ndarray.__getattribute__(self,'dtype').fields
        try:
            res = fielddict[attr][:2]
        except (TypeError, KeyError):
            raise AttributeError, "record array has no attribute %s" % attr
        obj = self.getfield(*res)
        # if it has fields return a recarray, otherwise return
        # normal array
        if obj.dtype.fields:
            return obj
        if obj.dtype.char in 'SU':
            return obj.view(chararray)
        return obj.view(ndarray)

# Save the dictionary
#  If the attr is a field name and not in the saved dictionary
#  Undo any "setting" of the attribute and do a setfield
# Thus, you can't create attributes on-the-fly that are field names. 

    def __setattr__(self, attr, val):
        newattr = attr not in self.__dict__
        try:
            ret = object.__setattr__(self, attr, val)
        except:
            fielddict = ndarray.__getattribute__(self,'dtype').fields or {}
            if attr not in fielddict:
                exctype, value = sys.exc_info()[:2]
                raise exctype, value
        else:
            fielddict = ndarray.__getattribute__(self,'dtype').fields or {}
            if attr not in fielddict:
                return ret
            if newattr:         # We just added this one
                try:            #  or this setattr worked on an internal
                                #  attribute. 
                    object.__delattr__(self, attr)
                except:
                    return ret
        try:
            res = fielddict[attr][:2]
        except (TypeError,KeyError):
            raise AttributeError, "record array has no attribute %s" % attr 
        return self.setfield(val,*res)

    def __getitem__(self, indx):
        obj = ndarray.__getitem__(self, indx)
        if (isinstance(obj, ndarray) and obj.dtype.isbuiltin):
            return obj.view(ndarray)
        return obj

    def field(self,attr, val=None):
        if isinstance(attr,int):
            names = ndarray.__getattribute__(self,'dtype').names
            attr=names[attr]

        fielddict = ndarray.__getattribute__(self,'dtype').fields

        res = fielddict[attr][:2]

        if val is None:
            obj = self.getfield(*res)
            if obj.dtype.fields:
                return obj
            if obj.dtype.char in 'SU':
                return obj.view(chararray)
            return obj.view(ndarray)
        else:
            return self.setfield(val, *res)

    def view(self, obj):
        try:
            if issubclass(obj, ndarray):
                return ndarray.view(self, obj)
        except TypeError:
            pass
        dtype = sb.dtype(obj)
        if dtype.fields is None:
            return self.__array__().view(dtype)
        return ndarray.view(self, obj)            
    
def fromarrays(arrayList, dtype=None, shape=None, formats=None,
               names=None, titles=None, aligned=False, byteorder=None):
    """ create a record array from a (flat) list of arrays

    >>> x1=array([1,2,3,4])
    >>> x2=array(['a','dd','xyz','12'])
    >>> x3=array([1.1,2,3,4])
    >>> r=fromarrays([x1,x2,x3],names='a,b,c')
    >>> print r[1]
    (2, 'dd', 2.0)
    >>> x1[1]=34
    >>> r.a
    array([1, 2, 3, 4])
    """
    
    arrayList = [sb.asarray(x) for x in arrayList]
    
    if shape is None or shape == 0:
        shape = arrayList[0].shape

    if isinstance(shape, int):
        shape = (shape,)

    if formats is None and dtype is None:
        # go through each object in the list to see if it is an ndarray
        # and determine the formats.
        formats = ''
        for obj in arrayList:
            if not isinstance(obj, ndarray):
                raise ValueError, "item in the array list must be an ndarray."
            formats += _typestr[obj.dtype.type]
            if issubclass(obj.dtype.type, nt.flexible):
                formats += `obj.itemsize`
            formats += ','
        formats=formats[:-1]

    if dtype is not None:
        descr = sb.dtype(dtype)
        _names = descr.names
    else:
        parsed = format_parser(formats, names, titles, aligned, byteorder)
        _names = parsed._names
        descr = parsed._descr

    # Determine shape from data-type.
    if len(descr) != len(arrayList):
        raise ValueError, "mismatch between the number of fields "\
              "and the number of arrays"
    
    d0 = descr[0].shape
    nn = len(d0)
    if nn > 0:
        shape = shape[:-nn]
        
    for k, obj in enumerate(arrayList):
        nn = len(descr[k].shape)
        testshape = obj.shape[:len(obj.shape)-nn]
        if testshape != shape:
            raise ValueError, "array-shape mismatch in array %d" % k
        
    _array = recarray(shape, descr)

    # populate the record array (makes a copy)
    for i in range(len(arrayList)):
        _array[_names[i]] = arrayList[i]

    return _array

# shape must be 1-d if you use list of lists...
def fromrecords(recList, dtype=None, shape=None, formats=None, names=None,
                titles=None, aligned=False, byteorder=None):
    """ create a recarray from a list of records in text form

        The data in the same field can be heterogeneous, they will be promoted
        to the highest data type.  This method is intended for creating
        smaller record arrays.  If used to create large array without formats
        defined

        r=fromrecords([(2,3.,'abc')]*100000)

        it can be slow.

        If formats is None, then this will auto-detect formats. Use list of
        tuples rather than list of lists for faster processing.

    >>> r=fromrecords([(456,'dbe',1.2),(2,'de',1.3)],names='col1,col2,col3')
    >>> print r[0]
    (456, 'dbe', 1.2)
    >>> r.col1
    array([456,   2])
    >>> r.col2
    chararray(['dbe', 'de'])
    >>> import cPickle
    >>> print cPickle.loads(cPickle.dumps(r))
    recarray[
    (456, 'dbe', 1.2),
    (2, 'de', 1.3)
    ]
    """
    
    nfields = len(recList[0])
    if formats is None and dtype is None:  # slower
        obj = sb.array(recList,dtype=object)
        arrlist = [sb.array(obj[...,i].tolist()) for i in xrange(nfields)]
        return fromarrays(arrlist, formats=formats, shape=shape, names=names,
                          titles=titles, aligned=aligned, byteorder=byteorder)

    if dtype is not None:
        descr = sb.dtype(dtype)
    else:
        descr = format_parser(formats, names, titles, aligned, byteorder)._descr

    try:
        retval = sb.array(recList, dtype = descr)
    except TypeError:  # list of lists instead of list of tuples
        if (shape is None or shape == 0):
            shape = len(recList)
        if isinstance(shape, (int, long)):
            shape = (shape,)
        if len(shape) > 1:
            raise ValueError, "Can only deal with 1-d array."
        _array = recarray(shape, descr)
        for k in xrange(_array.size):
            _array[k] = tuple(recList[k])
        return _array
    else:
        if shape is not None and retval.shape != shape:
            retval.shape = shape

    res = retval.view(recarray)
        
    res.dtype = sb.dtype((record, res.dtype))
    return res


def fromstring(datastring, dtype=None, shape=None, offset=0, formats=None,
               names=None, titles=None, aligned=False, byteorder=None):
    """ create a (read-only) record array from binary data contained in
    a string"""
    

    if dtype is None and formats is None:
        raise ValueError, "Must have dtype= or formats="

    if dtype is not None:
        descr = sb.dtype(dtype)
    else:
        descr = format_parser(formats, names, titles, aligned, byteorder)._descr
        
    itemsize = descr.itemsize
    if (shape is None or shape == 0 or shape == -1):
        shape = (len(datastring)-offset) / itemsize
        
    _array = recarray(shape, descr, buf=datastring, offset=offset)
    return _array

def get_remaining_size(fd):
    try:
        fn = fd.fileno()
    except AttributeError:
        return os.path.getsize(fd.name) - fd.tell()
    st = os.fstat(fn)
    size = st.st_size - fd.tell()
    return size

def fromfile(fd, dtype=None, shape=None, offset=0, formats=None,
             names=None, titles=None, aligned=False, byteorder=None):
    """Create an array from binary file data

    If file is a string then that file is opened, else it is assumed
    to be a file object.

    >>> import testdata, sys
    >>> fd=open(testdata.filename)
    >>> fd.seek(2880*2)
    >>> r=fromfile(fd, formats='f8,i4,a5', shape=3, byteorder='big')
    >>> print r[0]
    (5.1000000000000005, 61, 'abcde')
    >>> r._shape
    (3,)
    """


    if (shape is None or shape == 0):
        shape = (-1,)
    elif isinstance(shape, (int, long)):
        shape = (shape,)

    name = 0
    if isinstance(fd, str):
        name = 1
        fd = open(fd, 'rb')
    if (offset > 0):
        fd.seek(offset, 1)
    size = get_remaining_size(fd)
    
    if dtype is not None:
        descr = sb.dtype(dtype)
    else:
        descr = format_parser(formats, names, titles, aligned, byteorder)._descr

    itemsize = descr.itemsize

    shapeprod = sb.array(shape).prod()
    shapesize = shapeprod*itemsize
    if shapesize < 0:
        shape = list(shape)
        shape[ shape.index(-1) ] = size / -shapesize
        shape = tuple(shape)
        shapeprod = sb.array(shape).prod()

    nbytes = shapeprod*itemsize

    if nbytes > size:
        raise ValueError(
                "Not enough bytes left in file for specified shape and type")

    # create the array
    _array = recarray(shape, descr)
    nbytesread = fd.readinto(_array.data)
    if nbytesread != nbytes:
        raise IOError("Didn't read as many bytes as expected")
    if name:
        fd.close()

    return _array

def array(obj, dtype=None, shape=None, offset=0, strides=None, formats=None,
          names=None, titles=None, aligned=False, byteorder=None, copy=True):
    """Construct a record array from a wide-variety of objects.
    """

    if isinstance(obj, (type(None), str, file)) and (formats is None) \
           and (dtype is None):
        raise ValueError("Must define formats (or dtype) if object is "\
                         "None, string, or an open file")

    kwds = {}
    if dtype is not None:
        dtype = sb.dtype(dtype)
    elif formats is not None:
        dtype = format_parser(formats, names, titles,
                              aligned, byteorder)._descr
    else:
        kwds = {'formats': formats,
                'names' : names,
                'titles' : titles,
                'aligned' : aligned,
                'byteorder' : byteorder
                }
        
    if obj is None:
        if shape is None:
            raise ValueError("Must define a shape if obj is None")
        return recarray(shape, dtype, buf=obj, offset=offset, strides=strides)
    elif isinstance(obj, str):
        return fromstring(obj, dtype, shape=shape, offset=offset, **kwds)

    elif isinstance(obj, (list, tuple)):
        if isinstance(obj[0], (tuple, list)):
            return fromrecords(obj, dtype=dtype, shape=shape, **kwds)
        else:
            return fromarrays(obj, dtype=dtype, shape=shape, **kwds)

    elif isinstance(obj, recarray):
        if dtype is not None and (obj.dtype != dtype):
            new = obj.view(dtype)
        else:
            new = obj
        if copy:
            new = new.copy()
        return new

    elif isinstance(obj, file):
        return fromfile(obj, dtype=dtype, shape=shape, offset=offset)

    elif isinstance(obj, ndarray):
        if dtype is not None and (obj.dtype != dtype):
            new = obj.view(dtype)
        else:
            new = obj
        if copy:
            new = new.copy()
        res = new.view(recarray)
        if issubclass(res.dtype.type, nt.void):
            res.dtype = sb.dtype((record, res.dtype))
        return res

    else:
        interface = getattr(obj, "__array_interface__", None)
        if interface is None or not isinstance(interface, dict):
            raise ValueError("Unknown input type")
        obj = sb.array(obj)
        if dtype is not None and (obj.dtype != dtype):
            obj = obj.view(dtype)
        res  = obj.view(recarray)
        if issubclass(res.dtype.type, nt.void):
            res.dtype = sb.dtype((record, res.dtype))
        return res
