def test07(self):
"""Testing `wherechunks` method with a `limit`, `skip` parameter"""
N, M = int(1e4), 101
ra = np.fromiter(((i, i*2., i*3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', limit=N-M-2, skip=M):
l += len(block)
s += block['f0'].sum()
self.assert_(l == N - M - 2)
self.assert_(s == np.arange(M+1, N-1).sum())
def test00(self):
"""Testing `wherechunks` method with only an expression"""
N = int(1e4)
ra = np.fromiter(((i, i*2., i*3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2'):
l += len(block)
s += block['f0'].sum()
self.assert_(l == N - 1)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def test05(self):
"""Testing `wherechunks` method with a `limit` parameter"""
N, M = int(1e4), 101
ra = np.fromiter(((i, i*2., i*3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', limit=M):
l += len(block)
s += block['f0'].sum()
self.assert_(l == M)
self.assert_(s == M * ((M + 1) / 2)) # Gauss summation formula
def test02(self):
"""Testing `wherechunks` method with a `outfields` with 2 fields"""
N = int(1e4)
ra = np.fromiter(((i, i, i*3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', outfields=('f1','f2')):
self.assert_(block.dtype.names == ('f1','f2'))
l += len(block)
s += block['f1'].sum()
self.assert_(l == N - 1)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def test00(self):
"""Testing `wherechunks` method with only an expression"""
N = int(1e4)
ra = np.fromiter(((i, i * 2., i * 3) for i in xrange(N)),
dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2'):
l += len(block)
s += block['f0'].sum()
self.assert_(l == N - 1)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def test07(self):
"""Testing `wherechunks` method with a `limit`, `skip` parameter"""
N, M = int(1e4), 101
ra = np.fromiter(((i, i * 2., i * 3) for i in xrange(N)),
dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', limit=N - M - 2, skip=M):
l += len(block)
s += block['f0'].sum()
self.assert_(l == N - M - 2)
self.assert_(s == np.arange(M + 1, N - 1).sum())
def test05(self):
"""Testing `wherechunks` method with a `limit` parameter"""
N, M = int(1e4), 101
ra = np.fromiter(((i, i * 2., i * 3) for i in xrange(N)),
dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', limit=M):
l += len(block)
s += block['f0'].sum()
self.assert_(l == M)
self.assert_(s == M * ((M + 1) / 2)) # Gauss summation formula
def test03(self):
"""Testing `wherechunks` method with a `outfields` with 1 field"""
N = int(1e4)
ra = np.fromiter(((i, i, i * 3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f1 < f2', outfields=('f1', )):
self.assert_(block.dtype.names == ('f1', ))
l += len(block)
s += block['f1'].sum()
self.assert_(l == N - 1)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def test01(self):
"""Testing `wherechunks` method with a `blen`"""
N = int(1e4)
ra = np.fromiter(((i, i*2., i*3) for i in xrange(N)), dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f0 <= f1', blen=100):
l += len(block)
# All blocks should be of length 100, except the last one,
# which should be 0
self.assert_(len(block) in (0, 100))
s += block['f0'].sum()
self.assert_(l == N)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def test01(self):
"""Testing `wherechunks` method with a `blen`"""
N = int(1e4)
ra = np.fromiter(((i, i * 2., i * 3) for i in xrange(N)),
dtype='i4,f8,i8')
t = blz.btable(ra)
l, s = 0, 0
for block in blz.whereblocks(t, 'f0 <= f1', blen=100):
l += len(block)
# All blocks should be of length 100, except the last one,
# which should be 0
self.assert_(len(block) in (0, 100))
s += block['f0'].sum()
self.assert_(l == N)
self.assert_(s == (N - 1) * (N / 2)) # Gauss summation formula
def wherechunks(self,
expression,
blen=None,
outfields=None,
limit=None,
skip=0):
"""Return chunks fulfilling `expression`.
Iterate over the rows that fullfill the `expression` condition
on Table `self.original` in blocks of size `blen`.
Parameters
----------
expression : string or barray
A boolean Numexpr expression or a boolean barray.
blen : int
The length of the block that is returned. The default is the
chunklen, or for a btable, the minimum of the different column
chunklens.
outfields : list of strings or string
The list of column names that you want to get back in results.
Alternatively, it can be specified as a string such as 'f0 f1' or
'f0, f1'. If None, all the columns are returned.
limit : int
A maximum number of elements to return. The default is return
everything.
skip : int
An initial number of elements to skip. The default is 0.
Returns
-------
out : iterable
This iterable returns buffers as NumPy arrays made of
structured types (or homogeneous ones in case `outfields` is a
single field.
See Also
--------
iterchunks
"""
# Return the iterable
return blz.whereblocks(self.blzarr, expression, blen, outfields, limit,
skip)
def wherechunks(self, expression, blen=None, outfields=None, limit=None,
skip=0):
"""Return chunks fulfilling `expression`.
Iterate over the rows that fullfill the `expression` condition
on Table `self.original` in blocks of size `blen`.
Parameters
----------
expression : string or barray
A boolean Numexpr expression or a boolean barray.
blen : int
The length of the block that is returned. The default is the
chunklen, or for a btable, the minimum of the different column
chunklens.
outfields : list of strings or string
The list of column names that you want to get back in results.
Alternatively, it can be specified as a string such as 'f0 f1' or
'f0, f1'. If None, all the columns are returned.
limit : int
A maximum number of elements to return. The default is return
everything.
skip : int
An initial number of elements to skip. The default is 0.
Returns
-------
out : iterable
This iterable returns buffers as NumPy arrays made of
structured types (or homogeneous ones in case `outfields` is a
single field.
See Also
--------
iterchunks
"""
# Return the iterable
return blz.whereblocks(self.blzarr, expression, blen, outfields,
limit, skip)
