def calculate_contour_dvh(mask, doseplane, maxdose, dd, id, structure):
"""Calculate the differential DVH for the given contour and dose plane."""
# Multiply the structure mask by the dose plane to get the dose mask
mask = ma.array(doseplane * dd['dosegridscaling'] * 100, mask=~mask)
# Calculate the differential dvh
hist, edges = np.histogram(mask.compressed(),
bins=maxdose,
range=(0, maxdose))
# Calculate the volume for the contour for the given dose plane
vol = sum(hist) * ((id['pixelspacing'][0]) *
(id['pixelspacing'][1]) *
(structure['thickness']))
return hist, vol
# ========================== Test DVH Calculation =========================== #
python类array()的实例源码
def test_flatten_wflexible(self):
# Test flatten standard & nested
(w, x, _, _) = self.data
test = merge_arrays((x, w), flatten=True)
control = np.array([(1, 1, 2, 3.0), (2, 4, 5, 6.0)],
dtype=[('f0', int),
('a', int), ('ba', float), ('bb', int)])
assert_equal(test, control)
test = merge_arrays((x, w), flatten=False)
controldtype = [('f0', int),
('f1', [('a', int),
('b', [('ba', float), ('bb', int)])])]
control = np.array([(1., (1, (2, 3.0))), (2, (4, (5, 6.0)))],
dtype=controldtype)
assert_equal(test, control)
def test_defaults(self):
# Test defaults: no exception raised if keys of defaults are not fields.
(_, _, _, z) = self.data
zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
dtype=[('A', '|S3'), ('B', float), ('C', float)])
defaults = {'A': '???', 'B': -999., 'C': -9999., 'D': -99999.}
test = stack_arrays((z, zz), defaults=defaults)
control = ma.array([('A', 1, -9999.), ('B', 2, -9999.),
(
'a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
dtype=[('A', '|S3'), ('B', float), ('C', float)],
mask=[(0, 0, 1), (0, 0, 1),
(0, 0, 0), (0, 0, 0), (0, 0, 0)])
assert_equal(test, control)
assert_equal(test.data, control.data)
assert_equal(test.mask, control.mask)
def test_autoconversion(self):
# Tests autoconversion
adtype = [('A', int), ('B', bool), ('C', float)]
a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype)
bdtype = [('A', int), ('B', float), ('C', float)]
b = ma.array([(4, 5, 6)], dtype=bdtype)
control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)],
dtype=bdtype)
test = stack_arrays((a, b), autoconvert=True)
assert_equal(test, control)
assert_equal(test.mask, control.mask)
try:
test = stack_arrays((a, b), autoconvert=False)
except TypeError:
pass
else:
raise AssertionError
def test_join(self):
a, b = self.a, self.b
# Fixme, this test is broken
#test = join_by(('a', 'b'), a, b)
#control = np.array([(5, 55, 105, 100), (6, 56, 106, 101),
# (7, 57, 107, 102), (8, 58, 108, 103),
# (9, 59, 109, 104)],
# dtype=[('a', int), ('b', int),
# ('c', int), ('d', int)])
#assert_equal(test, control)
# Hack to avoid pyflakes unused variable warnings
join_by(('a', 'b'), a, b)
np.array([(5, 55, 105, 100), (6, 56, 106, 101),
(7, 57, 107, 102), (8, 58, 108, 103),
(9, 59, 109, 104)],
dtype=[('a', int), ('b', int),
('c', int), ('d', int)])
def test_leftouter_join(self):
a, b = self.a, self.b
test = join_by(('a', 'b'), a, b, 'leftouter')
control = ma.array([(0, 50, 100, -1), (1, 51, 101, -1),
(2, 52, 102, -1), (3, 53, 103, -1),
(4, 54, 104, -1), (5, 55, 105, -1),
(6, 56, 106, -1), (7, 57, 107, -1),
(8, 58, 108, -1), (9, 59, 109, -1)],
mask=[(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1)],
dtype=[('a', int), ('b', int), ('c', int), ('d', int)])
assert_equal(test, control)
def test_two_keys_two_vars(self):
a = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2),
np.arange(50, 60), np.arange(10, 20))),
dtype=[('k', int), ('a', int), ('b', int), ('c', int)])
b = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2),
np.arange(65, 75), np.arange(0, 10))),
dtype=[('k', int), ('a', int), ('b', int), ('c', int)])
control = np.array([(10, 0, 50, 65, 10, 0), (11, 0, 51, 66, 11, 1),
(10, 1, 52, 67, 12, 2), (11, 1, 53, 68, 13, 3),
(10, 2, 54, 69, 14, 4), (11, 2, 55, 70, 15, 5),
(10, 3, 56, 71, 16, 6), (11, 3, 57, 72, 17, 7),
(10, 4, 58, 73, 18, 8), (11, 4, 59, 74, 19, 9)],
dtype=[('k', int), ('a', int), ('b1', int),
('b2', int), ('c1', int), ('c2', int)])
test = join_by(
['a', 'k'], a, b, r1postfix='1', r2postfix='2', jointype='inner')
assert_equal(test.dtype, control.dtype)
assert_equal(test, control)
def test_format(self):
a = np.array([(1, 2), (3, 4)])
c = BytesIO()
# Sequence of formats
np.savetxt(c, a, fmt=['%02d', '%3.1f'])
c.seek(0)
assert_equal(c.readlines(), [b'01 2.0\n', b'03 4.0\n'])
# A single multiformat string
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Specify delimiter, should be overiden
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f', delimiter=',')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Bad fmt, should raise a ValueError
c = BytesIO()
assert_raises(ValueError, np.savetxt, c, a, fmt=99)
def test_record(self):
c = TextIO()
c.write('1 2\n3 4')
c.seek(0)
x = np.loadtxt(c, dtype=[('x', np.int32), ('y', np.int32)])
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
assert_array_equal(x, a)
d = TextIO()
d.write('M 64.0 75.0\nF 25.0 60.0')
d.seek(0)
mydescriptor = {'names': ('gender', 'age', 'weight'),
'formats': ('S1', 'i4', 'f4')}
b = np.array([('M', 64.0, 75.0),
('F', 25.0, 60.0)], dtype=mydescriptor)
y = np.loadtxt(d, dtype=mydescriptor)
assert_array_equal(y, b)
def test_dtype_with_object(self):
# Test using an explicit dtype with an object
data = """ 1; 2001-01-01
2; 2002-01-31 """
ndtype = [('idx', int), ('code', np.object)]
func = lambda s: strptime(s.strip(), "%Y-%m-%d")
converters = {1: func}
test = np.genfromtxt(TextIO(data), delimiter=";", dtype=ndtype,
converters=converters)
control = np.array(
[(1, datetime(2001, 1, 1)), (2, datetime(2002, 1, 31))],
dtype=ndtype)
assert_equal(test, control)
ndtype = [('nest', [('idx', int), ('code', np.object)])]
try:
test = np.genfromtxt(TextIO(data), delimiter=";",
dtype=ndtype, converters=converters)
except NotImplementedError:
pass
else:
errmsg = "Nested dtype involving objects should be supported."
raise AssertionError(errmsg)
def test_usecols(self):
# Test the selection of columns
# Select 1 column
control = np.array([[1, 2], [3, 4]], float)
data = TextIO()
np.savetxt(data, control)
data.seek(0)
test = np.ndfromtxt(data, dtype=float, usecols=(1,))
assert_equal(test, control[:, 1])
#
control = np.array([[1, 2, 3], [3, 4, 5]], float)
data = TextIO()
np.savetxt(data, control)
data.seek(0)
test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
assert_equal(test, control[:, 1:])
# Testing with arrays instead of tuples.
data.seek(0)
test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
assert_equal(test, control[:, 1:])
def test_withmissing(self):
data = TextIO('A,B\n0,1\n2,N/A')
kwargs = dict(delimiter=",", missing_values="N/A", names=True)
test = np.mafromtxt(data, dtype=None, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', np.int), ('B', np.int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
#
data.seek(0)
test = np.mafromtxt(data, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', np.float), ('B', np.float)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
def test_replace_space(self):
# Test the 'replace_space' option
txt = "A.A, B (B), C:C\n1, 2, 3.14"
# Test default: replace ' ' by '_' and delete non-alphanum chars
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None)
ctrl_dtype = [("AA", int), ("B_B", int), ("CC", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no replace, no delete
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None,
replace_space='', deletechars='')
ctrl_dtype = [("A.A", int), ("B (B)", int), ("C:C", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no delete (spaces are replaced by _)
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None,
deletechars='')
ctrl_dtype = [("A.A", int), ("B_(B)", int), ("C:C", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
def test_replace_space_known_dtype(self):
# Test the 'replace_space' (and related) options when dtype != None
txt = "A.A, B (B), C:C\n1, 2, 3"
# Test default: replace ' ' by '_' and delete non-alphanum chars
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int)
ctrl_dtype = [("AA", int), ("B_B", int), ("CC", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no replace, no delete
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int,
replace_space='', deletechars='')
ctrl_dtype = [("A.A", int), ("B (B)", int), ("C:C", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no delete (spaces are replaced by _)
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int,
deletechars='')
ctrl_dtype = [("A.A", int), ("B_(B)", int), ("C:C", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
def test_recfromtxt(self):
#
data = TextIO('A,B\n0,1\n2,3')
kwargs = dict(delimiter=",", missing_values="N/A", names=True)
test = np.recfromtxt(data, **kwargs)
control = np.array([(0, 1), (2, 3)],
dtype=[('A', np.int), ('B', np.int)])
self.assertTrue(isinstance(test, np.recarray))
assert_equal(test, control)
#
data = TextIO('A,B\n0,1\n2,N/A')
test = np.recfromtxt(data, dtype=None, usemask=True, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', np.int), ('B', np.int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
assert_equal(test.A, [0, 2])
def test_gzip_loadtxt():
# Thanks to another windows brokeness, we can't use
# NamedTemporaryFile: a file created from this function cannot be
# reopened by another open call. So we first put the gzipped string
# of the test reference array, write it to a securely opened file,
# which is then read from by the loadtxt function
s = BytesIO()
g = gzip.GzipFile(fileobj=s, mode='w')
g.write(b'1 2 3\n')
g.close()
s.seek(0)
with temppath(suffix='.gz') as name:
with open(name, 'wb') as f:
f.write(s.read())
res = np.loadtxt(name)
s.close()
assert_array_equal(res, [1, 2, 3])
def test_set_mask_fromfields(self):
mbase = self.base.copy().view(mrecarray)
nmask = np.array(
[(0, 1, 0), (0, 1, 0), (1, 0, 1), (1, 0, 1), (0, 0, 0)],
dtype=[('a', bool), ('b', bool), ('c', bool)])
mbase.mask = nmask
assert_equal(mbase.a.mask, [0, 0, 1, 1, 0])
assert_equal(mbase.b.mask, [1, 1, 0, 0, 0])
assert_equal(mbase.c.mask, [0, 0, 1, 1, 0])
# Reinitalizes and redo
mbase.mask = False
mbase.fieldmask = nmask
assert_equal(mbase.a.mask, [0, 0, 1, 1, 0])
assert_equal(mbase.b.mask, [1, 1, 0, 0, 0])
assert_equal(mbase.c.mask, [0, 0, 1, 1, 0])
def test_exotic_formats(self):
# Test that 'exotic' formats are processed properly
easy = mrecarray(1, dtype=[('i', int), ('s', '|S8'), ('f', float)])
easy[0] = masked
assert_equal(easy.filled(1).item(), (1, asbytes('1'), 1.))
solo = mrecarray(1, dtype=[('f0', '<f8', (2, 2))])
solo[0] = masked
assert_equal(solo.filled(1).item(),
np.array((1,), dtype=solo.dtype).item())
mult = mrecarray(2, dtype="i4, (2,3)float, float")
mult[0] = masked
mult[1] = (1, 1, 1)
mult.filled(0)
assert_equal_records(mult.filled(0),
np.array([(0, 0, 0), (1, 1, 1)],
dtype=mult.dtype))
def __setstate__(self, state):
"""
Restore the internal state of the masked array.
This is for pickling. ``state`` is typically the output of the
``__getstate__`` output, and is a 5-tuple:
- class name
- a tuple giving the shape of the data
- a typecode for the data
- a binary string for the data
- a binary string for the mask.
"""
(ver, shp, typ, isf, raw, msk, flv) = state
ndarray.__setstate__(self, (shp, typ, isf, raw))
mdtype = dtype([(k, bool_) for (k, _) in self.dtype.descr])
self.__dict__['_mask'].__setstate__((shp, mdtype, isf, msk))
self.fill_value = flv
def get_contour_mask(dd, id, dosegridpoints, contour):
"""Get the mask for the contour with respect to the dose plane."""
doselut = dd['lut']
c = matplotlib.path.Path(list(contour))
# def inpolygon(polygon, xp, yp):
# return np.array(
# [Point(x, y).intersects(polygon) for x, y in zip(xp, yp)],
# dtype=np.bool)
# p = Polygon(contour)
# x, y = np.meshgrid(np.array(dd['lut'][0]), np.array(dd['lut'][1]))
# mask = inpolygon(p, x.ravel(), y.ravel())
# return mask.reshape((len(doselut[1]), len(doselut[0])))
grid = c.contains_points(dosegridpoints)
grid = grid.reshape((len(doselut[1]), len(doselut[0])))
return grid
def test_flatten_wflexible(self):
# Test flatten standard & nested
(w, x, _, _) = self.data
test = merge_arrays((x, w), flatten=True)
control = np.array([(1, 1, 2, 3.0), (2, 4, 5, 6.0)],
dtype=[('f0', int),
('a', int), ('ba', float), ('bb', int)])
assert_equal(test, control)
test = merge_arrays((x, w), flatten=False)
controldtype = [('f0', int),
('f1', [('a', int),
('b', [('ba', float), ('bb', int)])])]
control = np.array([(1., (1, (2, 3.0))), (2, (4, (5, 6.0)))],
dtype=controldtype)
assert_equal(test, control)
def test_defaults(self):
# Test defaults: no exception raised if keys of defaults are not fields.
(_, _, _, z) = self.data
zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
dtype=[('A', '|S3'), ('B', float), ('C', float)])
defaults = {'A': '???', 'B': -999., 'C': -9999., 'D': -99999.}
test = stack_arrays((z, zz), defaults=defaults)
control = ma.array([('A', 1, -9999.), ('B', 2, -9999.),
(
'a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
dtype=[('A', '|S3'), ('B', float), ('C', float)],
mask=[(0, 0, 1), (0, 0, 1),
(0, 0, 0), (0, 0, 0), (0, 0, 0)])
assert_equal(test, control)
assert_equal(test.data, control.data)
assert_equal(test.mask, control.mask)
def test_autoconversion(self):
# Tests autoconversion
adtype = [('A', int), ('B', bool), ('C', float)]
a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype)
bdtype = [('A', int), ('B', float), ('C', float)]
b = ma.array([(4, 5, 6)], dtype=bdtype)
control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)],
dtype=bdtype)
test = stack_arrays((a, b), autoconvert=True)
assert_equal(test, control)
assert_equal(test.mask, control.mask)
try:
test = stack_arrays((a, b), autoconvert=False)
except TypeError:
pass
else:
raise AssertionError
def test_join(self):
a, b = self.a, self.b
# Fixme, this test is broken
#test = join_by(('a', 'b'), a, b)
#control = np.array([(5, 55, 105, 100), (6, 56, 106, 101),
# (7, 57, 107, 102), (8, 58, 108, 103),
# (9, 59, 109, 104)],
# dtype=[('a', int), ('b', int),
# ('c', int), ('d', int)])
#assert_equal(test, control)
# Hack to avoid pyflakes unused variable warnings
join_by(('a', 'b'), a, b)
np.array([(5, 55, 105, 100), (6, 56, 106, 101),
(7, 57, 107, 102), (8, 58, 108, 103),
(9, 59, 109, 104)],
dtype=[('a', int), ('b', int),
('c', int), ('d', int)])
def test_leftouter_join(self):
a, b = self.a, self.b
test = join_by(('a', 'b'), a, b, 'leftouter')
control = ma.array([(0, 50, 100, -1), (1, 51, 101, -1),
(2, 52, 102, -1), (3, 53, 103, -1),
(4, 54, 104, -1), (5, 55, 105, -1),
(6, 56, 106, -1), (7, 57, 107, -1),
(8, 58, 108, -1), (9, 59, 109, -1)],
mask=[(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1),
(0, 0, 0, 1), (0, 0, 0, 1)],
dtype=[('a', int), ('b', int), ('c', int), ('d', int)])
assert_equal(test, control)
def test_two_keys_two_vars(self):
a = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2),
np.arange(50, 60), np.arange(10, 20))),
dtype=[('k', int), ('a', int), ('b', int), ('c', int)])
b = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2),
np.arange(65, 75), np.arange(0, 10))),
dtype=[('k', int), ('a', int), ('b', int), ('c', int)])
control = np.array([(10, 0, 50, 65, 10, 0), (11, 0, 51, 66, 11, 1),
(10, 1, 52, 67, 12, 2), (11, 1, 53, 68, 13, 3),
(10, 2, 54, 69, 14, 4), (11, 2, 55, 70, 15, 5),
(10, 3, 56, 71, 16, 6), (11, 3, 57, 72, 17, 7),
(10, 4, 58, 73, 18, 8), (11, 4, 59, 74, 19, 9)],
dtype=[('k', int), ('a', int), ('b1', int),
('b2', int), ('c1', int), ('c2', int)])
test = join_by(
['a', 'k'], a, b, r1postfix='1', r2postfix='2', jointype='inner')
assert_equal(test.dtype, control.dtype)
assert_equal(test, control)
def test_format(self):
a = np.array([(1, 2), (3, 4)])
c = BytesIO()
# Sequence of formats
np.savetxt(c, a, fmt=['%02d', '%3.1f'])
c.seek(0)
assert_equal(c.readlines(), [b'01 2.0\n', b'03 4.0\n'])
# A single multiformat string
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Specify delimiter, should be overiden
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f', delimiter=',')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Bad fmt, should raise a ValueError
c = BytesIO()
assert_raises(ValueError, np.savetxt, c, a, fmt=99)
def test_record(self):
c = TextIO()
c.write('1 2\n3 4')
c.seek(0)
x = np.loadtxt(c, dtype=[('x', np.int32), ('y', np.int32)])
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
assert_array_equal(x, a)
d = TextIO()
d.write('M 64.0 75.0\nF 25.0 60.0')
d.seek(0)
mydescriptor = {'names': ('gender', 'age', 'weight'),
'formats': ('S1', 'i4', 'f4')}
b = np.array([('M', 64.0, 75.0),
('F', 25.0, 60.0)], dtype=mydescriptor)
y = np.loadtxt(d, dtype=mydescriptor)
assert_array_equal(y, b)
def main():
# Read the example RT structure and RT dose files
# The testdata was downloaded from the dicompyler website as testdata.zip
# Obtain the structures and DVHs from the DICOM data
rtssfile = 'testdata/rtss.dcm'
rtdosefile = 'testdata/rtdose.dcm'
RTss = dicomparser.DicomParser(rtssfile)
#RTdose = dicomparser.DicomParser("testdata/rtdose.dcm")
RTstructures = RTss.GetStructures()
# Generate the calculated DVHs
calcdvhs = {}
for key, structure in RTstructures.iteritems():
calcdvhs[key] = dvhcalc.get_dvh(rtssfile, rtdosefile, key)
if (key in calcdvhs) and (len(calcdvhs[key].counts) and calcdvhs[key].counts[0]!=0):
print ('DVH found for ' + structure['name'])
pl.plot(calcdvhs[key].counts * 100/calcdvhs[key].counts[0],
color=dvhcalc.np.array(structure['color'], dtype=float) / 255,
label=structure['name'],
linestyle='dashed')
#else:
# print("%d: no DVH"%key)
pl.xlabel('Distance (cm)')
pl.ylabel('Percentage Volume')
pl.legend(loc=7, borderaxespad=-5)
pl.setp(pl.gca().get_legend().get_texts(), fontsize='x-small')
pl.savefig('testdata/dvh.png', dpi = 75)
def setUp(self):
x = np.array([1, 2, ])
y = np.array([10, 20, 30])
z = np.array([('A', 1.), ('B', 2.)],
dtype=[('A', '|S3'), ('B', float)])
w = np.array([(1, (2, 3.0)), (4, (5, 6.0))],
dtype=[('a', int), ('b', [('ba', float), ('bb', int)])])
self.data = (w, x, y, z)
