python类sctypes()的实例源码

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def chooseAttr(data,class_values):

    # Initialising best    
    best={
            "name":"temp",
            "split_entropy":999999
         }

    # DataFrame.dtype.to_dict() returns a dictionary having keys as attribute name and value as attribute type 
    for name,dtype in data.dtypes.to_dict().iteritems():
        attr={"name":name,"type":dtype}
        # If data_type is not number, use subEntropyChar
        # Keys returned by subEntropyChar ["split_entropy"]
        if dtype in np.sctypes["others"] :
            attr.update(subEntropyChar(data,class_values, name)) 
        # If data_type is number, use subEntropyFloat
        # Keys returned by subEntropyFloat ["split_entropy","split_value"]
        else:
            attr.update(subEntropyFloat(data,class_values, name))

        if attr["split_entropy"] < best["split_entropy"]:
            best = attr


    best["tree_entropy"] = entropy(class_values)
    best["gain"] = best["tree_entropy"] - best["split_entropy"]

    return best

def set_preference(data,class_values,preference):

    preference = {
        "name":preference,
        "type":data[preference].dtype,
    }

    preference["tree_entropy"] = entropy(class_values.copy())

    if preference["type"] in np.sctypes["others"] :
        preference.update(subEntropyChar(data.copy(),class_values.copy(), preference["name"]))

    else:
        preference.update(subEntropyFloat(data.copy(),class_values.copy(),preference["name"]))

    preference["gain"] = preference["tree_entropy"] - preference["split_entropy"]    

    return preference

# @param
#   kwargs:
#       data        : Panda DataFrame
#       class_label : string if metadata is not None else integer
#       preference  : string if metadata is not None else integer ( Attribute prefered as root )
#       max_height  : integer > 0 
#
#   recursion: interger used to keep track of height
#   @return
#       tree : (type dictionary)
#       {
#           "info" : @node (type : dictionary)
#                attribute keys:["name","type","index","gain","sub_entropy","tree_entropy","gain","height"]
#                optional: ["split_value"]
#
#                @leaf
#                   attribute keys:["class","tree_entropy","height"]
#       }

def test_convert_objects_complex_number():
    for dtype in np.sctypes['complex']:
        arr = np.array(list(1j * np.arange(20, dtype=dtype)), dtype='O')
        assert (arr[0].dtype == np.dtype(dtype))
        result = lib.maybe_convert_objects(arr)
        assert (issubclass(result.dtype.type, np.complexfloating))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [bytes, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [bytes, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)

def test_unsigned_max(self):
        types = np.sctypes['uint']
        for T in types:
            assert_equal(iinfo(T).max, T(-1))

def _clip_type(self, type_group, array_max,
                   clip_min, clip_max, inplace=False,
                   expected_min=None, expected_max=None):
        if expected_min is None:
            expected_min = clip_min
        if expected_max is None:
            expected_max = clip_max

        for T in np.sctypes[type_group]:
            if sys.byteorder == 'little':
                byte_orders = ['=', '>']
            else:
                byte_orders = ['<', '=']

            for byteorder in byte_orders:
                dtype = np.dtype(T).newbyteorder(byteorder)

                x = (np.random.random(1000) * array_max).astype(dtype)
                if inplace:
                    x.clip(clip_min, clip_max, x)
                else:
                    x = x.clip(clip_min, clip_max)
                    byteorder = '='

                if x.dtype.byteorder == '|':
                    byteorder = '|'
                assert_equal(x.dtype.byteorder, byteorder)
                self._check_range(x, expected_min, expected_max)
        return x

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(1000)*100
        mask = x < 40

        for val in [-100, 0, 15]:
            for types in np.sctypes.values():
                for T in types:
                    if T not in unchecked_types:
                        yield self.tst_basic, x.copy().astype(T), T, mask, val

def test_ip_types(self):
        unchecked_types = [str, unicode, np.void, object]

        x = np.random.random(24)*100
        x.shape = 2, 3, 4
        for types in np.sctypes.values():
            for T in types:
                if T not in unchecked_types:
                    yield self.tst_basic, x.copy().astype(T)