python类any()的实例源码

generate.py 文件源码 项目:latplan 作者: guicho271828 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def random_walk_rec(current, trace, length, successor_fn): 
    import numpy.random as random
    if length == 0:
        return current
    else:
        sucs = successor_fn(current)
        first = random.randint(len(sucs))
        now = first

        while True:
            suc = sucs[now]
            try:
                assert not np.any([np.all(np.equal(suc, t)) for t in trace])
                result = random_walk_rec(suc, [*trace, suc], length-1, successor_fn)
                assert result is not None
                return result
            except AssertionError:
                now = (now+1)%len(sucs)
                if now == first:
                    print("B",end="")
                    return None
                else:
                    continue
test_numerics.py 文件源码 项目:npstreams 作者: LaurentRDC 项目源码 文件源码 阅读 28 收藏 0 点赞 0 评论 0
def test_against_numpy(self):
        """ Test iany against numpy.any """
        stream = [np.zeros((8, 16, 2)) for _ in range(11)]
        stream[3][3,0,1] = 1    # so that np.all(axis = None) evaluates to False
        stack = np.stack(stream, axis = -1)

        with self.subTest('axis = None'):
            from_numpy = np.any(stack, axis = None)
            from_stream = last(iany(stream, axis = None))
            self.assertEqual(from_numpy, from_stream)

        for axis in range(stack.ndim):
            with self.subTest('axis = {}'.format(axis)):
                from_numpy = np.any(stack, axis = axis)
                from_stream = last(iany(stream, axis = axis))
                self.assertTrue(np.allclose(from_numpy, from_stream))
report.py 文件源码 项目:cellranger 作者: 10XGenomics 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def _set_barcode_reads_metrics(self, read_type, read_type_set, bc):
        for genome in self.genomes:
            is_read_type = (genome, cr_constants.TRANSCRIPTOME_REGION) in read_type_set
            if is_read_type:
                barcode_reads = self._get_metric_attr(
                    'barcode_reads', genome, cr_constants.TRANSCRIPTOME_REGION, read_type)
                barcode_reads.add(bc)

        # Don't always-report the multi prefix for the barcode_reads metrics
        if self.has_multiple_genomes:
            is_read_type = any([(genome, cr_constants.TRANSCRIPTOME_REGION) in read_type_set for genome in self.genomes])
            if is_read_type:
                multi_barcode_reads = self._get_metric_attr(
                    'barcode_reads', cr_constants.MULTI_REFS_PREFIX,
                    cr_constants.TRANSCRIPTOME_REGION, read_type)
                multi_barcode_reads.add(bc)
ScatterPlotItem.py 文件源码 项目:NeoAnalysis 作者: neoanalysis 项目源码 文件源码 阅读 29 收藏 0 点赞 0 评论 0
def updateSpots(self, dataSet=None):
        if dataSet is None:
            dataSet = self.data

        invalidate = False
        if self.opts['pxMode']:
            mask = np.equal(dataSet['sourceRect'], None)
            if np.any(mask):
                invalidate = True
                opts = self.getSpotOpts(dataSet[mask])
                sourceRect = self.fragmentAtlas.getSymbolCoords(opts)
                dataSet['sourceRect'][mask] = sourceRect

            self.fragmentAtlas.getAtlas() # generate atlas so source widths are available.

            dataSet['width'] = np.array(list(imap(QtCore.QRectF.width, dataSet['sourceRect'])))/2
            dataSet['targetRect'] = None
            self._maxSpotPxWidth = self.fragmentAtlas.max_width
        else:
            self._maxSpotWidth = 0
            self._maxSpotPxWidth = 0
            self.measureSpotSizes(dataSet)

        if invalidate:
            self.invalidate()
ScatterPlotItem.py 文件源码 项目:NeoAnalysis 作者: neoanalysis 项目源码 文件源码 阅读 24 收藏 0 点赞 0 评论 0
def updateSpots(self, dataSet=None):
        if dataSet is None:
            dataSet = self.data

        invalidate = False
        if self.opts['pxMode']:
            mask = np.equal(dataSet['sourceRect'], None)
            if np.any(mask):
                invalidate = True
                opts = self.getSpotOpts(dataSet[mask])
                sourceRect = self.fragmentAtlas.getSymbolCoords(opts)
                dataSet['sourceRect'][mask] = sourceRect

            self.fragmentAtlas.getAtlas() # generate atlas so source widths are available.

            dataSet['width'] = np.array(list(imap(QtCore.QRectF.width, dataSet['sourceRect'])))/2
            dataSet['targetRect'] = None
            self._maxSpotPxWidth = self.fragmentAtlas.max_width
        else:
            self._maxSpotWidth = 0
            self._maxSpotPxWidth = 0
            self.measureSpotSizes(dataSet)

        if invalidate:
            self.invalidate()
test_bidirectional_rnn_encoder.py 文件源码 项目:yoctol-keras-layer-zoo 作者: Yoctol 项目源码 文件源码 阅读 35 收藏 0 点赞 0 评论 0
def test_mask_value(self):
        result = self.model.predict(self.data)
        np.testing.assert_array_almost_equal(
            result[:, 1:, :],
            np.zeros((
                self.data_size,
                self.max_length - 1,
                self.encoding_size
            ))
        )
        np.testing.assert_equal(
            np.any(
                np.not_equal(
                    result[:, 0:1, self.cell_units:],
                    np.zeros((self.data_size, 1, self.cell_units))
                )
            ),
            True
        )
test_mask_to_seq.py 文件源码 项目:yoctol-keras-layer-zoo 作者: Yoctol 项目源码 文件源码 阅读 29 收藏 0 点赞 0 评论 0
def test_image_data_mask(self):
        mask_cache_key = str(id(self.model.input)) + '_' + str(id(None))
        mask_tensor = self.model._output_mask_cache[mask_cache_key]
        mask = mask_tensor.eval(
            session=K.get_session(),
            feed_dict={self.model.input: self.data}
        )
        self.assertTrue(
            np.all(
                mask[:, self.x_start:self.x_end]
            )
        )
        self.assertFalse(
            np.any(
                mask[:, :self.x_start]
            )
        )
        self.assertFalse(
            np.any(
                mask[:, self.x_end:]
            )
        )
test_mask_to_seq.py 文件源码 项目:yoctol-keras-layer-zoo 作者: Yoctol 项目源码 文件源码 阅读 28 收藏 0 点赞 0 评论 0
def test_seq_data_mask(self):
        mask_cache_key = str(id(self.model.input)) + '_' + str(id(None))
        mask_tensor = self.model._output_mask_cache[mask_cache_key]
        mask = mask_tensor.eval(
            session=K.get_session(),
            feed_dict={self.model.input: self.seq_data}
        )
        self.assertTrue(
            np.all(
                mask[:, :self.seq_data_max_length]
            )
        )
        self.assertFalse(
            np.any(
                mask[:, self.seq_data_max_length:]
            )
        )
sleeploader.py 文件源码 项目:AutoSleepScorerDev 作者: skjerns 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def check_for_normalization(self, data_header):

        channels = [c.upper() for c in data_header.ch_names]
        if not data_header.info['sfreq'] == 100 and not self.resample:
            print('WARNING: Data not with 100hz. Use resample=True for resampling')      


#        if not data_header.info['lowpass'] == 50:
#            print('WARNING: lowpass not at 50')
        if (not self.channels['EEG'] in channels) and  not np.any(([ch in channels for ch in self.channels['EEG']])):
            print('WARNING: EEG channel missing')    
        if not self.channels['EMG'] in channels:
            print('WARNING: EMG channel missing')
        if not self.channels['EOG'] in channels:
            print('WARNING: EOG channel missing')


        if self.references['RefEEG'] and not self.references['RefEEG'] in channels:
            print('WARNING: RefEEG channel missing')
        if self.references['RefEMG'] and not self.references['RefEMG'] in channels:
            print('WARNING: RefEMG channel missing')
        if self.references['RefEOG'] and not self.references['RefEOG'] in channels:
            print('WARNING: RefEOG channel missing')
primitives.py 文件源码 项目:autolab_core 作者: BerkeleyAutomation 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def __init__(self, min_pt, max_pt, frame='unspecified'):
        """Initialize a box.

        Parameters
        ----------
        min_pt : :obj:`numpy.ndarray` of float
            The minimum x, y, and (optionally) z points.

        max_pt : :obj:`numpy.ndarray` of float
            The maximum x, y, and (optionally) z points.

        frame : :obj:`str`
            The frame in which this box is placed.

        Raises
        ------
        ValueError
            If max_pt is not strictly larger than min_pt in all dims.
        """
        if np.any((max_pt - min_pt) < 0):
            raise ValueError('Min point must be smaller than max point')
        self._min_pt = min_pt
        self._max_pt = max_pt
        self._frame = frame
points.py 文件源码 项目:autolab_core 作者: BerkeleyAutomation 项目源码 文件源码 阅读 41 收藏 0 点赞 0 评论 0
def _check_valid_data(self, data):
        """Checks that the incoming data is a 3 x #elements ndarray of normal
        vectors.

        Parameters
        ----------
        data : :obj:`numpy.ndarray`
            The data to verify.

        Raises
        ------
        ValueError
            If the data is not of the correct shape or type, or if the vectors
            therein are not normalized.
        """
        if data.dtype.type != np.float32 and data.dtype.type != np.float64:
            raise ValueError('Must initialize normals clouds with a numpy float ndarray')
        if data.shape[0] != 3:
            raise ValueError('Illegal data array passed to normal cloud. Must have 3 coordinates')
        if len(data.shape) > 2:
            raise ValueError('Illegal data array passed to normal cloud. Must have 1 or 2 dimensions')
        if np.any((np.abs(np.linalg.norm(data, axis=0) - 1) > 1e-4) & (np.linalg.norm(data, axis=0) != 0)):
            raise ValueError('Illegal data array passed to normal cloud. Must have norm=1.0 or norm=0.0')
Catastrophe.py 文件源码 项目:supremm 作者: ubccr 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def process(self, nodemeta, timestamp, data, description):

        if self._job.getdata('perf')['active'] != True:
            self._error = ProcessingError.RAW_COUNTER_UNAVAILABLE
            return False

        if len(data[0]) == 0:
            # Ignore datapoints where no data stored
            return True

        if nodemeta.nodename not in self._data:
            self._data[nodemeta.nodename] = {"x": [], "t": []}

        info = self._data[nodemeta.nodename]
        info['x'].append(1.0 * numpy.sum(data[0]))
        info['t'].append(timestamp)

        if len(info['x']) > 1:
            if numpy.any(info['x'][-1] - info['x'][-2] < 0.0):
                self._error = ProcessingError.PMDA_RESTARTED_DURING_JOB
                return False

        return True
UncoreCounters.py 文件源码 项目:supremm 作者: ubccr 项目源码 文件源码 阅读 22 收藏 0 点赞 0 评论 0
def process(self, nodemeta, timestamp, data, description):

        if self._job.getdata('perf')['active'] != True:
            self._error = ProcessingError.RAW_COUNTER_UNAVAILABLE
            return False

        ndata = numpy.array(data)

        if nodemeta.nodename not in self._first:
            self._first[nodemeta.nodename] = ndata
            return True

        if ndata.shape == self._first[nodemeta.nodename].shape:
            self._data[nodemeta.nodename] = numpy.sum(ndata - self._first[nodemeta.nodename])
            if numpy.any(numpy.fabs(self._data[nodemeta.nodename]) != self._data[nodemeta.nodename]):
                self._error = ProcessingError.PMDA_RESTARTED_DURING_JOB
                return False
        else:
            # Perf counters changed during the job
            self._error = ProcessingError.RAW_COUNTER_UNAVAILABLE
            return False

        return True
sph.py 文件源码 项目:sound_field_analysis-py 作者: QULab 项目源码 文件源码 阅读 28 收藏 0 点赞 0 评论 0
def dspneumann(n, kr):
    """Derivative spherical Neumann (Bessel second kind) of order n at kr

    Parameters
    ----------
    n : array_like
       Order
    kr: array_like
       Argument

    Returns
    -------
    Yv' : complex float
       Derivative of spherical Neumann (Bessel second kind)
    """
    n, kr = scalar_broadcast_match(n, kr)
    if _np.any(n < 0) | _np.any(_np.mod(n, 1) != 0) | _np.any(_np.mod(kr, 1) != 0):
        return spneumann(n, kr) * n / kr - spneumann(n + 1, kr)
    else:
        return scy.spherical_yn(n.astype(_np.int), kr.astype(_np.complex), derivative=True)
artificial.py 文件源码 项目:circletracking 作者: caspervdw 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def crop_pad(image, corner, shape):
    ndim = len(corner)
    corner = [int(round(c)) for c in corner]
    shape = [int(round(s)) for s in shape]
    original = image.shape[-ndim:]
    zipped = zip(corner, shape, original)

    if np.any(c < 0 or c + s > o for (c, s, o) in zipped):
        no_padding = [(0, 0)] * (image.ndim - ndim)
        padding = [(max(-c, 0), max(c + s - o, 0)) for (c, s, o) in zipped]
        corner = [c + max(-c, 0) for c in corner]
        image_temp = np.pad(image, no_padding + padding, mode=str('constant'))
    else:
        image_temp = image

    no_crop = [slice(o+1) for o in image.shape[:-ndim]]
    crop = [slice(c, c+s) for (c, s) in zip(corner, shape)]
    return image_temp[no_crop + crop]
masks.py 文件源码 项目:circletracking 作者: caspervdw 项目源码 文件源码 阅读 32 收藏 0 点赞 0 评论 0
def slice_image(pos, image, radius):
    """ Slice a box around a group of features from an image.

    The box is the smallest box that contains all coordinates up to `radius`
    from any coordinate.

    Parameters
    ----------
    image : ndarray
        The image that will be sliced
    pos : iterable
        An iterable (e.g. list or ndarray) that contains the feature positions
    radius : number or tuple of numbers
        Defines the size of the slice. Every pixel that has a distance lower or
        equal to `radius` to a feature position is included.

    Returns
    -------
    tuple of:
    - the sliced image
    - the coordinate of the slice origin (top-left pixel)
    """
    slices, origin = get_slice(pos, image.shape,  radius)
    return image[slices], origin
copula.py 文件源码 项目:mixedvines 作者: asnelt 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def _logcdf(self, samples):
        lower = np.full(2, -np.inf)
        upper = norm.ppf(samples)
        limit_flags = np.zeros(2)
        if upper.shape[0] > 0:

            def func1d(upper1d):
                '''
                Calculates the multivariate normal cumulative distribution
                function of a single sample.
                '''
                return mvn.mvndst(lower, upper1d, limit_flags, self.theta)[1]

            vals = np.apply_along_axis(func1d, -1, upper)
        else:
            vals = np.empty((0, ))
        old_settings = np.seterr(divide='ignore')
        vals = np.log(vals)
        np.seterr(**old_settings)
        vals[np.any(samples == 0.0, axis=1)] = -np.inf
        vals[samples[:, 0] == 1.0] = np.log(samples[samples[:, 0] == 1.0, 1])
        vals[samples[:, 1] == 1.0] = np.log(samples[samples[:, 1] == 1.0, 0])
        return vals
pyPPPETM_new.py 文件源码 项目:Parallel.GAMIT 作者: demiangomez 项目源码 文件源码 阅读 25 收藏 0 点赞 0 评论 0
def eval(self, t):
        # given a time vector t, return the design matrix column vector(s)

        if self.type is None:
            return np.array([])

        hl = np.zeros((t.shape[0],))
        ht = np.zeros((t.shape[0],))

        if self.type in (0,2):
            hl[t >= self.year] = np.log10(1 + (t[t >= self.year] - self.year) / self.T)

        if self.type in (1,2):
            ht[t >= self.year] = 1

        return np.append(ht,hl) if np.any(hl) else ht
puzzle.py 文件源码 项目:latplan 作者: guicho271828 项目源码 文件源码 阅读 29 收藏 0 点赞 0 评论 0
def validate_transitions_cpu_old(transitions, **kwargs):
    pre = np.array(transitions[0])
    suc = np.array(transitions[1])
    base = setting['base']
    width  = pre.shape[1] // base
    height = pre.shape[1] // base
    load(width,height)

    pre_validation = validate_states(pre, **kwargs)
    suc_validation = validate_states(suc, **kwargs)

    results = []
    for pre, suc, pre_validation, suc_validation in zip(pre, suc, pre_validation, suc_validation):

        if pre_validation and suc_validation:
            c = to_configs(np.array([pre, suc]), verbose=False)
            succs = successors(c[0], width, height)
            results.append(np.any(np.all(np.equal(succs, c[1]), axis=1)))
        else:
            results.append(False)

    return results
lightsout_digital.py 文件源码 项目:latplan 作者: guicho271828 项目源码 文件源码 阅读 29 收藏 0 点赞 0 评论 0
def validate_transitions(transitions, check_states=True, **kwargs):
    pre = np.array(transitions[0])
    suc = np.array(transitions[1])

    if check_states:
        pre_validation = validate_states(pre, verbose=False, **kwargs)
        suc_validation = validate_states(suc, verbose=False, **kwargs)

    pre_configs = to_configs(pre, verbose=False, **kwargs)
    suc_configs = to_configs(suc, verbose=False, **kwargs)

    results = []
    if check_states:
        for pre_c, suc_c, pre_validation, suc_validation in zip(pre_configs, suc_configs, pre_validation, suc_validation):

            if pre_validation and suc_validation:
                succs = successors(pre_c)
                results.append(np.any(np.all(np.equal(succs, suc_c), axis=1)))
            else:
                results.append(False)
    else:
        for pre_c, suc_c in zip(pre_configs, suc_configs):
            succs = successors(pre_c)
            results.append(np.any(np.all(np.equal(succs, suc_c), axis=1)))
    return results
transformers.py 文件源码 项目:triage 作者: dssg 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def transform(self, X):
        feature_range = self.feature_range

        X = check_array(X, copy=self.copy, ensure_2d=False, dtype=FLOAT_DTYPES)

        if X.ndim == 1:
            warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)

        if np.any(X > feature_range[1]) or np.any(X < feature_range[0]):
            warnings.warn(
                "You got data that are out of the range: {}"
                .format(feature_range)
            )

        X[X > feature_range[1]] = feature_range[1]
        X[X < feature_range[0]] = feature_range[0]

        return X
polyCrystal.py 文件源码 项目:Graphene 作者: ashivni 项目源码 文件源码 阅读 34 收藏 0 点赞 0 评论 0
def vorEdges(vor, far):
    """
    Given a voronoi tesselation, retuns the set of voronoi edges.
    far is the length of the "infinity" edges
    """
    edges = []
    for simplex in vor.ridge_vertices:
        simplex = numpy.asarray(simplex)
        if numpy.all(simplex >= 0):
            edge = {}
            edge['p1'], edge['p2'] = vor.vertices[simplex, 0], vor.vertices[simplex, 1]
            edge['p1'] = numpy.array([vor.vertices[simplex, 0][0], vor.vertices[simplex, 1][0]])
            edge['p2'] = numpy.array([vor.vertices[simplex, 0][1], vor.vertices[simplex, 1][1]])
            edge['t'] = (edge['p2'] - edge['p1']) / numpy.linalg.norm(edge['p2'] - edge['p1'])
            edges.append(edge)

    ptp_bound = vor.points.ptp(axis=0)
    center = vor.points.mean(axis=0)
    for pointidx, simplex in zip(vor.ridge_points, vor.ridge_vertices):
        simplex = numpy.asarray(simplex)
        if numpy.any(simplex < 0):
            i = simplex[simplex >= 0][0]  # finite end Voronoi vertex

            t = vor.points[pointidx[1]] - vor.points[pointidx[0]]  # tangent
            t /= numpy.linalg.norm(t)
            n = numpy.array([-t[1], t[0]])  # normal

            midpoint = vor.points[pointidx].mean(axis=0)
            direction = numpy.sign(numpy.dot(midpoint - center, n)) * n

            far_point = vor.vertices[i] + direction * ptp_bound.max() * far
            edge = {}
            edge['p1'], edge['p2'] = numpy.array([vor.vertices[i, 0], far_point[0]]), numpy.array(
                [vor.vertices[i, 1], far_point[1]])
            edge['p1'], edge['p2'] = vor.vertices[i, :], far_point
            edge['t'] = (edge['p2'] - edge['p1']) / numpy.linalg.norm(edge['p2'] - edge['p1'])
            edges.append(edge)
    return edges
fromnumeric.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 27 收藏 0 点赞 0 评论 0
def sometrue(a, axis=None, out=None, keepdims=False):
    """
    Check whether some values are true.

    Refer to `any` for full documentation.

    See Also
    --------
    any : equivalent function

    """
    arr = asanyarray(a)

    try:
        return arr.any(axis=axis, out=out, keepdims=keepdims)
    except TypeError:
        return arr.any(axis=axis, out=out)
test_nanfunctions.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 27 收藏 0 点赞 0 评论 0
def test_ddof_too_big(self):
        nanfuncs = [np.nanvar, np.nanstd]
        stdfuncs = [np.var, np.std]
        dsize = [len(d) for d in _rdat]
        for nf, rf in zip(nanfuncs, stdfuncs):
            for ddof in range(5):
                with warnings.catch_warnings(record=True) as w:
                    warnings.simplefilter('always')
                    tgt = [ddof >= d for d in dsize]
                    res = nf(_ndat, axis=1, ddof=ddof)
                    assert_equal(np.isnan(res), tgt)
                    if any(tgt):
                        assert_(len(w) == 1)
                        assert_(issubclass(w[0].category, RuntimeWarning))
                    else:
                        assert_(len(w) == 0)
core.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 30 收藏 0 点赞 0 评论 0
def __iadd__(self, other):
        """
        Add other to self in-place.

        """
        m = getmask(other)
        if self._mask is nomask:
            if m is not nomask and m.any():
                self._mask = make_mask_none(self.shape, self.dtype)
                self._mask += m
        else:
            if m is not nomask:
                self._mask += m
        self._data.__iadd__(np.where(self._mask, self.dtype.type(0),
                                     getdata(other)))
        return self
core.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 36 收藏 0 点赞 0 评论 0
def __idiv__(self, other):
        """
        Divide self by other in-place.

        """
        other_data = getdata(other)
        dom_mask = _DomainSafeDivide().__call__(self._data, other_data)
        other_mask = getmask(other)
        new_mask = mask_or(other_mask, dom_mask)
        # The following 3 lines control the domain filling
        if dom_mask.any():
            (_, fval) = ufunc_fills[np.divide]
            other_data = np.where(dom_mask, fval, other_data)
        self._mask |= new_mask
        self._data.__idiv__(np.where(self._mask, self.dtype.type(1),
                                     other_data))
        return self
core.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def __ifloordiv__(self, other):
        """
        Floor divide self by other in-place.

        """
        other_data = getdata(other)
        dom_mask = _DomainSafeDivide().__call__(self._data, other_data)
        other_mask = getmask(other)
        new_mask = mask_or(other_mask, dom_mask)
        # The following 3 lines control the domain filling
        if dom_mask.any():
            (_, fval) = ufunc_fills[np.floor_divide]
            other_data = np.where(dom_mask, fval, other_data)
        self._mask |= new_mask
        self._data.__ifloordiv__(np.where(self._mask, self.dtype.type(1),
                                          other_data))
        return self
core.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 33 收藏 0 点赞 0 评论 0
def __ipow__(self, other):
        """
        Raise self to the power other, in place.

        """
        other_data = getdata(other)
        other_mask = getmask(other)
        with np.errstate(divide='ignore', invalid='ignore'):
            self._data.__ipow__(np.where(self._mask, self.dtype.type(1),
                                         other_data))
        invalid = np.logical_not(np.isfinite(self._data))
        if invalid.any():
            if self._mask is not nomask:
                self._mask |= invalid
            else:
                self._mask = invalid
            np.copyto(self._data, self.fill_value, where=invalid)
        new_mask = mask_or(other_mask, invalid)
        self._mask = mask_or(self._mask, new_mask)
        return self
test_defmatrix.py 文件源码 项目:radar 作者: amoose136 项目源码 文件源码 阅读 24 收藏 0 点赞 0 评论 0
def test_comparisons(self):
        A = np.arange(100).reshape(10, 10)
        mA = matrix(A)
        mB = matrix(A) + 0.1
        assert_(np.all(mB == A+0.1))
        assert_(np.all(mB == matrix(A+0.1)))
        assert_(not np.any(mB == matrix(A-0.1)))
        assert_(np.all(mA < mB))
        assert_(np.all(mA <= mB))
        assert_(np.all(mA <= mA))
        assert_(not np.any(mA < mA))

        assert_(not np.any(mB < mA))
        assert_(np.all(mB >= mA))
        assert_(np.all(mB >= mB))
        assert_(not np.any(mB > mB))

        assert_(np.all(mA == mA))
        assert_(not np.any(mA == mB))
        assert_(np.all(mB != mA))

        assert_(not np.all(abs(mA) > 0))
        assert_(np.all(abs(mB > 0)))
data_manager.py 文件源码 项目:AutoML5 作者: djajetic 项目源码 文件源码 阅读 36 收藏 0 点赞 0 评论 0
def loadData (self, filename, verbose=True, replace_missing=True):
        ''' Get the data from a text file in one of 3 formats: matrix, sparse, binary_sparse'''
        if verbose:  print("========= Reading " + filename)
        start = time.time()
        if self.use_pickle and os.path.exists (os.path.join (self.tmp_dir, os.path.basename(filename) + ".pickle")):
            with open (os.path.join (self.tmp_dir, os.path.basename(filename) + ".pickle"), "r") as pickle_file:
                vprint (verbose, "Loading pickle file : " + os.path.join(self.tmp_dir, os.path.basename(filename) + ".pickle"))
                return pickle.load(pickle_file)
        if 'format' not in self.info.keys():
            self.getFormatData(filename)
        if 'feat_num' not in self.info.keys():
            self.getNbrFeatures(filename)

        data_func = {'dense':data_io.data, 'sparse':data_io.data_sparse, 'sparse_binary':data_io.data_binary_sparse}

        data = data_func[self.info['format']](filename, self.info['feat_num'])

        # INPORTANT: when we replace missing values we double the number of variables

        if self.info['format']=='dense' and replace_missing and np.any(map(np.isnan,data)):
            vprint (verbose, "Replace missing values by 0 (slow, sorry)")
            data = data_converter.replace_missing(data)
        if self.use_pickle:
            with open (os.path.join (self.tmp_dir, os.path.basename(filename) + ".pickle"), "wb") as pickle_file:
                vprint (verbose, "Saving pickle file : " + os.path.join (self.tmp_dir, os.path.basename(filename) + ".pickle"))
                p = pickle.Pickler(pickle_file) 
                p.fast = True 
                p.dump(data)
        end = time.time()
        if verbose:  print( "[+] Success in %5.2f sec" % (end - start))
        return data


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