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doc_22000
Associate dialect with name. name must be a string. The dialect can be specified either by passing a sub-class of Dialect, or by fmtparams keyword arguments, or both, with keyword arguments overriding parameters of the dialect. For full details about the dialect and formatting parameters, see section Dialects and Forma...
doc_22001
See Migration guide for more details. tf.compat.v1.raw_ops.Pack tf.raw_ops.Pack( values, axis=0, name=None ) Packs the N tensors in values into a tensor with rank one higher than each tensor in values, by packing them along the axis dimension. Given a list of tensors of shape (A, B, C); if axis == 0 then the out...
doc_22002
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op. Parameters valuesarray The input v...
doc_22003
Bases: object Base tool class. A base tool, only implements trigger method or no method at all. The tool is instantiated by matplotlib.backend_managers.ToolManager. propertycanvas The canvas of the figure affected by this tool, or None. default_keymap=None Keymap to associate with this tool. list[str]: List...
doc_22004
Push the argument onto the token stack.
doc_22005
Perform the command’s actions for label, which will be the string as given on the command line.
doc_22006
Return selected slices of an array along given axis. When working along a given axis, a slice along that axis is returned in output for each index where condition evaluates to True. When working on a 1-D array, compress is equivalent to extract. Parameters condition1-D array of bools Array that selects which en...
doc_22007
Returns self tensor’s offset in the underlying storage in terms of number of storage elements (not bytes). Example: >>> x = torch.tensor([1, 2, 3, 4, 5]) >>> x.storage_offset() 0 >>> x[3:].storage_offset() 3
doc_22008
class sklearn.covariance.MinCovDet(*, store_precision=True, assume_centered=False, support_fraction=None, random_state=None) [source] Minimum Covariance Determinant (MCD): robust estimator of covariance. The Minimum Covariance Determinant covariance estimator is to be applied on Gaussian-distributed data, but could s...
doc_22009
Mouse kidney tissue. This biological tissue on a pre-prepared slide was imaged with confocal fluorescence microscopy (Nikon C1 inverted microscope). Image shape is (16, 512, 512, 3). That is 512x512 pixels in X-Y, 16 image slices in Z, and 3 color channels (emission wavelengths 450nm, 515nm, and 605nm, respectively)....
doc_22010
Alias for get_linestyle.
doc_22011
Pads the input tensor boundaries with zero. For N-dimensional padding, use torch.nn.functional.pad(). Parameters padding (int, tuple) – the size of the padding. If is int, uses the same padding in all boundaries. If a 4-tuple, uses (padding_left\text{padding\_left} , padding_right\text{padding\_right} , padding_top...
doc_22012
tf.compat.v1.metrics.mean_absolute_error( labels, predictions, weights=None, metrics_collections=None, updates_collections=None, name=None ) The mean_absolute_error function creates two local variables, total and count that are used to compute the mean absolute error. This average is weighted by weights, and i...
doc_22013
Copy an element of an array to a standard Python scalar and return it. Parameters *argsArguments (variable number and type) none: in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned. int_type: this argument is ...
doc_22014
shelve.open(filename, flag='c', protocol=None, writeback=False) Open a persistent dictionary. The filename specified is the base filename for the underlying database. As a side-effect, an extension may be added to the filename and more than one file may be created. By default, the underlying database file is opened f...
doc_22015
'blogs.blog': lambda o: "/blogs/%s/" % o.slug, 'news.story': lambda o: "/stories/%s/%s/" % (o.pub_year, o.slug), } The model name used in this setting should be all lowercase, regardless of the case of the actual model class name. ADMINS Default: [] (Empty list) A list of all the people who get code error noti...
doc_22016
bytearray.replace(old, new[, count]) Return a copy of the sequence with all occurrences of subsequence old replaced by new. If the optional argument count is given, only the first count occurrences are replaced. The subsequence to search for and its replacement may be any bytes-like object. Note The bytearray versio...
doc_22017
class collections.abc.ItemsView class collections.abc.KeysView class collections.abc.ValuesView ABCs for mapping, items, keys, and values views.
doc_22018
tf.compat.v1.graph_util.must_run_on_cpu( node, pin_variables_on_cpu=False ) Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.compat.v1.graph_util.must_run_on_cpu Args node The node to be assigned to a device. Could be either an ops.Operation o...
doc_22019
Get the artist's bounding box in display space. The bounding box' width and height are nonnegative. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0. Be careful when using this function, the results will not update if the artist windo...
doc_22020
Associates a value with a specified key. key is an already open key, or one of the predefined HKEY_* constants. sub_key is a string that names the subkey with which the value is associated. type is an integer that specifies the type of the data. Currently this must be REG_SZ, meaning only strings are supported. Use the...
doc_22021
Set the Categorical to be ordered. Parameters inplace:bool, default False Whether or not to set the ordered attribute in-place or return a copy of this categorical with ordered set to True. Returns Categorical or None Ordered Categorical or None if inplace=True.
doc_22022
Convert date_time to an IMAP4 INTERNALDATE representation. The return value is a string in the form: "DD-Mmm-YYYY HH:MM:SS +HHMM" (including double-quotes). The date_time argument can be a number (int or float) representing seconds since epoch (as returned by time.time()), a 9-tuple representing local time an instance ...
doc_22023
Writes a list of lines to the response. Line separators are not added. This method makes an HttpResponse instance a stream-like object.
doc_22024
Returns a list of values, including nulls, concatenated into an array, or default if there are no values. distinct An optional boolean argument that determines if array values will be distinct. Defaults to False. ordering An optional string of a field name (with an optional "-" prefix which indicates descendi...
doc_22025
Modify the filename of a log file when rotating. This is provided so that a custom filename can be provided. The default implementation calls the ‘namer’ attribute of the handler, if it’s callable, passing the default name to it. If the attribute isn’t callable (the default is None), the name is returned unchanged. Pa...
doc_22026
Deserialize an object from a string of JSON. Takes the same arguments as the built-in json.loads(), with some defaults from application configuration. Parameters s (str) – JSON string to deserialize. app (Optional[Flask]) – Use this app’s config instead of the active app context or defaults. kwargs (Any) – Extra ...
doc_22027
Set the offsets for the collection. Parameters offsets(N, 2) or (2,) array-like
doc_22028
axisartist.angle_helper axisartist.axes_divider axisartist.axes_grid axisartist.axes_rgb axisartist.axis_artist The axis_artist module implements custom artists to draw axis elements (axis lines and labels, tick lines and labels, grid lines). axisartist.axisline_style axisartist.axislines Axislines inc...
doc_22029
Bases: object A helper class to implement a renderer that switches between vector and raster drawing. An example may be a PDF writer, where most things are drawn with PDF vector commands, but some very complex objects, such as quad meshes, are rasterised and then output as images. Parameters figurematplotlib.figu...
doc_22030
Approximate feature map for additive chi2 kernel. Uses sampling the fourier transform of the kernel characteristic at regular intervals. Since the kernel that is to be approximated is additive, the components of the input vectors can be treated separately. Each entry in the original space is transformed into 2*sample...
doc_22031
Indicator for whether the date is the first day of a quarter. Returns is_quarter_start:Series or DatetimeIndex The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have the same name. See also quarter Return the quarter of the date. is_quar...
doc_22032
Alias for torch.ne().
doc_22033
Check if we match ‘dtype’. Parameters dtype:object The object to check. Returns bool Notes The default implementation is True if cls.construct_from_string(dtype) is an instance of cls. dtype is an object and is an instance of cls dtype has a dtype attribute, and any of the above conditions is true for ...
doc_22034
Raised when an implicitly defined __setattr__() or __delattr__() is called on a dataclass which was defined with frozen=True. It is a subclass of AttributeError.
doc_22035
Compute the roots of a polynomial. Return the roots (a.k.a. “zeros”) of the polynomial \[p(x) = \sum_i c[i] * x^i.\] Parameters c1-D array_like 1-D array of polynomial coefficients. Returns outndarray Array of the roots of the polynomial. If all the roots are real, then out is also real, otherwise it i...
doc_22036
Match.end([group]) Return the indices of the start and end of the substring matched by group; group defaults to zero (meaning the whole matched substring). Return -1 if group exists but did not contribute to the match. For a match object m, and a group g that did contribute to the match, the substring matched by grou...
doc_22037
The Kullback-Leibler divergence loss measure Kullback-Leibler divergence is a useful distance measure for continuous distributions and is often useful when performing direct regression over the space of (discretely sampled) continuous output distributions. As with NLLLoss, the input given is expected to contain log-p...
doc_22038
Draw streamlines of a vector flow. Parameters x, y1D/2D arrays Evenly spaced strictly increasing arrays to make a grid. If 2D, all rows of x must be equal and all columns of y must be equal; i.e., they must be as if generated by np.meshgrid(x_1d, y_1d). u, v2D arrays x and y-velocities. The number of rows a...
doc_22039
Returns a copy of this storage
doc_22040
>>> serializer = AccountSerializer() >>> print(repr(serializer)) AccountSerializer(): id = IntegerField(label='ID', read_only=True) name = CharField(allow_blank=True, max_length=100, required=False) owner = PrimaryKeyRelatedField(queryset=User.objects.all()) API Reference In order to explain the various ty...
doc_22041
Return if the index has unique values.
doc_22042
Bases: matplotlib.axes._axes.Axes 3D axes object. Parameters figFigure The parent figure. rect(float, float, float, float) The (left, bottom, width, height) axes position. azimfloat, default: -60 Azimuthal viewing angle. elevfloat, default: 30 Elevation viewing angle. sharezAxes3D, optional Othe...
doc_22043
sklearn.utils.assert_all_finite(X, *, allow_nan=False) [source] Throw a ValueError if X contains NaN or infinity. Parameters X{ndarray, sparse matrix} allow_nanbool, default=False
doc_22044
Put an item into the queue without blocking. If no free slot is immediately available, raise QueueFull.
doc_22045
A data structure of registered error handlers, in the format {scope: {code: {class: handler}}}`. The scope key is the name of a blueprint the handlers are active for, or None for all requests. The code key is the HTTP status code for HTTPException, or None for other exceptions. The innermost dictionary maps exception c...
doc_22046
Returns a string representation of the internal graph for the forward method. This graph will be preprocessed to inline all function and method calls. See Interpreting Graphs for details.
doc_22047
Return the SymmetricalLogTransform associated with this scale.
doc_22048
CAN_BCM_* CAN_BCM, in the CAN protocol family, is the broadcast manager (BCM) protocol. Broadcast manager constants, documented in the Linux documentation, are also defined in the socket module. Availability: Linux >= 2.6.25. Note The CAN_BCM_CAN_FD_FRAME flag is only available on Linux >= 4.8. New in version 3.4.
doc_22049
Roll provided date forward to next offset only if not on offset. Returns TimeStamp Rolled timestamp if not on offset, otherwise unchanged timestamp.
doc_22050
This is similar to urlparse(), but does not split the params from the URL. This should generally be used instead of urlparse() if the more recent URL syntax allowing parameters to be applied to each segment of the path portion of the URL (see RFC 2396) is wanted. A separate function is needed to separate the path segme...
doc_22051
Append the callable hook to the list of active auditing hooks for the current (sub)interpreter. When an auditing event is raised through the sys.audit() function, each hook will be called in the order it was added with the event name and the tuple of arguments. Native hooks added by PySys_AddAuditHook() are called firs...
doc_22052
Return a sorted copy of the index. Return a sorted copy of the index, and optionally return the indices that sorted the index itself. Parameters return_indexer:bool, default False Should the indices that would sort the index be returned. ascending:bool, default True Should the index values be sorted in an a...
doc_22053
class sklearn.covariance.OAS(*, store_precision=True, assume_centered=False) [source] Oracle Approximating Shrinkage Estimator Read more in the User Guide. OAS is a particular form of shrinkage described in “Shrinkage Algorithms for MMSE Covariance Estimation” Chen et al., IEEE Trans. on Sign. Proc., Volume 58, Issue...
doc_22054
Reads and returns the response body, or up to the next amt bytes.
doc_22055
tf.experimental.numpy.compress( condition, a, axis=None ) Unsupported arguments: out. See the NumPy documentation for numpy.compress.
doc_22056
Show a Region Adjacency Graph on an image. Given a labelled image and its corresponding RAG, show the nodes and edges of the RAG on the image with the specified colors. Edges are displayed between the centroid of the 2 adjacent regions in the image. Parameters labelsndarray, shape (M, N) The labelled image. r...
doc_22057
Required. 100 characters or fewer. Example: 'can_vote'.
doc_22058
Resets the starting point in tracking maximum GPU memory occupied by tensors for a given device. See max_memory_allocated() for details. Parameters device (torch.device or int, optional) – selected device. Returns statistic for the current device, given by current_device(), if device is None (default). Warning T...
doc_22059
Compute the per-sample average log-likelihood of the given data X. Parameters Xarray-like of shape (n_samples, n_dimensions) List of n_features-dimensional data points. Each row corresponds to a single data point. Returns log_likelihoodfloat Log likelihood of the Gaussian mixture given X.
doc_22060
Set the parameters of this kernel. The method works on simple kernels as well as on nested kernels. The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Returns self
doc_22061
""" May be applied as a `default=...` value on a serializer field. Returns the current user. """ requires_context = True def __call__(self, serializer_field): return serializer_field.context['request'].user When serializing the instance, default will be used if the object attribute or ...
doc_22062
See Migration guide for more details. tf.compat.v1.math.segment_max, tf.compat.v1.segment_max tf.math.segment_max( data, segment_ids, name=None ) Read the section on segmentation for an explanation of segments. Computes a tensor such that \(output_i = \max_j(data_j)\) where max is over j such that segment_ids[j]...
doc_22063
Returns a new tensor with the arctangent of the elements of input. outi=tan⁡−1(inputi)\text{out}_{i} = \tan^{-1}(\text{input}_{i}) Parameters input (Tensor) – the input tensor. Keyword Arguments out (Tensor, optional) – the output tensor. Example: >>> a = torch.randn(4) >>> a tensor([ 0.2341, 0.2539, -0.6256,...
doc_22064
Incrementally fit the model to data. Fit a separate model for each output variable. Parameters X{array-like, sparse matrix} of shape (n_samples, n_features) Data. y{array-like, sparse matrix} of shape (n_samples, n_outputs) Multi-output targets. classeslist of ndarray of shape (n_outputs,) Each array is...
doc_22065
See Migration guide for more details. tf.compat.v1.raw_ops.Qr tf.raw_ops.Qr( input, full_matrices=False, name=None ) Computes the QR decomposition of each inner matrix in tensor such that tensor[..., :, :] = q[..., :, :] * r[..., :,:]) Currently, the gradient for the QR decomposition is well-defined only when th...
doc_22066
Set the snapping behavior. Snapping aligns positions with the pixel grid, which results in clearer images. For example, if a black line of 1px width was defined at a position in between two pixels, the resulting image would contain the interpolated value of that line in the pixel grid, which would be a grey value on ...
doc_22067
Very Deep Convolutional Networks for Large-Scale Image Recognition (ICLR 2015) Functions VGG16(...): Instantiates the VGG16 model. decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_input(...): Preprocesses a tensor or Numpy array encoding a batch of images.
doc_22068
See Migration guide for more details. tf.compat.v1.raw_ops.BlockLSTMGrad tf.raw_ops.BlockLSTMGrad( seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad, use_peephole, name=None ) This implementation is to be used in conjunction of LSTMBlock. Args seq_len_max ...
doc_22069
Normalized Mutual Information between two clusterings. Normalized Mutual Information (NMI) is a normalization of the Mutual Information (MI) score to scale the results between 0 (no mutual information) and 1 (perfect correlation). In this function, mutual information is normalized by some generalized mean of H(labels...
doc_22070
Return the offsets for the collection.
doc_22071
Bases: matplotlib.transforms.Affine2DBase BboxTransformTo is a transformation that linearly transforms points from the unit bounding box to a given Bbox. Create a new BboxTransformTo that linearly transforms points from the unit bounding box to boxout. __init__(boxout, **kwargs)[source] Create a new BboxTransform...
doc_22072
Configure the ScalarFormatter used by default for linear axes. If a parameter is not set, the corresponding property of the formatter is left unchanged. Parameters axis{'x', 'y', 'both'}, default: 'both' The axis to configure. Only major ticks are affected. style{'sci', 'scientific', 'plain'} Whether to use...
doc_22073
Define the picking behavior of the artist. Parameters pickerNone or bool or float or callable This can be one of the following: None: Picking is disabled for this artist (default). A boolean: If True then picking will be enabled and the artist will fire a pick event if the mouse event is over the artist. A fl...
doc_22074
The tuple of base classes of a class object.
doc_22075
Computes the log-likelihood of a Gaussian data set with self.covariance_ as an estimator of its covariance matrix. Parameters X_testarray-like of shape (n_samples, n_features) Test data of which we compute the likelihood, where n_samples is the number of samples and n_features is the number of features. X_test ...
doc_22076
Can be passed to the stdin, stdout or stderr parameters. If PIPE is passed to stdin argument, the Process.stdin attribute will point to a StreamWriter instance. If PIPE is passed to stdout or stderr arguments, the Process.stdout and Process.stderr attributes will point to StreamReader instances.
doc_22077
tf.experimental.numpy.uint64( *args, **kwargs ) Character code: 'L'. Canonical name: np.uint. Alias on this platform: np.uint64: 64-bit unsigned integer (0 to 18446744073709551615). Alias on this platform: np.uintp: Unsigned integer large enough to fit pointer, compatible with C uintptr_t. Methods all all() Not ...
doc_22078
tf.experimental.numpy.real( val ) See the NumPy documentation for numpy.real.
doc_22079
Make an iterator that returns consecutive keys and groups from the iterable. The key is a function computing a key value for each element. If not specified or is None, key defaults to an identity function and returns the element unchanged. Generally, the iterable needs to already be sorted on the same key function. The...
doc_22080
BitGenerator for the PCG-64 pseudo-random number generator. Parameters seed{None, int, array_like[ints], SeedSequence}, optional A seed to initialize the BitGenerator. If None, then fresh, unpredictable entropy will be pulled from the OS. If an int or array_like[ints] is passed, then it will be passed to SeedSe...
doc_22081
Evaluate an HermiteE series at points x. If c is of length n + 1, this function returns the value: \[p(x) = c_0 * He_0(x) + c_1 * He_1(x) + ... + c_n * He_n(x)\] The parameter x is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either x or its elements mus...
doc_22082
Sort an array in-place. Refer to numpy.sort for full documentation. Parameters axisint, optional Axis along which to sort. Default is -1, which means sort along the last axis. kind{‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional Sorting algorithm. The default is ‘quicksort’. Note that both ‘stable...
doc_22083
Alternatively, a __reduce_ex__() method may be defined. The only difference is this method should take a single integer argument, the protocol version. When defined, pickle will prefer it over the __reduce__() method. In addition, __reduce__() automatically becomes a synonym for the extended version. The main use for t...
doc_22084
Load a multi-img.
doc_22085
Return a string representation of data. Note This method is intended to be overridden by artist subclasses. As an end-user of Matplotlib you will most likely not call this method yourself. The default implementation converts ints and floats and arrays of ints and floats into a comma-separated string enclosed in squ...
doc_22086
Open a new pseudo-terminal pair, using os.openpty() if possible, or emulation code for generic Unix systems. Return a pair of file descriptors (master, slave), for the master and the slave end, respectively.
doc_22087
Send a STARTTLS command. The ssl_context argument is optional and should be a ssl.SSLContext object. This will enable encryption on the IMAP connection. Please read Security considerations for best practices. New in version 3.2. Changed in version 3.4: The method now supports hostname check with ssl.SSLContext.check...
doc_22088
If true, request that the CookieJar instance downgrade RFC 2109 cookies (ie. cookies received in a Set-Cookie header with a version cookie-attribute of 1) to Netscape cookies by setting the version attribute of the Cookie instance to 0. The default value is None, in which case RFC 2109 cookies are downgraded if and onl...
doc_22089
Draw samples from a Beta distribution. The Beta distribution is a special case of the Dirichlet distribution, and is related to the Gamma distribution. It has the probability distribution function \[f(x; a,b) = \frac{1}{B(\alpha, \beta)} x^{\alpha - 1} (1 - x)^{\beta - 1},\] where the normalization, B, is the beta f...
doc_22090
Create an AppContext. Use as a with block to push the context, which will make current_app point at this application. An application context is automatically pushed by RequestContext.push() when handling a request, and when running a CLI command. Use this to manually create a context outside of these situations. with a...
doc_22091
Initializes the handler with a buffer of the specified capacity. Here, capacity means the number of logging records buffered. emit(record) Append the record to the buffer. If shouldFlush() returns true, call flush() to process the buffer. flush() You can override this to implement custom flushing behavior. Th...
doc_22092
See Migration guide for more details. tf.compat.v1.raw_ops.AdjustContrastv2 tf.raw_ops.AdjustContrastv2( images, contrast_factor, name=None ) images is a tensor of at least 3 dimensions. The last 3 dimensions are interpreted as [height, width, channels]. The other dimensions only represent a collection of images...
doc_22093
alias of matplotlib.backend_tools.ToolCopyToClipboardBase
doc_22094
See Migration guide for more details. tf.compat.v1.signal.rfft2d, tf.compat.v1.spectral.rfft2d tf.signal.rfft2d( input_tensor, fft_length=None, name=None ) Computes the 2-dimensional discrete Fourier transform of a real-valued signal over the inner-most 2 dimensions of input. Since the DFT of a real signal is He...
doc_22095
Set the alpha value used for blending - not supported on all backends. Parameters alphascalar or None alpha must be within the 0-1 range, inclusive.
doc_22096
Add a new record to the Feature table, using the values id, parent.id, title, desc, display, level, directory, and attributes. The resulting feature object can be passed to the start_component() method of Directory. set_current() Make this feature the current feature of msilib. New components are automatically adde...
doc_22097
Return a list of the values. These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns list See also numpy.ndarray.tolist Return the array as an a.ndim-levels deep nested list of Python scalars.
doc_22098
Sets the seed for generating random numbers. Returns a torch.Generator object. Parameters seed (int) – The desired seed. Value must be within the inclusive range [-0x8000_0000_0000_0000, 0xffff_ffff_ffff_ffff]. Otherwise, a RuntimeError is raised. Negative inputs are remapped to positive values with the formula 0xf...
doc_22099
Return a new array of given shape and type, filled with ones. Parameters shapeint or sequence of ints Shape of the new array, e.g., (2, 3) or 2. dtypedata-type, optional The desired data-type for the array, e.g., numpy.int8. Default is numpy.float64. order{‘C’, ‘F’}, optional, default: C Whether to stor...