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doc_1100
Set the z-axis scale. Parameters value{"linear"} The axis scale type to apply. 3D axes currently only support linear scales; other scales yield nonsensical results. **kwargs Keyword arguments are nominally forwarded to the scale class, but none of them is applicable for linear scales.
doc_1101
Get the hour of the day component of the Period. Returns int The hour as an integer, between 0 and 23. See also Period.second Get the second component of the Period. Period.minute Get the minute component of the Period. Examples >>> p = pd.Period("2018-03-11 13:03:12.050000") >>> p.hour 13 Period l...
doc_1102
See Migration guide for more details. tf.compat.v1.raw_ops.DummySeedGenerator tf.raw_ops.DummySeedGenerator( name=None ) Args name A name for the operation (optional). Returns A Tensor of type resource.
doc_1103
alias of Linear
doc_1104
Return the parent’s process id. When the parent process has exited, on Unix the id returned is the one of the init process (1), on Windows it is still the same id, which may be already reused by another process. Availability: Unix, Windows. Changed in version 3.2: Added support for Windows.
doc_1105
Holds a string containing the greeting sent by the client in its “HELO”.
doc_1106
Fork. Connect the child’s controlling terminal to a pseudo-terminal. Return value is (pid, fd). Note that the child gets pid 0, and the fd is invalid. The parent’s return value is the pid of the child, and fd is a file descriptor connected to the child’s controlling terminal (and also to the child’s standard input and ...
doc_1107
Array interface to get at this Transform's affine matrix.
doc_1108
Length of the network prefix, in bits.
doc_1109
get version number of the SDL_Image library being used get_sdl_image_version() -> None get_sdl_image_version() -> (major, minor, patch) If pygame is built with extended image formats, then this function will return the SDL_Image library's version number as a tuple of 3 integers (major, minor, patch). If not, then it ...
doc_1110
Returns the average of the array elements along given axis. Refer to numpy.mean for full documentation. See also numpy.mean equivalent function
doc_1111
Create a new figure, or activate an existing figure. Parameters numint or str or Figure, optional A unique identifier for the figure. If a figure with that identifier already exists, this figure is made active and returned. An integer refers to the Figure.number attribute, a string refers to the figure label. I...
doc_1112
turtle.fd(distance) Parameters distance – a number (integer or float) Move the turtle forward by the specified distance, in the direction the turtle is headed. >>> turtle.position() (0.00,0.00) >>> turtle.forward(25) >>> turtle.position() (25.00,0.00) >>> turtle.forward(-75) >>> turtle.position() (-50.00,0.00)
doc_1113
This decorator marks a view as being exempt from the protection ensured by the middleware. Example: from django.http import HttpResponse from django.views.decorators.csrf import csrf_exempt @csrf_exempt def my_view(request): return HttpResponse('Hello world')
doc_1114
Update colors from the scalar mappable array, if any. Assign colors to edges and faces based on the array and/or colors that were directly set, as appropriate.
doc_1115
Bases: matplotlib.backend_bases.Event A pick event. This event is fired when the user picks a location on the canvas sufficiently close to an artist that has been made pickable with Artist.set_picker. A PickEvent has a number of special attributes in addition to those defined by the parent Event class. Examples Bind ...
doc_1116
A mixin class that performs template-based response rendering for views that operate upon a single object instance. Requires that the view it is mixed with provides self.object, the object instance that the view is operating on. self.object will usually be, but is not required to be, an instance of a Django model. It m...
doc_1117
Run awaitable objects in the aws iterable concurrently and block until the condition specified by return_when. The aws iterable must not be empty. Returns two sets of Tasks/Futures: (done, pending). Usage: done, pending = await asyncio.wait(aws) timeout (a float or int), if specified, can be used to control the maximu...
doc_1118
Applies element-wise LogSigmoid(xi)=log⁡(11+exp⁡(−xi))\text{LogSigmoid}(x_i) = \log \left(\frac{1}{1 + \exp(-x_i)}\right) See LogSigmoid for more details.
doc_1119
test if a Group contains Sprites has(*sprites) -> bool Return True if the Group contains all of the given sprites. This is similar to using the "in" operator on the Group ("if sprite in group: ..."), which tests if a single Sprite belongs to a Group. Each sprite argument can also be a iterator containing Sprites.
doc_1120
Returns true for each element if the element is a titlecased string and there is at least one character, false otherwise. See also char.istitle
doc_1121
tf.keras.applications.nasnet.NASNetMobile Compat aliases for migration See Migration guide for more details. tf.compat.v1.keras.applications.NASNetMobile, tf.compat.v1.keras.applications.nasnet.NASNetMobile tf.keras.applications.NASNetMobile( input_shape=None, include_top=True, weights='imagenet', input_tenso...
doc_1122
Return the internal pad in points. See set_pad for more details.
doc_1123
returns a vector with the same direction but length 1. normalize() -> Vector3 Returns a new vector that has length equal to 1 and the same direction as self.
doc_1124
rotates a vector by a given angle in radians. rotate_rad(angle, Vector3) -> Vector3 Returns a vector which has the same length as self but is rotated counterclockwise by the given angle in radians around the given axis. New in pygame 2.0.0.
doc_1125
Load “dotenv” files in order of precedence to set environment variables. If an env var is already set it is not overwritten, so earlier files in the list are preferred over later files. This is a no-op if python-dotenv is not installed. Parameters path – Load the file at this location instead of searching. Returns ...
doc_1126
tf.experimental.numpy.vander( x, N=None, increasing=False ) See the NumPy documentation for numpy.vander.
doc_1127
Remove a child node. oldChild must be a child of this node; if not, ValueError is raised. oldChild is returned on success. If oldChild will not be used further, its unlink() method should be called.
doc_1128
Handle a defect found on obj. When the email package calls this method, defect will always be a subclass of Defect. The default implementation checks the raise_on_defect flag. If it is True, defect is raised as an exception. If it is False (the default), obj and defect are passed to register_defect().
doc_1129
See Migration guide for more details. tf.compat.v1.raw_ops.DepthwiseConv2dNative tf.raw_ops.DepthwiseConv2dNative( input, filter, strides, padding, explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1], name=None ) Given an input tensor of shape [batch, in_height, in_width, in_channels] and a filt...
doc_1130
class sklearn.feature_selection.VarianceThreshold(threshold=0.0) [source] Feature selector that removes all low-variance features. This feature selection algorithm looks only at the features (X), not the desired outputs (y), and can thus be used for unsupervised learning. Read more in the User Guide. Parameters t...
doc_1131
show lots of sprites moving around testsprite.main(update_rects = True, use_static = False, use_FastRenderGroup = False, screen_dims = [640, 480], use_alpha = False, flags = 0) -> None Optional keyword arguments: update_rects - use the RenderUpdate sprite group class use_static - include non-moving images use_FastRen...
doc_1132
See Migration guide for more details. tf.compat.v1.raw_ops.ReciprocalGrad tf.raw_ops.ReciprocalGrad( y, dy, name=None ) Specifically, grad = -dy * y*y, where y = 1/x, and dy is the corresponding input gradient. Args y A Tensor. Must be one of the following types: bfloat16, half, float32, float64, comple...
doc_1133
Set the norm limits for image scaling. Parameters vmin, vmaxfloat The limits. The limits may also be passed as a tuple (vmin, vmax) as a single positional argument.
doc_1134
Bases: object A base class for providing timer events, useful for things animations. Backends need to implement a few specific methods in order to use their own timing mechanisms so that the timer events are integrated into their event loops. Subclasses must override the following methods: _timer_start: Backend-spe...
doc_1135
Principal component analysis (PCA). Linear dimensionality reduction using Singular Value Decomposition of the data to project it to a lower dimensional space. The input data is centered but not scaled for each feature before applying the SVD. It uses the LAPACK implementation of the full SVD or a randomized truncated...
doc_1136
Remove sequence from the list of sequences that include this message.
doc_1137
See Migration guide for more details. tf.compat.v1.keras.layers.InputSpec, tf.compat.v1.layers.InputSpec tf.keras.layers.InputSpec( dtype=None, shape=None, ndim=None, max_ndim=None, min_ndim=None, axes=None, allow_last_axis_squeeze=False, name=None ) Layers can expose (if appropriate) an input_spec attribute...
doc_1138
Compute the standard deviation along the specified axis. Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis. Parameters aarray_like Calculate the standard devia...
doc_1139
Count non-NA cells for each column or row. The values None, NaN, NaT, and optionally numpy.inf (depending on pandas.options.mode.use_inf_as_na) are considered NA. Parameters axis:{0 or ‘index’, 1 or ‘columns’}, default 0 If 0 or ‘index’ counts are generated for each column. If 1 or ‘columns’ counts are generate...
doc_1140
See Migration guide for more details. tf.compat.v1.estimator.VocabInfo, tf.compat.v1.train.VocabInfo tf.estimator.VocabInfo( new_vocab, new_vocab_size, num_oov_buckets, old_vocab, old_vocab_size=-1, backup_initializer=None, axis=0 ) See tf.estimator.WarmStartSettings for examples of using VocabInfo to warm-s...
doc_1141
sklearn.metrics.log_loss(y_true, y_pred, *, eps=1e-15, normalize=True, sample_weight=None, labels=None) [source] Log loss, aka logistic loss or cross-entropy loss. This is the loss function used in (multinomial) logistic regression and extensions of it such as neural networks, defined as the negative log-likelihood o...
doc_1142
calculates the Euclidean distance to a given vector. distance_to(Vector3) -> float
doc_1143
Remove an event from the event list -- by default, the last. Note that this does not check that there are events, much like the normal pop method. If no events exist, this will throw an exception.
doc_1144
Optional. This attribute defines the maximum number of URLs included on each page of the sitemap. Its value should not exceed the default value of 50000, which is the upper limit allowed in the Sitemaps protocol.
doc_1145
pygame module to transform surfaces A Surface transform is an operation that moves or resizes the pixels. All these functions take a Surface to operate on and return a new Surface with the results. Some of the transforms are considered destructive. These means every time they are performed they lose pixel data. Co...
doc_1146
lookup_name = 'second'
doc_1147
mimetypes.guess_type(url, strict=True) Guess the type of a file based on its filename, path or URL, given by url. URL can be a string or a path-like object. The return value is a tuple (type, encoding) where type is None if the type can’t be guessed (missing or unknown suffix) or a string of the form 'type/subtype', ...
doc_1148
The maximum resident set size that should be made available to the process.
doc_1149
The degree of the series. New in version 1.5.0. Returns degreeint Degree of the series, one less than the number of coefficients.
doc_1150
Transform dataset. Parameters X{array-like, sparse matrix} of shape (n_samples, n_features) Input data to be transformed. Use dtype=np.float32 for maximum efficiency. Sparse matrices are also supported, use sparse csr_matrix for maximum efficiency. Returns X_transformedsparse matrix of shape (n_samples, n...
doc_1151
os.PRIO_PGRP os.PRIO_USER Parameters for the getpriority() and setpriority() functions. Availability: Unix. New in version 3.3.
doc_1152
Add a colorbar to a plot. Parameters mappable The matplotlib.cm.ScalarMappable (i.e., AxesImage, ContourSet, etc.) described by this colorbar. This argument is mandatory for the Figure.colorbar method but optional for the pyplot.colorbar function, which sets the default to the current image. Note that one can cre...
doc_1153
A method that takes a template_name and yields Origin instances for each possible source. For example, the filesystem loader may receive 'index.html' as a template_name argument. This method would yield origins for the full path of index.html as it appears in each template directory the loader looks at. The method does...
doc_1154
Return a list of URLs, one for each element of the collection. The list contains None for elements without a URL. See Hyperlinks for an example.
doc_1155
Computes Felsenszwalb’s efficient graph based image segmentation. Produces an oversegmentation of a multichannel (i.e. RGB) image using a fast, minimum spanning tree based clustering on the image grid. The parameter scale sets an observation level. Higher scale means less and larger segments. sigma is the diameter of...
doc_1156
Compute the truth value of x1 AND x2 element-wise. Parameters x1, x2array_like Input arrays. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output). outndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If ...
doc_1157
Disable all renegotiation in TLSv1.2 and earlier. Do not send HelloRequest messages, and ignore renegotiation requests via ClientHello. This option is only available with OpenSSL 1.1.0h and later. New in version 3.7.
doc_1158
Extension dtype for string data. New in version 1.0.0. Warning StringDtype is considered experimental. The implementation and parts of the API may change without warning. In particular, StringDtype.na_value may change to no longer be numpy.nan. Parameters storage:{“python”, “pyarrow”}, optional If not given...
doc_1159
os.RTLD_NOW os.RTLD_GLOBAL os.RTLD_LOCAL os.RTLD_NODELETE os.RTLD_NOLOAD os.RTLD_DEEPBIND Flags for use with the setdlopenflags() and getdlopenflags() functions. See the Unix manual page dlopen(3) for what the different flags mean. New in version 3.3.
doc_1160
Set the current value of the ctypes-private copy of the system errno variable in the calling thread to value and return the previous value. Raises an auditing event ctypes.set_errno with argument errno.
doc_1161
An optional boolean argument that determines if concatenated values will be distinct. Defaults to False.
doc_1162
Divides (“unscales”) the optimizer’s gradient tensors by the scale factor. unscale_() is optional, serving cases where you need to modify or inspect gradients between the backward pass(es) and step(). If unscale_() is not called explicitly, gradients will be unscaled automatically during step(). Simple example, using...
doc_1163
tf.device( device_name ) This function specifies the device to be used for ops created/executed in a particular context. Nested contexts will inherit and also create/execute their ops on the specified device. If a specific device is not required, consider not using this function so that a device can be automatical...
doc_1164
Bases: matplotlib.patches.ArrowStyle._Base Wedge(?) shape. Only works with a quadratic Bezier curve. The begin point has a width of the tail_width and the end point has a width of 0. At the middle, the width is shrink_factor*tail_width. Parameters tail_widthfloat, default: 0.3 Width of the tail. shrink_factor...
doc_1165
See Migration guide for more details. tf.compat.v1.ragged.constant tf.ragged.constant( pylist, dtype=None, ragged_rank=None, inner_shape=None, name=None, row_splits_dtype=tf.dtypes.int64 ) Example: tf.ragged.constant([[1, 2], [3], [4, 5, 6]]) <tf.RaggedTensor [[1, 2], [3], [4, 5, 6]]> All scalar values in ...
doc_1166
A decorator that is used to register custom template filter. You can specify a name for the filter, otherwise the function name will be used. Example: @app.template_filter() def reverse(s): return s[::-1] Parameters name (Optional[str]) – the optional name of the filter, otherwise the function name will be used....
doc_1167
Estimate circle model from data using total least squares. Parameters data(N, 2) array N points with (x, y) coordinates, respectively. Returns successbool True, if model estimation succeeds.
doc_1168
tf.compat.v1.layers.max_pooling1d( inputs, pool_size, strides, padding='valid', data_format='channels_last', name=None ) Arguments inputs The tensor over which to pool. Must have rank 3. pool_size An integer or tuple/list of a single integer, representing the size of the pooling window. stri...
doc_1169
sklearn.datasets.load_diabetes(*, return_X_y=False, as_frame=False) [source] Load and return the diabetes dataset (regression). Samples total 442 Dimensionality 10 Features real, -.2 < x < .2 Targets integer 25 - 346 Read more in the User Guide. Parameters return_X_ybool, default=False. If True, retur...
doc_1170
See Migration guide for more details. tf.compat.v1.stop_gradient tf.stop_gradient( input, name=None ) When executed in a graph, this op outputs its input tensor as-is. When building ops to compute gradients, this op prevents the contribution of its inputs to be taken into account. Normally, the gradient generato...
doc_1171
Subtract one Hermite series from another. Returns the difference of two Hermite series c1 - c2. The sequences of coefficients are from lowest order term to highest, i.e., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_2. Parameters c1, c2array_like 1-D arrays of Hermite series coefficients ordered from low to ...
doc_1172
See Migration guide for more details. tf.compat.v1.config.experimental.enable_mlir_graph_optimization tf.config.experimental.enable_mlir_graph_optimization() DO NOT USE, DEV AND TESTING ONLY AT THE MOMENT. Note: MLIR-Based TensorFlow Compiler is under active development and has missing features, please refrain from...
doc_1173
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayPack tf.raw_ops.TensorArrayPack( handle, flow_in, dtype, element_shape=None, name=None ) Args handle A Tensor of type mutable string. flow_in A Tensor of type float32. dtype A tf.DType. element_shape An optional tf.T...
doc_1174
See Migration guide for more details. tf.compat.v1.math.rint, tf.compat.v1.rint tf.math.rint( x, name=None ) If the result is midway between two representable values, the even representable is chosen. For example: rint(-1.5) ==> -2.0 rint(0.5000001) ==> 1.0 rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., ...
doc_1175
Send an IHAVE command. message_id is the id of the message to send to the server (enclosed in '<' and '>'). The data parameter and the return value are the same as for post().
doc_1176
Get parameters for this estimator. Parameters deepbool, default=True If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns paramsdict Parameter names mapped to their values.
doc_1177
Unflattens a tensor dim expanding it to a desired shape. For use with Sequential. dim specifies the dimension of the input tensor to be unflattened, and it can be either int or str when Tensor or NamedTensor is used, respectively. unflattened_size is the new shape of the unflattened dimension of the tensor and it ...
doc_1178
GLOBAL_VARIABLES: the default collection of Variable objects, shared across distributed environment (model variables are subset of these). See tf.compat.v1.global_variables for more details. Commonly, all TRAINABLE_VARIABLES variables will be in MODEL_VARIABLES, and all MODEL_VARIABLES variables will be in GLOBAL_VARIA...
doc_1179
Access a group of rows and columns by label(s) or a boolean array. .loc[] is primarily label based, but may also be used with a boolean array. Allowed inputs are: A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). A list or array of ...
doc_1180
See Migration guide for more details. tf.compat.v1.test.is_built_with_rocm tf.test.is_built_with_rocm()
doc_1181
Return the picking behavior of the artist. The possible values are described in set_picker. See also set_picker, pickable, pick
doc_1182
An object that stores some headers. It has a dict-like interface, but is ordered, can store the same key multiple times, and iterating yields (key, value) pairs instead of only keys. This data structure is useful if you want a nicer way to handle WSGI headers which are stored as tuples in a list. From Werkzeug 0.3 onwa...
doc_1183
Set the alpha value used for blending - not supported on all backends. If alpha=None (the default), the alpha components of the foreground and fill colors will be used to set their respective transparencies (where applicable); otherwise, alpha will override them.
doc_1184
The class to which a class instance belongs.
doc_1185
Split a Bezier segment defined by its control points beta into two separate segments divided at t and return their control points.
doc_1186
Alias for get_facecolor.
doc_1187
See Migration guide for more details. tf.compat.v1.ifft2d, tf.compat.v1.signal.ifft2d, tf.compat.v1.spectral.ifft2d tf.signal.ifft2d( input, name=None ) Computes the inverse 2-dimensional discrete Fourier transform over the inner-most 2 dimensions of input. Args input A Tensor. Must be one of the follow...
doc_1188
Return a ZipInfo object with information about the archive member name. Calling getinfo() for a name not currently contained in the archive will raise a KeyError.
doc_1189
See Migration guide for more details. tf.compat.v1.raw_ops.Conv2DBackpropInput tf.raw_ops.Conv2DBackpropInput( input_sizes, filter, out_backprop, strides, padding, use_cudnn_on_gpu=True, explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1], name=None ) Args input_sizes A Tensor of ty...
doc_1190
class sklearn.gaussian_process.kernels.Matern(length_scale=1.0, length_scale_bounds=1e-05, 100000.0, nu=1.5) [source] Matern kernel. The class of Matern kernels is a generalization of the RBF. It has an additional parameter \(\nu\) which controls the smoothness of the resulting function. The smaller \(\nu\), the less...
doc_1191
Takes an optional file object fp, which is ignored by the base class. Initializes “protected” instance variables _info and _charset which are set by derived classes, as well as _fallback, which is set through add_fallback(). It then calls self._parse(fp) if fp is not None. _parse(fp) No-op in the base class, this m...
doc_1192
Assume the end of the document. That will check well-formedness conditions that can be checked only at the end, invoke handlers, and may clean up resources allocated during parsing.
doc_1193
Open url in a new page (“tab”) of the default browser, if possible, otherwise equivalent to open_new().
doc_1194
Return the round-robin quantum in seconds for the process with PID pid. A pid of 0 means the calling process.
doc_1195
Fit the model to data matrix X and target(s) y. Parameters Xndarray or sparse matrix of shape (n_samples, n_features) The input data. yndarray of shape (n_samples,) or (n_samples, n_outputs) The target values (class labels in classification, real numbers in regression). Returns selfreturns a trained M...
doc_1196
Return whether this path points to the same file as other_path, which can be either a Path object, or a string. The semantics are similar to os.path.samefile() and os.path.samestat(). An OSError can be raised if either file cannot be accessed for some reason. >>> p = Path('spam') >>> q = Path('eggs') >>> p.samefile(q) ...
doc_1197
tf.compat.v1.nn.moments( x, axes, shift=None, name=None, keep_dims=None, keepdims=None ) The mean and variance are calculated by aggregating the contents of x across axes. If x is 1-D and axes = [0] this is just the mean and variance of a vector. Note: shift is currently not used; the true mean is computed and us...
doc_1198
Windows only: Represents a HRESULT value, which contains success or error information for a function or method call.
doc_1199
tf.autodiff.ForwardAccumulator( primals, tangents ) Compare to tf.GradientTape which computes vector-Jacobian products ("VJP"s) using reverse-mode autodiff (backprop). Reverse mode is more attractive when computing gradients of a scalar-valued function with respect to many inputs (e.g. a neural network with many p...