_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_15700 |
Return the Blackman window. The Blackman window is a taper formed by using the first three terms of a summation of cosines. It was designed to have close to the minimal leakage possible. It is close to optimal, only slightly worse than a Kaiser window. Parameters
Mint
Number of points in the output window. If z... | |
doc_15701 | Renders a template from the template folder with the given context. Parameters
template_name_or_list (Union[str, List[str]]) – the name of the template to be rendered, or an iterable with template names the first one existing will be rendered
context (Any) – the variables that should be available in the context of... | |
doc_15702 | A string representing the HTTP method used in the request. This is guaranteed to be uppercase. For example: if request.method == 'GET':
do_something()
elif request.method == 'POST':
do_something_else() | |
doc_15703 | URL decode a single string with the given charset and decode “+” to whitespace. Per default encoding errors are ignored. If you want a different behavior you can set errors to 'replace' or 'strict'. Parameters
s (Union[str, bytes]) – The string to unquote.
charset (str) – the charset of the query string. If set to... | |
doc_15704 | Change the owner and group id of path to the numeric uid and gid. To leave one of the ids unchanged, set it to -1. This function can support specifying a file descriptor, paths relative to directory descriptors and not following symlinks. See shutil.chown() for a higher-level function that accepts names in addition to ... | |
doc_15705 |
Broadcast an array to a new shape. Parameters
arrayarray_like
The array to broadcast.
shapetuple or int
The shape of the desired array. A single integer i is interpreted as (i,).
subokbool, optional
If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a bas... | |
doc_15706 |
Set the semi-major (a) and semi-minor radii (b) of the annulus. Parameters
rfloat or (float, float)
The radius, or semi-axes: If float: radius of the outer circle. If two floats: semi-major and -minor axes of outer ellipse. | |
doc_15707 | Return the size of the terminal window as (columns, lines), tuple of type terminal_size. The optional argument fd (default STDOUT_FILENO, or standard output) specifies which file descriptor should be queried. If the file descriptor is not connected to a terminal, an OSError is raised. shutil.get_terminal_size() is the ... | |
doc_15708 | alias of flask.sessions.SecureCookieSession | |
doc_15709 | method to control sprite behavior update(*args, **kwargs) -> None The default implementation of this method does nothing; it's just a convenient "hook" that you can override. This method is called by Group.update() with whatever arguments you give it. There is no need to use this method if not using the convenience m... | |
doc_15710 |
Bases: matplotlib.widgets.Widget A tool to adjust the subplot params of a matplotlib.figure.Figure. Parameters
targetfigFigure
The figure instance to adjust.
toolfigFigure
The figure instance to embed the subplot tool into. | |
doc_15711 | save a png/jpg image to file (or file-like object) save_extended(Surface, filename) -> None save_extended(Surface, fileobj, namehint="") -> None This will save your Surface as either a PNG or JPEG image. Incase the image is being saved to a file-like object, this function uses the namehint argument to determine the f... | |
doc_15712 | Set the number of channels. | |
doc_15713 |
Return the coefficient of determination \(R^2\) of the prediction. The coefficient \(R^2\) is defined as \((1 - \frac{u}{v})\), where \(u\) is the residual sum of squares ((y_true - y_pred)
** 2).sum() and \(v\) is the total sum of squares ((y_true -
y_true.mean()) ** 2).sum(). The best possible score is 1.0 and it c... | |
doc_15714 | Create an EnvBuilder with the given keyword arguments, and call its create() method with the env_dir argument. New in version 3.3. Changed in version 3.4: Added the with_pip parameter Changed in version 3.6: Added the prompt parameter | |
doc_15715 | Call open() with method set to PUT. Parameters
args (Any) –
kw (Any) – Return type
werkzeug.test.TestResponse | |
doc_15716 | Return a m-column calendar for an entire year as a multi-line string. Optional parameters w, l, and c are for date column width, lines per week, and number of spaces between month columns, respectively. Depends on the first weekday as specified in the constructor or set by the setfirstweekday() method. The earliest yea... | |
doc_15717 | self.float() is equivalent to self.to(torch.float32). See to(). Parameters
memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format. | |
doc_15718 |
Return the Bartlett window. The Bartlett window is very similar to a triangular window, except that the end points are at zero. It is often used in signal processing for tapering a signal, without generating too much ripple in the frequency domain. Parameters
Mint
Number of points in the output window. If zero ... | |
doc_15719 |
Check whether the provided array or dtype is of the timedelta64[ns] dtype. This is a very specific dtype, so generic ones like np.timedelta64 will return False if passed into this function. Parameters
arr_or_dtype:array-like or dtype
The array or dtype to check. Returns
boolean
Whether or not the array or... | |
doc_15720 | Returns an empty set. | |
doc_15721 |
Draw a series of Gouraud triangles. Parameters
points(N, 3, 2) array-like
Array of N (x, y) points for the triangles.
colors(N, 3, 4) array-like
Array of N RGBA colors for each point of the triangles.
transformmatplotlib.transforms.Transform
An affine transform to apply to the points. | |
doc_15722 |
Compute the pruning path during Minimal Cost-Complexity Pruning. See Minimal Cost-Complexity Pruning for details on the pruning process. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The training input samples. Internally, it will be converted to dtype=np.float32 and if a sparse matri... | |
doc_15723 |
Microscopy image of dermis and epidermis (skin layers). Hematoxylin and eosin stained slide at 10x of normal epidermis and dermis with a benign intradermal nevus. Returns
skin(960, 1280, 3) RGB image of uint8
Notes This image requires an Internet connection the first time it is called, and to have the pooch p... | |
doc_15724 | class ast.Nonlocal(names)
global and nonlocal statements. names is a list of raw strings. >>> print(ast.dump(ast.parse('global x,y,z'), indent=4))
Module(
body=[
Global(
names=[
'x',
'y',
'z'])],
type_ignores=[])
>>> print(ast.dump(ast.parse... | |
doc_15725 |
Get the hatch linewidth. | |
doc_15726 | tf.experimental.numpy.float32(
*args, **kwargs
)
Character code: 'f'. Canonical name: np.single. Alias on this platform: np.float32: 32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa. Methods all
all()
Not implemented (virtual attribute) Class generic exists solely to deriv... | |
doc_15727 |
The module records the running histogram of tensor values along with min/max values. calculate_qparams will calculate scale and zero_point. Parameters
bins – Number of bins to use for the histogram
upsample_rate – Factor by which the histograms are upsampled, this is used to interpolate histograms with varying r... | |
doc_15728 | Return the IEEE 754-style remainder of x with respect to y. For finite x and finite nonzero y, this is the difference x - n*y, where n is the closest integer to the exact value of the quotient x /
y. If x / y is exactly halfway between two consecutive integers, the nearest even integer is used for n. The remainder r = ... | |
doc_15729 | sklearn.get_config() [source]
Retrieve current values for configuration set by set_config Returns
configdict
Keys are parameter names that can be passed to set_config. See also
config_context
Context manager for global scikit-learn configuration.
set_config
Set global scikit-learn configuration. | |
doc_15730 | moves the rectangle inside another, in place clamp_ip(Rect) -> None Same as the Rect.clamp() method, but operates in place. | |
doc_15731 |
Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. Parameters
**paramsdict
Estimator parameters. Returns... | |
doc_15732 | See torch.addcmul() | |
doc_15733 | See torch.take() | |
doc_15734 |
Add a callback function that will be called whenever one of the Artist's properties changes. Parameters
funccallable
The callback function. It must have the signature: def func(artist: Artist) -> Any
where artist is the calling Artist. Return values may exist but are ignored. Returns
int
The observer id ... | |
doc_15735 | Return the delivery date of the message as a floating-point number representing seconds since the epoch. | |
doc_15736 | Transforms this raster to a different spatial reference system (srs), which may be a SpatialReference object, or any other input accepted by SpatialReference (including spatial reference WKT and PROJ strings, or an integer SRID). It calculates the bounds and scale of the current raster in the new spatial reference syst... | |
doc_15737 | Exception to be raised when a test fails. This is deprecated in favor of unittest-based tests and unittest.TestCase’s assertion methods. | |
doc_15738 |
Add one or more events at the specified positions. | |
doc_15739 | Bases: skimage.graph._mcp.MCP Connect source points using the distance-weighted minimum cost function. A front is grown from each seed point simultaneously, while the origin of the front is tracked as well. When two fronts meet, create_connection() is called. This method must be overloaded to deal with the found edges ... | |
doc_15740 | The size, in bytes, of the uploaded file. | |
doc_15741 |
Draw the Artist (and its children) using the given renderer. This has no effect if the artist is not visible (Artist.get_visible returns False). Parameters
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses. | |
doc_15742 |
Reduce a mask to nomask when possible. Parameters
None
Returns
None
Examples >>> x = np.ma.array([[1,2 ], [3, 4]], mask=[0]*4)
>>> x.mask
array([[False, False],
[False, False]])
>>> x.shrink_mask()
masked_array(
data=[[1, 2],
[3, 4]],
mask=False,
fill_value=999999)
>>> x.mask
False | |
doc_15743 |
Computes the squared Mahalanobis distances of given observations. Parameters
Xarray-like of shape (n_samples, n_features)
The observations, the Mahalanobis distances of the which we compute. Observations are assumed to be drawn from the same distribution than the data used in fit. Returns
distndarray of s... | |
doc_15744 | draw all sprites in the right order onto the passed surface. draw(surface) -> Rect_list | |
doc_15745 | Moves all model parameters and buffers to the GPU. This also makes associated parameters and buffers different objects. So it should be called before constructing optimizer if the module will live on GPU while being optimized. Parameters
device (int, optional) – if specified, all parameters will be copied to that dev... | |
doc_15746 | if self.request.version == 'v1':
return AccountSerializerVersion1
return AccountSerializer
Reversing URLs for versioned APIs The reverse function included by REST framework ties in with the versioning scheme. You need to make sure to include the current request as a keyword argument, like so. from rest... | |
doc_15747 | tf.compat.v1.data.Dataset()
A Dataset can be used to represent an input pipeline as a collection of elements and a "logical plan" of transformations that act on those elements.
Args
variant_tensor A DT_VARIANT tensor that represents the dataset.
Attributes
element_spec The type specification of an... | |
doc_15748 | '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_15749 |
Group DataFrame using a mapper or by a Series of columns. A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and compute operations on these groups. Parameters
by:mapping, function, label, or list o... | |
doc_15750 | See Migration guide for more details. tf.compat.v1.raw_ops.ScatterDiv
tf.raw_ops.ScatterDiv(
ref, indices, updates, use_locking=False, name=None
)
This operation computes # Scalar indices
ref[indices, ...] /= updates[...]
# Vector indices (for each i)
ref[indices[i], ...] /= updates[i, ...]
# High rank indices... | |
doc_15751 |
Set whether the legend box patch is drawn. Parameters
bbool | |
doc_15752 | Sequence containing all the type objects for proxies. This can make it simpler to test if an object is a proxy without being dependent on naming both proxy types. | |
doc_15753 |
Return the coefficient of determination \(R^2\) of the prediction. The coefficient \(R^2\) is defined as \((1 - \frac{u}{v})\), where \(u\) is the residual sum of squares ((y_true - y_pred)
** 2).sum() and \(v\) is the total sum of squares ((y_true -
y_true.mean()) ** 2).sum(). The best possible score is 1.0 and it c... | |
doc_15754 |
Return a list of the names of the subplot parameters explicitly set in the GridSpec. This is a subset of the attributes of SubplotParams. | |
doc_15755 |
Check if the object is a number. Returns True when the object is a number, and False if is not. Parameters
obj:any type
The object to check if is a number. Returns
is_number:bool
Whether obj is a number or not. See also api.types.is_integer
Checks a subgroup of numbers. Examples
>>> from pand... | |
doc_15756 |
Get the transformation used for drawing y-axis labels, ticks and gridlines. The x-direction is in axis coordinates and the y-direction is in data coordinates. Note This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements i... | |
doc_15757 |
Plot y versus x as lines and/or markers. Call signatures: plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
The coordinates of the points or line nodes are given by x, y. The optional parameter fmt is a convenient way for defining basic formatting like color, marker and... | |
doc_15758 | Returns True if and only if all elements are closed. | |
doc_15759 | tf.reduce_max
tf.math.reduce_max(
input_tensor, axis=None, keepdims=False, name=None
)
Reduces input_tensor along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each of the entries in axis, which must be unique. If keepdims is true, the reduced dimensions are re... | |
doc_15760 | See Migration guide for more details. tf.compat.v1.app.flags.DEFINE_flag
tf.compat.v1.flags.DEFINE_flag(
flag, flag_values=_flagvalues.FLAGS, module_name=None
)
By default, the global FLAGS 'FlagValue' object is used. Typical users will use one of the more specialized DEFINE_xxx functions, such as DEFINE_string ... | |
doc_15761 |
Theil-Sen Estimator: robust multivariate regression model. The algorithm calculates least square solutions on subsets with size n_subsamples of the samples in X. Any value of n_subsamples between the number of features and samples leads to an estimator with a compromise between robustness and efficiency. Since the nu... | |
doc_15762 | See Migration guide for more details. tf.compat.v1.data.experimental.get_structure
tf.data.experimental.get_structure(
dataset_or_iterator
)
Args
dataset_or_iterator A tf.data.Dataset or an tf.data.Iterator.
Returns A nested structure of tf.TypeSpec objects matching the structure of an element... | |
doc_15763 | tf.compat.v1.nn.separable_conv2d(
input, depthwise_filter, pointwise_filter, strides, padding, rate=None,
name=None, data_format=None, dilations=None
)
Performs a depthwise convolution that acts separately on channels followed by a pointwise convolution that mixes channels. Note that this is separability betwe... | |
doc_15764 | tf.experimental.numpy.meshgrid(
*xi, **kwargs
)
Unsupported arguments: copy, sparse, indexing. This currently requires copy=True and sparse=False. See the NumPy documentation for numpy.meshgrid. | |
doc_15765 |
Return the visibility. | |
doc_15766 | Method called to prepare the test fixture. This is called immediately before calling the test method; other than AssertionError or SkipTest, any exception raised by this method will be considered an error rather than a test failure. The default implementation does nothing. | |
doc_15767 | See Migration guide for more details. tf.compat.v1.keras.preprocessing.image.save_img
tf.keras.preprocessing.image.save_img(
path, x, data_format=None, file_format=None, scale=True, **kwargs
)
Arguments
path Path or file object.
x Numpy array.
data_format Image data format, either "channels_... | |
doc_15768 | The OS name, if it could be parsed from the string. | |
doc_15769 | A named tuple that holds information about Python’s internal representation of integers. The attributes are read only.
Attribute Explanation
bits_per_digit number of bits held in each digit. Python integers are stored internally in base 2**int_info.bits_per_digit
sizeof_digit size in bytes of the C type used to... | |
doc_15770 |
Hook method for deconstructing the class fixture after running all tests in the class. | |
doc_15771 |
Set the sizes of each member of the collection. Parameters
sizesndarray or None
The size to set for each element of the collection. The value is the 'area' of the element.
dpifloat, default: 72
The dpi of the canvas. | |
doc_15772 | Equivalent to put(obj, False). | |
doc_15773 |
Set whether to use offset notation. When formatting a set numbers whose value is large compared to their range, the formatter can separate an additive constant. This can shorten the formatted numbers so that they are less likely to overlap when drawn on an axis. Parameters
valbool or float
If False, do not use... | |
doc_15774 | Binds the app context to the current context. Return type
None | |
doc_15775 |
Binarize data (set feature values to 0 or 1) according to a threshold. Values greater than the threshold map to 1, while values less than or equal to the threshold map to 0. With the default threshold of 0, only positive values map to 1. Binarization is a common operation on text count data where the analyst can deci... | |
doc_15776 |
Update the theta position of the radius labels. Parameters
valuenumber
The angular position of the radius labels in degrees. | |
doc_15777 | See Migration guide for more details. tf.compat.v1.raw_ops.AssignAdd
tf.raw_ops.AssignAdd(
ref, value, use_locking=False, name=None
)
This operation outputs "ref" after the update is done. This makes it easier to chain operations that need to use the reset value.
Args
ref A mutable Tensor. Must be one o... | |
doc_15778 | See Migration guide for more details. tf.compat.v1.image.random_crop, tf.compat.v1.random_crop
tf.image.random_crop(
value, size, seed=None, name=None
)
Slices a shape size portion out of value at a uniformly chosen offset. Requires value.shape >= size. If a dimension should not be cropped, pass the full size of... | |
doc_15779 | See Migration guide for more details. tf.compat.v1.math.scalar_mul
tf.compat.v1.scalar_mul(
scalar, x, name=None
)
Intended for use in gradient code which might deal with IndexedSlices objects, which are easy to multiply by a scalar but more expensive to multiply with arbitrary tensors.
Args
scalar A 0-... | |
doc_15780 |
Draw samples from a Weibull distribution. Draw samples from a 1-parameter Weibull distribution with the given shape parameter a. \[X = (-ln(U))^{1/a}\] Here, U is drawn from the uniform distribution over (0,1]. The more common 2-parameter Weibull, including a scale parameter \(\lambda\) is just \(X = \lambda(-ln(U))... | |
doc_15781 | Set the value of the named cookie-attribute. | |
doc_15782 | Returns a tensor filled with the scalar value 0, with the same size as input. torch.zeros_like(input) is equivalent to torch.zeros(input.size(), dtype=input.dtype, layout=input.layout, device=input.device). Warning As of 0.4, this function does not support an out keyword. As an alternative, the old torch.zeros_like(in... | |
doc_15783 |
An unstructured triangular grid consisting of npoints points and ntri triangles. The triangles can either be specified by the user or automatically generated using a Delaunay triangulation. Parameters
x, y(npoints,) array-like
Coordinates of grid points.
triangles(ntri, 3) array-like of int, optional
For ea... | |
doc_15784 |
The transmute method is the very core of the ArrowStyle class and must be overridden in the subclasses. It receives the path object along which the arrow will be drawn, and the mutation_size, with which the arrow head etc. will be scaled. The linewidth may be used to adjust the path so that it does not pass beyond th... | |
doc_15785 |
Convert a 2D line to 3D. | |
doc_15786 |
Bases: matplotlib.colors.LogNorm Normalize a given value to the 0-1 range on a log scale. Parameters
vmin, vmaxfloat or None
If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) calls autoscale_None(A).
clipboo... | |
doc_15787 |
Return the url. | |
doc_15788 | See Migration guide for more details. tf.compat.v1.raw_ops.Less
tf.raw_ops.Less(
x, y, name=None
)
Note: math.less supports broadcasting. More about broadcasting here
Example: x = tf.constant([5, 4, 6])
y = tf.constant([5])
tf.math.less(x, y) ==> [False, True, False]
x = tf.constant([5, 4, 6])
y = tf.constant... | |
doc_15789 | Removes the pruning reparameterization from a module. The pruned parameter named name remains permanently pruned, and the parameter named name+'_orig' is removed from the parameter list. Similarly, the buffer named name+'_mask' is removed from the buffers. Note Pruning itself is NOT undone or reversed! | |
doc_15790 | control which events are allowed on the queue set_blocked(type) -> None set_blocked(typelist) -> None set_blocked(None) -> None The given event types are not allowed to appear on the event queue. By default all events can be placed on the queue. It is safe to disable an event type multiple times. If None is passed as... | |
doc_15791 |
Compute the absolute values element-wise. This function returns the absolute values (positive magnitude) of the data in x. Complex values are not handled, use absolute to find the absolute values of complex data. Parameters
xarray_like
The array of numbers for which the absolute values are required. If x is a s... | |
doc_15792 |
Linear model fitted by minimizing a regularized empirical loss with SGD SGD stands for Stochastic Gradient Descent: the gradient of the loss is estimated each sample at a time and the model is updated along the way with a decreasing strength schedule (aka learning rate). The regularizer is a penalty added to the loss... | |
doc_15793 |
Cursor to use when the tool is active. | |
doc_15794 |
Bases: matplotlib.patches.RegularPolygon A polygon-approximation of a circle patch. Create a circle at xy = (x, y) with given radius. This circle is approximated by a regular polygon with resolution sides. For a smoother circle drawn with splines, see Circle. Valid keyword arguments are:
Property Description
ag... | |
doc_15795 |
Draw the Artist (and its children) using the given renderer. This has no effect if the artist is not visible (Artist.get_visible returns False). Parameters
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses. | |
doc_15796 | tf.compat.v1.keras.initializers.he_normal(
seed=None
)
With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untruncated normal distribution with a mean of zero and a standard deviation (after truncation, if used) stddev = sqrt(scale / n) where n is: number of input unit... | |
doc_15797 | tf.distribute.experimental.coordinator.ClusterCoordinator(
strategy
)
This class is used to create fault-tolerant resources and dispatch functions to remote TensorFlow servers. Currently, this class is not supported to be used in a standalone manner. It should be used in conjunction with a tf.distribute strategy t... | |
doc_15798 |
Transform new data by linear interpolation Parameters
Tarray-like of shape (n_samples,) or (n_samples, 1)
Data to transform. Changed in version 0.24: Also accepts 2d array with 1 feature. Returns
y_predndarray of shape (n_samples,)
The transformed data | |
doc_15799 |
Bases: torch.distributions.transformed_distribution.TransformedDistribution Creates a RelaxedBernoulli distribution, parametrized by temperature, and either probs or logits (but not both). This is a relaxed version of the Bernoulli distribution, so the values are in (0, 1), and has reparametrizable samples. Example: ... |
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