_id stringlengths 5 9 | text stringlengths 5 385k | title stringclasses 1
value |
|---|---|---|
doc_16100 |
For each element in self, return a copy of the string where all characters occurring in the optional argument deletechars are removed, and the remaining characters have been mapped through the given translation table. See also char.translate | |
doc_16101 |
Attributes
base Returns a copy of the calling offset object with n=1 and all other attributes equal.
delta
freqstr
kwds
n
name
nanos
normalize
rule_code Methods
__call__(*args, **kwargs) Call self as a function.
rollback Roll provided date backward to next offset onl... | |
doc_16102 |
Set the Axes box aspect, i.e. the ratio of height to width. This defines the aspect of the Axes in figure space and is not to be confused with the data aspect (see set_aspect). Parameters
aspectfloat or None
Changes the physical dimensions of the Axes, such that the ratio of the Axes height to the Axes width in... | |
doc_16103 | @functools.lru_cache(maxsize=128, typed=False)
Decorator to wrap a function with a memoizing callable that saves up to the maxsize most recent calls. It can save time when an expensive or I/O bound function is periodically called with the same arguments. Since a dictionary is used to cache results, the positional and... | |
doc_16104 | Called when a previous send or receive operation raises an OSError. exc is the OSError instance. This method is called in rare conditions, when the transport (e.g. UDP) detects that a datagram could not be delivered to its recipient. In many conditions though, undeliverable datagrams will be silently dropped. | |
doc_16105 | tf.compat.v1.WholeFileReader(
name=None
)
To use, enqueue filenames in a Queue. The output of Read will be a filename (key) and the contents of that file (value). See ReaderBase for supported methods.
Args
name A name for the operation (optional). Eager Compatibility Readers are not compatible with eag... | |
doc_16106 |
Alias for set_linewidth. | |
doc_16107 |
Probability estimates. The returned estimates for all classes are ordered by label of classes. Note that in the multilabel case, each sample can have any number of labels. This returns the marginal probability that the given sample has the label in question. For example, it is entirely consistent that two labels both... | |
doc_16108 |
Initialize self. See help(type(self)) for accurate signature. | |
doc_16109 |
Return the kernel k(X, Y) and optionally its gradient. Parameters
Xarray-like of shape (n_samples_X, n_features) or list of object
Left argument of the returned kernel k(X, Y)
Yarray-like of shape (n_samples_Y, n_features) or list of object, default=None
Right argument of the returned kernel k(X, Y). If Non... | |
doc_16110 | Same as Element.find(), starting at the root of the tree. | |
doc_16111 | Return a suite of all test cases given a string specifier. The specifier name is a “dotted name” that may resolve either to a module, a test case class, a test method within a test case class, a TestSuite instance, or a callable object which returns a TestCase or TestSuite instance. These checks are applied in the orde... | |
doc_16112 |
Return the group id. | |
doc_16113 | Do not wait for data which is not immediately available. If this flag is specified, the system call will return instantly if it would have to read data from the backing storage or wait for a lock. If some data was successfully read, it will return the number of bytes read. If no bytes were read, it will return -1 and s... | |
doc_16114 |
Least squares fit to data. Return a series instance that is the least squares fit to the data y sampled at x. The domain of the returned instance can be specified and this will often result in a superior fit with less chance of ill conditioning. Parameters
xarray_like, shape (M,)
x-coordinates of the M sample p... | |
doc_16115 |
Set the font weight. Options are: A numeric value in the range 0-1000 or one of 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black' | |
doc_16116 |
Return a tuple of the shape of the underlying data. | |
doc_16117 | GeoDjango Tutorial Introduction Setting Up Geographic Data Geographic Models Importing Spatial Data Spatial Queries Putting your data on the map
GeoDjango Installation Overview Requirements Installation Troubleshooting Platform-specific instructions
GeoDjango Model API Spatial Field Types Spatial Field Options Ge... | |
doc_16118 |
Return data label of Stata file. | |
doc_16119 |
flatten_parameters() [source]
Resets parameter data pointer so that they can use faster code paths. Right now, this works only if the module is on the GPU and cuDNN is enabled. Otherwise, it’s a no-op. | |
doc_16120 |
Construct an array by executing a function over each coordinate. The resulting array therefore has a value fn(x, y, z) at coordinate (x, y, z). Parameters
functioncallable
The function is called with N parameters, where N is the rank of shape. Each parameter represents the coordinates of the array varying along... | |
doc_16121 | Converts a string into a normalized number string, following the LC_NUMERIC settings. New in version 3.5. | |
doc_16122 |
Return the Transform instance used by this ContourSet. | |
doc_16123 |
Convert a shortcut string from the notation used in rc config to the standard notation for displaying shortcuts, e.g. 'ctrl+a' -> 'Ctrl+A'. | |
doc_16124 |
The .. plot:: directive, as documented in the module's docstring. run()[source]
Run the plot directive. | |
doc_16125 |
Returns a field of the given array as a certain type. A field is a view of the array data with a given data-type. The values in the view are determined by the given type and the offset into the current array in bytes. The offset needs to be such that the view dtype fits in the array dtype; for example an array of dty... | |
doc_16126 |
Bases: torch.distributions.distribution.Distribution Creates a Student’s t-distribution parameterized by degree of freedom df, mean loc and scale scale. Example: >>> m = StudentT(torch.tensor([2.0]))
>>> m.sample() # Student's t-distributed with degrees of freedom=2
tensor([ 0.1046])
Parameters
df (float or Ten... | |
doc_16127 |
Called when a pan operation has started. Parameters
x, yfloat
The mouse coordinates in display coords.
buttonMouseButton
The pressed mouse button. Notes This is intended to be overridden by new projection types. | |
doc_16128 |
Multi-task ElasticNet model trained with L1/L2 mixed-norm as regularizer. The optimization objective for MultiTaskElasticNet is: (1 / (2 * n_samples)) * ||Y - XW||_Fro^2
+ alpha * l1_ratio * ||W||_21
+ 0.5 * alpha * (1 - l1_ratio) * ||W||_Fro^2
Where: ||W||_21 = sum_i sqrt(sum_j W_ij ^ 2)
i.e. the sum of norms of e... | |
doc_16129 |
Set multiple properties at once. Supported properties are
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
annotation_clip bool or None
antialiased or aa bool or None
arrowstyle None... | |
doc_16130 | Return the integer represented by the given array of bytes. >>> int.from_bytes(b'\x00\x10', byteorder='big')
16
>>> int.from_bytes(b'\x00\x10', byteorder='little')
4096
>>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=True)
-1024
>>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=False)
64512
>>> int.from_b... | |
doc_16131 |
Compute the embedding vectors for data X Parameters
X{array-like, sparse graph, BallTree, KDTree, NearestNeighbors}
Sample data, shape = (n_samples, n_features), in the form of a numpy array, sparse graph, precomputed tree, or NearestNeighbors object.
yIgnored
Returns
selfreturns an instance of self. | |
doc_16132 | When you use Django’s rendering shortcuts, CSS classes are used to indicate required form fields or fields that contain errors. If you’re manually rendering a form, you can access these CSS classes using the css_classes method: >>> f = ContactForm(data={'message': ''})
>>> f['message'].css_classes()
'required'
If you ... | |
doc_16133 | Child process stopped or terminated. Availability: Unix. | |
doc_16134 |
Bases: mpl_toolkits.axisartist.axis_artist.AxisLabel Tick Labels. While derived from Text, this single artist draws all ticklabels. As in AxisLabel, the position of the text is updated in the fly, so changing text position has no effect. Otherwise, the properties can be changed as a normal Text. Unlike the ticklabels... | |
doc_16135 | Get the type of completion being attempted. This returns the rl_completion_type variable in the underlying library as an integer. | |
doc_16136 | tf.strings.substr(
input, pos, len, unit='BYTE', name=None
)
For each string in the input Tensor, creates a substring starting at index pos with a total length of len. If len defines a substring that would extend beyond the length of the input string, or if len is negative, then as many characters as possible are ... | |
doc_16137 |
Synonym for DataFrame.fillna() with method='ffill'. Returns
Series/DataFrame or None
Object with missing values filled or None if inplace=True. | |
doc_16138 | alias of flask.wrappers.Request | |
doc_16139 | Return a measure of the sequences’ similarity as a float in the range [0, 1]. Where T is the total number of elements in both sequences, and M is the number of matches, this is 2.0*M / T. Note that this is 1.0 if the sequences are identical, and 0.0 if they have nothing in common. This is expensive to compute if get_ma... | |
doc_16140 | builder = tf.compat.v1.saved_model.builder.SavedModelBuilder(export_dir)
with tf.compat.v1.Session(graph=tf.Graph()) as sess:
...
builder.add_meta_graph_and_variables(sess,
["foo-tag"],
signature_def_map=foo_signatures,
... | |
doc_16141 | See Migration guide for more details. tf.compat.v1.raw_ops.DebugIdentityV2
tf.raw_ops.DebugIdentityV2(
input, tfdbg_context_id='', op_name='', output_slot=-1,
tensor_debug_mode=-1, debug_urls=[], circular_buffer_size=1000,
tfdbg_run_id='', name=None
)
Provides an identity mapping from input to output, wh... | |
doc_16142 |
Get the factor by which to magnify images passed to draw_image(). Allows a backend to have images at a different resolution to other artists. | |
doc_16143 | The type of methods of some built-in data types and base classes such as object.__init__() or object.__lt__(). New in version 3.7. | |
doc_16144 | '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_16145 |
Convert the input to an array, checking for NaNs or Infs. Parameters
aarray_like
Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Success requires no NaNs or Infs.
dtypedata-type, optional
By default, the... | |
doc_16146 | Return the values tensor of a sparse COO tensor. Warning Throws an error if self is not a sparse COO tensor. See also Tensor.indices(). Note This method can only be called on a coalesced sparse tensor. See Tensor.coalesce() for details. | |
doc_16147 |
Set pane color to a RGBA tuple. | |
doc_16148 | Send a randomly generated message to the other end of the connection and wait for a reply. If the reply matches the digest of the message using authkey as the key then a welcome message is sent to the other end of the connection. Otherwise AuthenticationError is raised. | |
doc_16149 | Return a randomly-chosen element from a non-empty sequence. | |
doc_16150 |
Initialize self. See help(type(self)) for accurate signature. | |
doc_16151 | See Migration guide for more details. tf.compat.v1.train.SequenceExample
Attributes
context Features context
feature_lists FeatureLists feature_lists | |
doc_16152 | Calculate the product of all the elements in the input iterable. The default start value for the product is 1. When the iterable is empty, return the start value. This function is intended specifically for use with numeric values and may reject non-numeric types. New in version 3.8. | |
doc_16153 | The master class-based base view. All other class-based views inherit from this base class. It isn’t strictly a generic view and thus can also be imported from django.views. Method Flowchart setup() dispatch() http_method_not_allowed() options() Example views.py: from django.http import HttpResponse
from django.views... | |
doc_16154 | Sets the user’s password to the given raw string, taking care of the password hashing. Doesn’t save the AbstractBaseUser object. When the raw_password is None, the password will be set to an unusable password, as if set_unusable_password() were used. | |
doc_16155 |
Transform X back to original space. Parameters
X{array-like, sparse matrix} of shape (n_samples, n_components)
Returns
X_newndarray of shape (n_samples, n_features)
References “Learning to Find Pre-Images”, G BakIr et al, 2004. | |
doc_16156 |
Bases: matplotlib.ticker.Locator Used to locate theta ticks. This will work the same as the base locator except in the case that the view spans the entire circle. In such cases, the previously used default locations of every 45 degrees are returned. refresh()[source]
set_axis(axis)[source]
view_limits(vmin,... | |
doc_16157 | Returns a new tensor which indexes the input tensor along dimension dim using the entries in index which is a LongTensor. The returned tensor has the same number of dimensions as the original tensor (input). The dimth dimension has the same size as the length of index; other dimensions have the same size as in the orig... | |
doc_16158 |
Return a list representing the axes of the DataFrame. It has the row axis labels and column axis labels as the only members. They are returned in that order. Examples
>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> df.axes
[RangeIndex(start=0, stop=2, step=1), Index(['col1', 'col2'],
dtype='object')] | |
doc_16159 | See Migration guide for more details. tf.compat.v1.raw_ops.BoostedTreesQuantileStreamResourceHandleOp
tf.raw_ops.BoostedTreesQuantileStreamResourceHandleOp(
container='', shared_name='', name=None
)
Args
container An optional string. Defaults to "".
shared_name An optional string. Defaults to "". ... | |
doc_16160 |
Return the Bbox bounding the text, in display units. In addition to being used internally, this is useful for specifying clickable regions in a png file on a web page. Parameters
rendererRenderer, optional
A renderer is needed to compute the bounding box. If the artist has already been drawn, the renderer is ca... | |
doc_16161 |
A 1-D iterator over the array. This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object. See also flatten
Return a copy of the array collapsed into one dimension. flatiter
Examples >>> x = np.arange(1, 7).reshape(2, 3)
>>> x
array([[1, 2, 3],
... | |
doc_16162 | tf.compat.v1.get_collection_ref(
key
)
See tf.Graph.get_collection_ref for more details.
Args
key The key for the collection. For example, the GraphKeys class contains many standard names for collections.
Returns The list of values in the collection with the given name, or an empty list if no va... | |
doc_16163 |
Return the offsets for the collection. | |
doc_16164 |
Return a configuration dictionary for usage in configuration() function defined in file setup_<name>.py. | |
doc_16165 |
Proxy objects are Node wrappers that flow through the program during symbolic tracing and record all the operations (torch function calls, method calls, operators) that they touch into the growing FX Graph. If you’re doing graph transforms, you can wrap your own Proxy method around a raw Node so that you can use the ... | |
doc_16166 | operator.__iand__(a, b)
a = iand(a, b) is equivalent to a &= b. | |
doc_16167 |
Generate indices to split data into training and test set. Parameters
Xarray-like of shape (n_samples, n_features)
Training data, where n_samples is the number of samples and n_features is the number of features.
yarray-like of shape (n_samples,)
The target variable for supervised learning problems.
group... | |
doc_16168 |
Fit the data from X, and returns the embedded coordinates. Parameters
Xarray-like of shape (n_samples, n_features) or (n_samples, n_samples)
Input data. If dissimilarity=='precomputed', the input should be the dissimilarity matrix.
yIgnored
initndarray of shape (n_samples,), default=None
Starting configur... | |
doc_16169 | class sklearn.base.DensityMixin [source]
Mixin class for all density estimators in scikit-learn. Methods
score(X[, y]) Return the score of the model on the data X.
score(X, y=None) [source]
Return the score of the model on the data X. Parameters
Xarray-like of shape (n_samples, n_features)
Test samples.... | |
doc_16170 | Put item into the queue. If optional args block is true and timeout is None (the default), block if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Full exception if no free slot was available within that time. Otherwise (block is false), put a... | |
doc_16171 | Change the owner and group id of path to the numeric uid and gid. This function will not follow symbolic links. As of Python 3.3, this is equivalent to os.chown(path, uid, gid, follow_symlinks=False). Raises an auditing event os.chown with arguments path, uid, gid, dir_fd. Availability: Unix. Changed in version 3.6: A... | |
doc_16172 |
Return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation. | |
doc_16173 |
Build a boosted classifier from the training set (X, y). Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)
The training input samples. Sparse matrix can be CSC, CSR, COO, DOK, or LIL. COO, DOK, and LIL are converted to CSR.
yarray-like of shape (n_samples,)
The target values (class la... | |
doc_16174 | A context manager that disables the garbage collector upon entry and reenables it upon exit. | |
doc_16175 |
Load and return the wine dataset (classification). New in version 0.18. The wine dataset is a classic and very easy multi-class classification dataset.
Classes 3
Samples per class [59,71,48]
Samples total 178
Dimensionality 13
Features real, positive Read more in the User Guide. Parameters
return_X_... | |
doc_16176 | Return the timeout in seconds (float) associated with socket operations, or None if no timeout is set. This reflects the last call to setblocking() or settimeout(). | |
doc_16177 | Creates a new test database and runs migrate against it. verbosity has the same behavior as in run_tests(). autoclobber describes the behavior that will occur if a database with the same name as the test database is discovered: If autoclobber is False, the user will be asked to approve destroying the existing database... | |
doc_16178 | A string mnemonic designating the reason this error occurred, for example CERTIFICATE_VERIFY_FAILED. The range of possible values depends on the OpenSSL version. New in version 3.3. | |
doc_16179 | Return some locale-specific information as a string. This function is not available on all systems, and the set of possible options might also vary across platforms. The possible argument values are numbers, for which symbolic constants are available in the locale module. The nl_langinfo() function accepts one of the f... | |
doc_16180 | ABC for iterable classes that also provide the __reversed__() method. New in version 3.6. | |
doc_16181 | urllib.request for opening and reading URLs
urllib.error containing the exceptions raised by urllib.request
urllib.parse for parsing URLs
urllib.robotparser for parsing robots.txt files | |
doc_16182 | draw a circle circle(surface, color, center, radius) -> Rect circle(surface, color, center, radius, width=0, draw_top_right=None, draw_top_left=None, draw_bottom_left=None, draw_bottom_right=None) -> Rect Draws a circle on the given surface.
Parameters:
surface (Surface) -- surface to draw on
color (Color or... | |
doc_16183 | tf.compat.v1.tpu.shard(
computation, inputs=None, num_shards=1, input_shard_axes=None,
outputs_from_all_shards=True, output_shard_axes=None, infeed_queue=None,
device_assignment=None, name=None, xla_options=None
)
inputs must be a list of Tensors or None (equivalent to an empty list), each of which has a c... | |
doc_16184 |
An HermiteE series class. The HermiteE class provides the standard Python numerical methods ‘+’, ‘-’, ‘*’, ‘//’, ‘%’, ‘divmod’, ‘**’, and ‘()’ as well as the attributes and methods listed in the ABCPolyBase documentation. Parameters
coefarray_like
HermiteE coefficients in order of increasing degree, i.e, (1, 2,... | |
doc_16185 | See Migration guide for more details. tf.compat.v1.raw_ops.TPUReplicateMetadata
tf.raw_ops.TPUReplicateMetadata(
num_replicas, num_cores_per_replica=1, topology='', use_tpu=True,
device_assignment=[], computation_shape=[], host_compute_core=[],
padding_map=[], step_marker_location='STEP_MARK_AT_ENTRY',
... | |
doc_16186 |
Evaluates module(input) in parallel across the GPUs given in device_ids. This is the functional version of the DataParallel module. Parameters
module (Module) – the module to evaluate in parallel
inputs (Tensor) – inputs to the module
device_ids (list of python:int or torch.device) – GPU ids on which to replica... | |
doc_16187 |
Evenly round to the given number of decimals. Parameters
aarray_like
Input data.
decimalsint, optional
Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point.
outndarray, optional
Alternative output array in which... | |
doc_16188 |
Return the array as an a.ndim-levels deep nested list of Python scalars. Return a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible builtin Python type, via the item function. If a.ndim is 0, then since the depth of the nested list is 0, it will not be a list at all,... | |
doc_16189 |
Return a Series containing counts of unique rows in the DataFrame. New in version 1.1.0. Parameters
subset:list-like, optional
Columns to use when counting unique combinations.
normalize:bool, default False
Return proportions rather than frequencies.
sort:bool, default True
Sort by frequencies.
asce... | |
doc_16190 | tf.experimental.numpy.square(
x
)
Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj. See the NumPy documentation for numpy.square. | |
doc_16191 | See Migration guide for more details. tf.compat.v1.keras.layers.RepeatVector
tf.keras.layers.RepeatVector(
n, **kwargs
)
Example: model = Sequential()
model.add(Dense(32, input_dim=32))
# now: model.output_shape == (None, 32)
# note: `None` is the batch dimension
model.add(RepeatVector(3))
# now: model.output_s... | |
doc_16192 |
Binarize labels in a one-vs-all fashion. Several regression and binary classification algorithms are available in scikit-learn. A simple way to extend these algorithms to the multi-class classification case is to use the so-called one-vs-all scheme. At learning time, this simply consists in learning one regressor or ... | |
doc_16193 |
Set the id. | |
doc_16194 | Raised when an input byte could not properly be assigned to a character; for example, a NUL byte (value 0) in a UTF-8 input stream. | |
doc_16195 |
When we want to use the LaTeX backend with postscript, we write PSFrag tags to a temporary postscript file, each one marking a position for LaTeX to render some text. convert_psfrags generates a LaTeX document containing the commands to convert those tags to text. LaTeX/dvips produces the postscript file that include... | |
doc_16196 | The name of the application the model is part of. This is taken from the app_label attribute of the model, and includes only the last part of the application’s Python import path; django.contrib.contenttypes, for example, becomes an app_label of contenttypes. | |
doc_16197 | Use list_display_links to control if and which fields in list_display should be linked to the “change” page for an object. By default, the change list page will link the first column – the first field specified in list_display – to the change page for each item. But list_display_links lets you change this: Set it to N... | |
doc_16198 | See Migration guide for more details. tf.compat.v1.raw_ops.SegmentMean
tf.raw_ops.SegmentMean(
data, segment_ids, name=None
)
Read the section on segmentation for an explanation of segments. Computes a tensor such that \(output_i = \frac{\sum_j data_j}{N}\) where mean is over j such that segment_ids[j] == i and ... | |
doc_16199 |
Set the linewidth in points. |
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