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Various richly-typed exceptions, that also help us deal with string formatting
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in python where it's easier.
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By putting the formatting in `__str__`, we also avoid paying the cost for
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users who silence the exceptions.
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set_modulec C s t | dkr| d S | S d S )Né r )Úlen)Útup© r úMd:\z\workplace\vscode\pyvenv\venv\Lib\site-packages\numpy/core/_exceptions.pyÚ _unpack_tuple
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s r c C s t | tst| jj| _| S )aG
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A decorator that makes an exception class look like its base.
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We use this to hide subclasses that are implementation details - the user
|
should catch the base type, which is what the traceback will show them.
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|
Classes decorated with this decorator are subject to removal without a
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¡S )NzLufunc {!r} did not contain a loop with signature matching types {!r} -> {!r})r r r r r Úninr! r r r r" = s ÿúz_UFuncNoLoopError.__str__r# r r r r r% 6 s r% c s e Zd Z fddZ ZS )Ú_UFuncCastingErrorc s" t |¡ || _|| _|| _d S r )r r ÚcastingÚfrom_Úto)r r r( r) r* r r r r J s z_UFuncCastingError.__init__)r r r r r$ r r r r r' H s r' c s( e Zd ZdZ fddZdd Z ZS )Ú_UFuncInputCastingErrorz, Thrown when a ufunc input cannot be casted c s t ||||¡ || _d S r )r r Úin_i©r r r( r) r* Úir r r r T s z _UFuncInputCastingError.__init__c C s8 | j jdkrd | j¡nd}d | j j|| j| j| j¡S )Nr ú{} Ú zGCannot cast ufunc {!r} input {}from {!r} to {!r} with casting rule {!r})r r& r r, r r) r* r( ©r Zi_strr r r r" X s ÿ üz _UFuncInputCastingError.__str__r# r r r r r+ Q s r+ c s( e Zd ZdZ fddZdd Z ZS )Ú_UFuncOutputCastingErrorz- Thrown when a ufunc output cannot be casted c s t ||||¡ || _d S r )r r Úout_ir- r r r r f s z!_UFuncOutputCastingError.__init__c C s8 | j jdkrd | j¡nd}d | j j|| j| j| j¡S )Nr r/ r0 zHCannot cast ufunc {!r} output {}from {!r} to {!r} with casting rule {!r})r Znoutr r3 r r) r* r( r1 r r r r" j s ÿ üz _UFuncOutputCastingError.__str__r# r r r r r2 c s r2 Únumpyc @ s e Zd ZdZdS )Ú TooHardErrorzÿmax_work was exceeded.
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This is raised whenever the maximum number of candidate solutions
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|
N)r r r r r r r r r5 v s r5 c @ s& e Zd ZdZdZdddZdd ZdS ) Ú AxisErroraÞ Axis supplied was invalid.
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|
This is raised whenever an ``axis`` parameter is specified that is larger
|
than the number of array dimensions.
|
For compatibility with code written against older numpy versions, which
|
raised a mixture of `ValueError` and `IndexError` for this situation, this
|
exception subclasses both to ensure that ``except ValueError`` and
|
``except IndexError`` statements continue to catch `AxisError`.
|
|
.. versionadded:: 1.13
|
|
Parameters
|
----------
|
axis : int or str
|
The out of bounds axis or a custom exception message.
|
If an axis is provided, then `ndim` should be specified as well.
|
ndim : int, optional
|
The number of array dimensions.
|
msg_prefix : str, optional
|
A prefix for the exception message.
|
|
Attributes
|
----------
|
axis : int, optional
|
The out of bounds axis or ``None`` if a custom exception
|
message was provided. This should be the axis as passed by
|
the user, before any normalization to resolve negative indices.
|
|
.. versionadded:: 1.22
|
ndim : int, optional
|
The number of array dimensions or ``None`` if a custom exception
|
message was provided.
|
|
.. versionadded:: 1.22
|
|
|
Examples
|
--------
|
>>> array_1d = np.arange(10)
|
>>> np.cumsum(array_1d, axis=1)
|
Traceback (most recent call last):
|
...
|
numpy.AxisError: axis 1 is out of bounds for array of dimension 1
|
|
Negative axes are preserved:
|
|
>>> np.cumsum(array_1d, axis=-2)
|
Traceback (most recent call last):
|
...
|
numpy.AxisError: axis -2 is out of bounds for array of dimension 1
|
|
The class constructor generally takes the axis and arrays'
|
dimensionality as arguments:
|
|
>>> print(np.AxisError(2, 1, msg_prefix='error'))
|
error: axis 2 is out of bounds for array of dimension 1
|
|
Alternatively, a custom exception message can be passed:
|
|
>>> print(np.AxisError('Custom error message'))
|
Custom error message
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©ÚaxisÚndimÚ_msgNc C sB || krd kr,n n|| _ d | _d | _n|| _ || _|| _d S r )r: r8 r9 )r r8 r9 Z
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r r r r r ÚpropertyrB Ú staticmethodrH r" r r r r r= à s
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