
    !Цig                        S SK r S SKrS SKrS SKr\R                  R                  S5      r\ R                  S 5       r
\ R                  S 5       r\ R                  S 5       r\ R                  S 5       r\ R                  S 5       rg)    Nz	pywt.datac                      [         R                  R                  [        R	                  S5      5       n [
        R                  " U 5      S   nSSS5        U$ ! , (       d  f       W$ = f)aL  
Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
easy use in demos

The image is derived from accent-to-the-top.jpg at
http://www.public-domain-image.com/people-public-domain-images-pictures/

Parameters
----------
None

Returns
-------
ascent : ndarray
   convenient image to use for testing and demonstration

Examples
--------
>>> import pywt.data
>>> ascent = pywt.data.ascent()
>>> ascent.shape == (512, 512)
True
>>> ascent.max()
255

>>> import matplotlib.pyplot as plt
>>> plt.gray()
>>> plt.imshow(ascent)
<matplotlib.image.AxesImage object at ...>
>>> plt.show()

z
ascent.npzdataN	importlib	resourcesas_file_DATADIRjoinpathnpload)fascents     Q/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/pywt/data/_readers.pyr   r   
   sV    D 
			$	$X%6%6|%D	EF# 
F M 
F	E M   A
A&c                      [         R                  R                  [        R	                  S5      5       n [
        R                  " U 5      S   nSSS5        U$ ! , (       d  f       W$ = f)a  
Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
easy use in demos

Parameters
----------
None

Returns
-------
aero : ndarray
   convenient image to use for testing and demonstration

Examples
--------
>>> import pywt.data
>>> aero = pywt.data.ascent()
>>> aero.shape == (512, 512)
True
>>> aero.max()
255

>>> import matplotlib.pyplot as plt
>>> plt.gray()
>>> plt.imshow(aero)
<matplotlib.image.AxesImage object at ...>
>>> plt.show()

zaero.npzr   Nr   )r   aeros     r   r   r   2   sU    > 
			$	$X%6%6z%B	Cqwwqz&! 
D K 
D	C Kr   c                      [         R                  R                  [        R	                  S5      5       n [
        R                  " U 5      S   nSSS5        U$ ! , (       d  f       W$ = f)a  
Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
easy use in demos

Parameters
----------
None

Returns
-------
camera : ndarray
   convenient image to use for testing and demonstration

Notes
-----
No copyright restrictions. CC0 by the photographer (Lav Varshney).

.. versionchanged:: 0.18
    This image was replaced due to copyright restrictions. For more
    information, please see [1]_, where the same change was made in
    scikit-image.

References
----------
.. [1] https://github.com/scikit-image/scikit-image/issues/3927

Examples
--------
>>> import pywt.data
>>> camera = pywt.data.ascent()
>>> camera.shape == (512, 512)
True

>>> import matplotlib.pyplot as plt
>>> plt.gray()
>>> plt.imshow(camera)
<matplotlib.image.AxesImage object at ...>
>>> plt.show()

z
camera.npzr   Nr   )r   cameras     r   r   r   W   sV    T 
			$	$X%6%6|%D	EF# 
F M 
F	E Mr   c                      [         R                  R                  [        R	                  S5      5       n [
        R                  " U 5      S   nSSS5        U$ ! , (       d  f       W$ = f)ap  
Get 1024 points of an ECG timeseries.

Parameters
----------
None

Returns
-------
ecg : ndarray
   convenient timeseries to use for testing and demonstration

Examples
--------
>>> import pywt.data
>>> ecg = pywt.data.ecg()
>>> ecg.shape == (1024,)
True

>>> import matplotlib.pyplot as plt
>>> plt.plot(ecg)
[<matplotlib.lines.Line2D object at ...>]
>>> plt.show()
zecg.npzr   Nr   )r   ecgs     r   r   r      sU    4 
			$	$X%6%6y%A	Baggaj  
C J 
C	B Jr   c                  v   [         R                  R                  [        R	                  S5      5       n [
        R                  " U 5      S   nSSS5        [        [
        R                  " WR                  S   S-  5      S-  5      n[
        R                  " [
        R                  " [
        R                  " U5      SU2S4   US-  S45      S	S
9nU[
        R                  " U5      -
  [
        R                  " US	S9-  nSn[
        R                  " [        U5      5      U-  S-   nXS4$ ! , (       d  f       N= f)a!  
This data contains the averaged monthly sea surface temperature in degrees
Celsius of the Pacific Ocean, between 0-10 degrees South and 90-80 degrees West, from 1950 to 2016.
This dataset is in the public domain and was obtained from NOAA.
National Oceanic and Atmospheric Administration's National Weather Service
ERSSTv4 dataset, nino 3, http://www.cpc.ncep.noaa.gov/data/indices/

Parameters
----------
None

Returns
-------
time : ndarray
   convenient timeseries to use for testing and demonstration
sst : ndarray
   convenient timeseries to use for testing and demonstration

Examples
--------
>>> import pywt.data
>>> time, sst = pywt.data.nino()
>>> sst.shape == (264,)
True

>>> import matplotlib.pyplot as plt
>>> plt.plot(time,sst)
[<matplotlib.lines.Line2D object at ...>]
>>> plt.show()
zsst_nino3.npzr   Nr   g      (@         )axis)ddofg      ?g     x@)r   r   r   r	   r
   r   r   intfloorshapemeanreshapearraystdarangelen)r   sst_csvnsstdttimes         r   ninor,      s    @ 
			$	$X%6%6%G	HA''!*V$ 
I
 	BHHW]]1%c)*3./A ''"**RXXg.rr1u51bzB
KC!!4
4C	B99SX#f,D9 
I	Hs   D**
D8)	functoolsimportlib.resourcesr   osnumpyr   r   filesr	   cacher   r   r   r   r,        r   <module>r5      s      	 $$[1 $ $N ! !H , ,^  > , ,r4   