186 lines
4.4 KiB
Python
186 lines
4.4 KiB
Python
import os
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import numpy as np
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def ascent():
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"""
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Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
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easy use in demos
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The image is derived from accent-to-the-top.jpg at
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http://www.public-domain-image.com/people-public-domain-images-pictures/
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Parameters
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----------
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None
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Returns
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-------
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ascent : ndarray
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convenient image to use for testing and demonstration
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Examples
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--------
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>>> import pywt.data
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>>> ascent = pywt.data.ascent()
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>>> ascent.shape == (512, 512)
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True
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>>> ascent.max()
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255
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>>> import matplotlib.pyplot as plt
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>>> plt.gray()
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>>> plt.imshow(ascent) # doctest: +ELLIPSIS
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<matplotlib.image.AxesImage object at ...>
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>>> plt.show() # doctest: +SKIP
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"""
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fname = os.path.join(os.path.dirname(__file__), 'ascent.npz')
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ascent = np.load(fname)['data']
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return ascent
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def aero():
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"""
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Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
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easy use in demos
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Parameters
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----------
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None
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Returns
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-------
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aero : ndarray
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convenient image to use for testing and demonstration
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Examples
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--------
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>>> import pywt.data
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>>> aero = pywt.data.ascent()
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>>> aero.shape == (512, 512)
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True
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>>> aero.max()
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255
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>>> import matplotlib.pyplot as plt
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>>> plt.gray()
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>>> plt.imshow(aero) # doctest: +ELLIPSIS
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<matplotlib.image.AxesImage object at ...>
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>>> plt.show() # doctest: +SKIP
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"""
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fname = os.path.join(os.path.dirname(__file__), 'aero.npz')
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aero = np.load(fname)['data']
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return aero
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def camera():
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"""
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Get an 8-bit grayscale bit-depth, 512 x 512 derived image for
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easy use in demos
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Parameters
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----------
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None
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Returns
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-------
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camera : ndarray
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convenient image to use for testing and demonstration
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Examples
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--------
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>>> import pywt.data
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>>> camera = pywt.data.ascent()
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>>> camera.shape == (512, 512)
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True
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>>> import matplotlib.pyplot as plt
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>>> plt.gray()
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>>> plt.imshow(camera) # doctest: +ELLIPSIS
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<matplotlib.image.AxesImage object at ...>
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>>> plt.show() # doctest: +SKIP
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"""
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fname = os.path.join(os.path.dirname(__file__), 'camera.npz')
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camera = np.load(fname)['data']
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return camera
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def ecg():
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"""
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Get 1024 points of an ECG timeseries.
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Parameters
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----------
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None
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Returns
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-------
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ecg : ndarray
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convenient timeseries to use for testing and demonstration
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Examples
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--------
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>>> import pywt.data
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>>> ecg = pywt.data.ecg()
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>>> ecg.shape == (1024,)
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True
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>>> import matplotlib.pyplot as plt
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>>> plt.plot(ecg) # doctest: +ELLIPSIS
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[<matplotlib.lines.Line2D object at ...>]
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>>> plt.show() # doctest: +SKIP
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"""
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fname = os.path.join(os.path.dirname(__file__), 'ecg.npy')
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ecg = np.load(fname)
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return ecg
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def nino():
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"""
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This data contains the averaged monthly sea surface temperature in degrees
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Celcius of the Pacific Ocean, between 0-10 degrees South and 90-80 degrees West, from 1950 to 2016.
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This dataset is in the public domain and was obtained from NOAA.
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National Oceanic and Atmospheric Administration's National Weather Service
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ERSSTv4 dataset, nino 3, http://www.cpc.ncep.noaa.gov/data/indices/
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Parameters
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----------
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None
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Returns
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-------
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time : ndarray
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convenient timeseries to use for testing and demonstration
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sst : ndarray
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convenient timeseries to use for testing and demonstration
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Examples
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--------
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>>> import pywt.data
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>>> time, sst = pywt.data.nino()
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>>> sst.shape == (264,)
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True
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>>> import matplotlib.pyplot as plt
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>>> plt.plot(time,sst) # doctest: +ELLIPSIS
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[<matplotlib.lines.Line2D object at ...>]
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>>> plt.show() # doctest: +SKIP
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"""
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fname = os.path.join(os.path.dirname(__file__), 'sst_nino3.npz')
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sst_csv = np.load(fname)['sst_csv']
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# sst_csv = pd.read_csv("http://www.cpc.ncep.noaa.gov/data/indices/ersst4.nino.mth.81-10.ascii", sep=' ', skipinitialspace=True)
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# take only full years
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n = int(np.floor(sst_csv.shape[0]/12.)*12.)
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# Building the mean of three mounth
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# the 4. column is nino 3
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sst = np.mean(np.reshape(np.array(sst_csv)[:n, 4], (n//3, -1)), axis=1)
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sst = (sst - np.mean(sst)) / np.std(sst, ddof=1)
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dt = 0.25
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time = np.arange(len(sst)) * dt + 1950.0 # construct time array
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return time, sst
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