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import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
from skimage import data
from skimage.color import rgb2gray
from colorspacious import cspace_converter

I = data.astronaut()
I = rgb2gray(I)
cmaps = ['gray', 'magma', 'jet', 'RdGy']

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import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import KDTree

# Generate some number of sites in 
# the square [0, 1] x [0, 1]
np.random.seed(0)
n_sites = 20
sites = np.random.rand(n_sites, 2)
# Create random velocities

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import numpy as np
import scipy.io.wavfile as wavfile
import matplotlib.pyplot as plt

duration = 20
fs = 44100
y = np.zeros(fs*duration)
n_harmonics = 5
t = np.arange(fs*duration) # INCORRECT SAMPLING
#t = np.linspace(0, duration, fs*duration)  # CORRECT SAMPLING

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import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def getEDM(X):
    """
    Compute an all pairs distance matrix using broadcasting
    and matrix multiplications to speed up computations
    Parameters
    ----------

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"""
Programmer: Chris Tralie
Purpose: To show how to plot "time-ordered point clouds"
with colors on the rainbow to indicate the time
(red beginning, magenta end)
"""
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

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"""
Programmer: Chris Tralie ([email protected])
Purpose: To implement the connection Laplacian and show its use
for synchronizing a set of vectors on an NxN grid
"""
import numpy as np
import numpy.linalg as linalg
from scipy import sparse 
from scipy.sparse.linalg import lsqr, cg, eigsh
import matplotlib.pyplot as plt