klotz: plot*

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  1. GitHub - brad-darksbian/fed_dashboard: A simple Dash and Plotly dashboard to review and compare…
    A simple dashboard to view federal economic data. This system uses the included CSV file of federal economic data to…
    github.com
  2. t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. The technique can be implemented via Barnes-Hut approximations, allowing it to be applied on large real-world datasets. We applied it on data sets with up to 30 million examples. The technique and its variants are introduced in the following papers:
  3. import numpy as np
    import matplotlib.pyplot as plt
    from scipy.interpolate import griddata

    # Load data from CSV
    dat = np.genfromtxt('dat.xyz', delimiter=' ',skip_header=0)
    X_dat = dat :,0 »
    Y_dat = dat :,1 »
    Z_dat = dat :,2 »

    # Convert from pandas dataframes to numpy arrays
    X, Y, Z, = np.array( » ), np.array( » ), np.array( » )
    for i in range(len(X_dat)):
    X = np.append(X,X_dat i » )
    Y = np.append(Y,Y_dat i » )
    Z = np.append(Z,Z_dat i » )

    # create x-y points to be used in heatmap
    xi = np.linspace(X.min(),X.max(),1000)
    yi = np.linspace(Y.min(),Y.max(),1000)

    # Z is a matrix of x-y values
    zi = griddata((X, Y), Z, (xi None,: » , yi :,None » ), method='cubic')

    # I control the range of my colorbar by removing data
    # outside of my range of interest
    zmin = 3
    zmax = 12
    zi (zi<zmin) | (zi>zmax) » = None

    # Create the contour plot
    CS = plt.contourf(xi, yi, zi, 15, cmap=plt.cm.rainbow,
    vmax=zmax, vmin=zmin)
    plt.colorbar()
    plt.show()
    2017-07-30 Tags: , , , , by klotz

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