Python matplotlib.cm.coolwarm() Examples

The following are 30 code examples of matplotlib.cm.coolwarm(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib.cm , or try the search function .
Example #1
Source File: benchmark.py    From NiaPy with MIT License 6 votes vote down vote up
def plot3d(self, scale=0.32):
		r"""Plot 3d scatter plot of benchmark function.

		Args:
			scale (float): Scale factor for points.
		"""
		fig = plt.figure()
		ax = Axes3D(fig)
		func = self.function()
		Xr, Yr = arange(self.Lower, self.Upper, scale), arange(self.Lower, self.Upper, scale)
		X, Y = meshgrid(Xr, Yr)
		Z = vectorize(self.__2dfun)(X, Y, func)
		ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
		ax.contourf(X, Y, Z, zdir='z', offset=-10, cmap=cm.coolwarm)
		ax.set_xlabel('X')
		ax.set_ylabel('Y')
		ax.set_zlabel('Z')
		plt.show()

# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3 
Example #2
Source File: franke.py    From pyGPGO with MIT License 6 votes vote down vote up
def plotFranke():
    """
    Plots Franke's function
    """
    x = np.linspace(0, 1, num=1000)
    y = np.linspace(0, 1, num=1000)
    X, Y = np.meshgrid(x, y)
    Z = f(X, Y)

    fig = plt.figure()
    ax = fig.gca(projection='3d')

    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                           linewidth=0)
    fig.colorbar(surf, shrink=0.5, aspect=5)
    plt.show() 
Example #3
Source File: gif_gen.py    From pyGPGO with MIT License 6 votes vote down vote up
def plotPred(gpgo, num=100):
    X = np.linspace(0, 1, num=num)
    Y = np.linspace(0, 1, num=num)
    U = np.zeros((num**2, 2))
    i = 0
    for x in X:
        for y in Y:
            U[i, :] = [x, y]
            i += 1
    z = gpgo.GP.predict(U)[0]
    Z = z.reshape((num, num))
    X, Y = np.meshgrid(X, Y)
    ax = fig.add_subplot(1, 2, 2, projection='3d')
    ax.set_title('Gaussian Process surrogate')
    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                           linewidth=0)
    fig.colorbar(surf, shrink=0.5, aspect=5)
    best = gpgo.best
    ax.scatter([best[0]], [best[1]], s=40, marker='x', c='r', label='Sampled point')
    plt.legend(loc='lower right')
    #plt.show()
    return Z 
Example #4
Source File: LST.py    From python-urbanPlanning with MIT License 6 votes vote down vote up
def ThrShow(self,data):        
        font1 = {'family' : 'STXihei',
         'weight' : 'normal',
         'size'   : 50,
         }
        fig, ax = plt.subplots(subplot_kw=dict(projection='3d'),figsize=(50,20))
        ls = LightSource(data.shape[0], data.shape[1])
        rgb = ls.shade(data, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')
        x=np.array([list(range(data.shape[0]))]*data.shape[1])
        print(x.shape,x.T.shape,data.shape)
        surf = ax.plot_surface(x, x.T, data, rstride=1, cstride=1, facecolors=rgb,linewidth=0, antialiased=False, shade=False,alpha=0.3)
        fig.colorbar(surf,shrink=0.5,aspect=5)
        cset = ax.contour(x, x.T, data, zdir='z', offset=37, cmap=cm.coolwarm)
        cset = ax.contour(x, x.T, data, zdir='x', offset=-30, cmap=cm.coolwarm)
        cset = ax.contour(x, x.T, data, zdir='y', offset=-30, cmap=cm.coolwarm)
        plt.show() 
Example #5
Source File: lagrange.py    From pyray with MIT License 6 votes vote down vote up
def three_d_grid():
    fig = plt.figure()
    ax = fig.gca(projection='3d')

    # Make data.
    X = np.arange(-5, 5, 0.25)
    Y = np.arange(-5, 5, 0.25)
    X, Y = np.meshgrid(X, Y)
    R = (X**3 + Y**3)
    Z = R

    # Plot the surface.
    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                        linewidth=0, antialiased=False)

    # Customize the z axis.
    #ax.set_zlim(-1.01, 1.01)
    #ax.zaxis.set_major_locator(LinearLocator(10))
    #ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)
    plt.show() 
Example #6
Source File: deforme.py    From Image-Restoration with MIT License 6 votes vote down vote up
def plot_surface(x,y,z):
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    surf = ax.plot_surface(x, y, z, cmap=cm.coolwarm,
                           linewidth=0, antialiased=False)

    # Customize the z axis.
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)
    if save_info:
        fig.tight_layout()
        fig.savefig('./gaussian'+ str(idx) + '.png')
    plt.show() 
Example #7
Source File: plotting.py    From incubator-sdap-nexus with Apache License 2.0 5 votes vote down vote up
def createHoffmueller(data, coordSeries, timeSeries, coordName, title, interpolate='nearest'):
    cmap = cm.coolwarm
    # ls = LightSource(315, 45)
    # rgb = ls.shade(data, cmap)

    fig, ax = plt.subplots()
    fig.set_size_inches(11.0, 8.5)
    cax = ax.imshow(data, interpolation=interpolate, cmap=cmap)

    def yFormatter(y, pos):
        if y < len(coordSeries):
            return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.)
        else:
            return ""

    def xFormatter(x, pos):
        if x < len(timeSeries):
            return timeSeries[int(x)].strftime('%b %Y')
        else:
            return ""

    ax.xaxis.set_major_formatter(FuncFormatter(xFormatter))
    ax.yaxis.set_major_formatter(FuncFormatter(yFormatter))

    ax.set_title(title)
    ax.set_ylabel(coordName)
    ax.set_xlabel('Date')

    fig.colorbar(cax)
    fig.autofmt_xdate()

    labels = ['point {0}'.format(i + 1) for i in range(len(data))]
    # plugins.connect(fig, plugins.MousePosition(fontsize=14))
    tooltip = mpld3.plugins.PointLabelTooltip(cax, labels=labels)
    mpld3.plugins.connect(fig, tooltip)
    mpld3.show()
    # sio = StringIO()
    # plt.savefig(sio, format='png')
    # return sio.getvalue() 
Example #8
Source File: drawing.py    From crappy with GNU General Public License v2.0 5 votes vote down vote up
def update(self,data):
    self.txt.set_text(self.text%data[self.label])
    self.dot.set_color(cm.coolwarm((data[self.label]-self.low)/self.amp)) 
Example #9
Source File: network.py    From Hopfield-Network with MIT License 5 votes vote down vote up
def plot_weights(self):
        plt.figure(figsize=(6, 5))
        w_mat = plt.imshow(self.W, cmap=cm.coolwarm)
        plt.colorbar(w_mat)
        plt.title("Network Weights")
        plt.tight_layout()
        plt.savefig("weights.png")
        plt.show() 
Example #10
Source File: pendulum_dpg.py    From mushroom-rl with MIT License 5 votes vote down vote up
def __init__(self, V, mu, low, high, phi, psi):
        plt.ion()

        self._V = V
        self._mu = mu
        self._phi = phi
        self._psi = psi

        fig = plt.figure(figsize=(10, 5))
        ax1 = fig.add_subplot(1, 2, 1)
        ax2 = fig.add_subplot(1, 2, 2)

        self._theta = np.linspace(low[0], high[0], 100)
        self._omega = np.linspace(low[1], high[1], 100)

        vv, mm = self._compute_data()

        ext = [low[0], high[0],
               low[1], high[1]]

        ax1.set_title('V')
        im1 = ax1.imshow(vv, cmap=cm.coolwarm, extent=ext, aspect='auto')
        fig.colorbar(im1, ax=ax1)

        ax2.set_title('mean')
        im2 = ax2.imshow(mm, cmap=cm.coolwarm, extent=ext, aspect='auto')
        fig.colorbar(im2, ax=ax2)

        self._im = [im1, im2]

        self._counter = 0

        plt.draw()
        plt.pause(0.1) 
Example #11
Source File: pendulum_ac.py    From mushroom-rl with MIT License 5 votes vote down vote up
def __init__(self, V, mu, std, low, high, phi, psi):
        plt.ion()

        self._V = V
        self._mu = mu
        self._std = std
        self._phi = phi
        self._psi = psi

        fig = plt.figure(figsize=(15, 5))
        ax1 = fig.add_subplot(1, 3, 1)
        ax2 = fig.add_subplot(1, 3, 2)
        ax3 = fig.add_subplot(1, 3, 3)

        self._theta = np.linspace(low[0], high[0], 100)
        self._omega = np.linspace(low[1], high[1], 100)

        vv, mm, ss = self._compute_data()

        ext = [low[0], high[0],
               low[1], high[1]]

        ax1.set_title('V')
        im1 = ax1.imshow(vv, cmap=cm.coolwarm, extent=ext, aspect='auto')
        fig.colorbar(im1, ax=ax1)

        ax2.set_title('mean')
        im2 = ax2.imshow(mm, cmap=cm.coolwarm, extent=ext, aspect='auto')
        fig.colorbar(im2, ax=ax2)

        ax3.set_title('sigma')
        im3 = ax3.imshow(ss, cmap=cm.coolwarm, extent=ext, aspect='auto')
        fig.colorbar(im3, ax=ax3)

        self._im = [im1, im2, im3]

        self._counter = 0

        plt.draw()
        plt.pause(.1) 
Example #12
Source File: simulation.py    From hypermax with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def createInteractionChartExample():
    algo = AlgorithmSimulation()
    param1 = algo.createHyperParameter()
    param2 = algo.createHyperParameter()
    interaction = algo.createHyperParameterInteraction(param1, param2, type=3)

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import axes3d, Axes3D
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    from matplotlib import cm

    fig = plt.figure()
    ax = fig.gca(projection='3d')

    funcStore = {}
    exec("import math\nimport scipy.interpolate\nfrom scipy.stats import norm\nfunc = " + interaction['func'], funcStore)
    func = funcStore['func']

    xVals = numpy.linspace(0, 1, 25)
    yVals = numpy.linspace(0, 1, 25)

    grid = []
    for x in xVals:
        row = []
        for y in yVals:
            row.append(func(x, y)[0])
        grid.append(row)

    # Plot the surface.
    xVals, yVals = numpy.meshgrid(xVals, yVals)
    surf = ax.plot_surface(xVals, yVals, numpy.array(grid), cmap=cm.coolwarm, linewidth=0, antialiased=False, vmin=0, vmax=1)

    # Customize the z axis.
    ax.set_zlim(0, 1.00)
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)

    plt.show() 
Example #13
Source File: simulation.py    From hypermax with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def createContributionChartExample():
    algo = AlgorithmSimulation()
    param1 = algo.createHyperParameter()
    contribution = algo.createHyperParameterContribution(param1, type=4)

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import axes3d, Axes3D
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    from matplotlib import cm

    fig, ax = plt.subplots()

    print(contribution['func'])
    funcStore = {}
    exec("import math\nimport scipy.interpolate\nfunc = " + contribution['func'], funcStore)
    func = funcStore['func']

    xVals = numpy.linspace(0, 1, 25)

    yVals = []
    for x in xVals:
        yVals.append(func(x))

    # Plot the surface.
    surf = ax.scatter(numpy.array(xVals), numpy.array(yVals), cmap=cm.coolwarm, linewidth=0, antialiased=False, vmin=0, vmax=1)

    plt.show() 
Example #14
Source File: simulation.py    From hypermax with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def createInteractionChartExample():
    algo = AlgorithmSimulation()
    param1 = algo.createHyperParameter()
    param2 = algo.createHyperParameter()
    interaction = algo.createHyperParameterInteraction(param1, param2, type=3)

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import axes3d, Axes3D
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    from matplotlib import cm

    fig = plt.figure()
    ax = fig.gca(projection='3d')

    funcStore = {}
    exec("import math\nimport scipy.interpolate\nfrom scipy.stats import norm\nfunc = " + interaction['func'], funcStore)
    func = funcStore['func']

    xVals = numpy.linspace(0, 1, 25)
    yVals = numpy.linspace(0, 1, 25)

    grid = []
    for x in xVals:
        row = []
        for y in yVals:
            row.append(func(x, y)[0])
        grid.append(row)

    # Plot the surface.
    xVals, yVals = numpy.meshgrid(xVals, yVals)
    surf = ax.plot_surface(xVals, yVals, numpy.array(grid), cmap=cm.coolwarm, linewidth=0, antialiased=False, vmin=0, vmax=1)

    # Customize the z axis.
    ax.set_zlim(0, 1.00)
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)

    plt.show() 
Example #15
Source File: simulation.py    From hypermax with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def createContributionChartExample(type=4):
    algo = AlgorithmSimulation()
    param1 = algo.createHyperParameter()
    contribution = algo.createHyperParameterContribution(param1, type=type)

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import axes3d, Axes3D
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    from matplotlib import cm

    fig, ax = plt.subplots()

    print(contribution['func'])
    funcStore = {}
    exec("import math\nimport scipy.interpolate\nfunc = " + contribution['func'], funcStore)
    func = funcStore['func']

    xVals = numpy.linspace(0, 1, 25)

    yVals = []
    for x in xVals:
        yVals.append(func(x))

    # Plot the surface.
    surf = ax.scatter(numpy.array(xVals), numpy.array(yVals), cmap=cm.coolwarm, linewidth=0, antialiased=False, vmin=0, vmax=1)

    plt.show() 
Example #16
Source File: tools.py    From L2L with GNU General Public License v3.0 5 votes vote down vote up
def plot(fn, random_state):
    """
    Implements plotting of 2D functions generated by FunctionGenerator
    :param fn: Instance of FunctionGenerator
    """
    import numpy as np
    from l2l.matplotlib_ import plt
    from mpl_toolkits.mplot3d import Axes3D
    from matplotlib import cm
    from matplotlib.ticker import LinearLocator, FormatStrFormatter

    fig = plt.figure()
    ax = fig.gca(projection=Axes3D.name)

    # Make data.
    X = np.arange(fn.bound[0], fn.bound[1], 0.05)
    Y = np.arange(fn.bound[0], fn.bound[1], 0.05)
    XX, YY = np.meshgrid(X, Y)
    Z = [fn.cost_function([x, y], random_state=random_state) for x, y in zip(XX.ravel(), YY.ravel())]
    Z = np.array(Z).reshape(XX.shape)

    # Plot the surface.
    surf = ax.plot_surface(XX, YY, Z, cmap=cm.coolwarm, linewidth=0, antialiased=False)

    # Customize the z axis.
    # ax.set_zlim(-1.01, 1.01)
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
    W = np.where(Z == np.min(Z))
    ax.set(title='Min value is %.2f at (%.2f, %.2f)' % (np.min(Z), X[W[0]], Y[W[1]]))

    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)
    plt.savefig('function.png')
    plt.show() 
Example #17
Source File: density.py    From SqueezeMeta with GNU General Public License v3.0 5 votes vote down vote up
def plot(self, data, xlabel, ylabel):
        # set size of figure
        self.fig.clear()
        self.fig.set_size_inches(self.options.width, self.options.height)
        axis = self.fig.add_subplot(111)
        
        cax = axis.imshow(data, cmap=cm.coolwarm)
        cbar = self.fig.colorbar(cax)

        axis.set_xlabel(xlabel)
        axis.set_ylabel(ylabel)
        
        axis.set_yticks([0, 4, 8, 12, 16, 20])
        axis.set_yticklabels(['100', '90', '80', '70', '60', '50'])
        
        # *** Prettify plot
        for line in axis.yaxis.get_ticklines(): 
            line.set_color(self.axes_colour)
                
        for line in axis.xaxis.get_ticklines(): 
            line.set_color(self.axes_colour)
            
        for loc, spine in axis.spines.items():
            spine.set_color(self.axes_colour)

        self.fig.tight_layout(pad=1.0, w_pad=0.1, h_pad=0.1)
        self.draw() 
Example #18
Source File: plt_results2D.py    From snn4hrl with MIT License 5 votes vote down vote up
def plot_reward(fig, data_unpickle, color, fig_dir):
    env = data_unpickle['env']
    # retrieve original policy
    poli = data_unpickle['policy']
    mean = poli.get_action(np.array((0, 0)))[1]['mean']
    logstd = poli.get_action(np.array((0, 0)))[1]['log_std']
    # def normal(x): return 1/(np.exp(logstd)*np.sqrt(2*np.pi) )*np.exp(-0.5/np.exp(logstd)**2*(x-mean)**2) 
    ax = fig.gca(projection='3d')
    bound = env.mu[0]*1.2  # bound to plot: 20% more than the good modes
    X = np.arange(-bound, bound, 0.05)
    Y = np.arange(-bound, bound, 0.05)
    X, Y = np.meshgrid(X, Y)
    X_flat = X.reshape((-1, 1))
    Y_flat = Y.reshape((-1, 1))
    XY = np.concatenate((X_flat, Y_flat), axis=1)
    rew = np.array([env.reward_state(xy) for xy in XY]).reshape(np.shape(X))

    surf = ax.plot_surface(X, Y, rew, rstride=1, cstride=1, cmap=cm.coolwarm,
                           linewidth=0, antialiased=False)
    # policy_at0 = [normal(s) for s in x]
    # plt.plot(x,policy_at0,color=color*0.5,label='Policy at 0')
    plt.title('Reward acording to the state')
    fig.colorbar(surf, shrink=0.8)
    # plt.show()
    if fig_dir:
        plt.savefig(os.path.join(fig_dir, 'Reward_function'))
    else:
        print("No directory for saving plots")


# Plot learning curve 
Example #19
Source File: HofMoellerSpark.py    From incubator-sdap-nexus with Apache License 2.0 5 votes vote down vote up
def createHoffmueller(self, data, coordSeries, timeSeries, coordName, title, interpolate='nearest'):
        cmap = cm.coolwarm
        # ls = LightSource(315, 45)
        # rgb = ls.shade(data, cmap)

        fig, ax = plt.subplots()
        fig.set_size_inches(11.0, 8.5)
        cax = ax.imshow(data, interpolation=interpolate, cmap=cmap)

        def yFormatter(y, pos):
            if y < len(coordSeries):
                return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.)
            else:
                return ""

        def xFormatter(x, pos):
            if x < len(timeSeries):
                return timeSeries[int(x)].strftime('%b %Y')
            else:
                return ""

        ax.xaxis.set_major_formatter(FuncFormatter(xFormatter))
        ax.yaxis.set_major_formatter(FuncFormatter(yFormatter))

        ax.set_title(title)
        ax.set_ylabel(coordName)
        ax.set_xlabel('Date')

        fig.colorbar(cax)
        fig.autofmt_xdate()

        labels = ['point {0}'.format(i + 1) for i in range(len(data))]
        # plugins.connect(fig, plugins.MousePosition(fontsize=14))
        tooltip = mpld3.plugins.PointLabelTooltip(cax, labels=labels)

        sio = StringIO()
        plt.savefig(sio, format='png')
        return sio.getvalue() 
Example #20
Source File: lon_hof_moeller.py    From incubator-sdap-nexus with Apache License 2.0 5 votes vote down vote up
def createHoffmueller(data, coordSeries, timeSeries, coordName, title, interpolate='nearest'):

    cmap = cm.coolwarm
    # ls = LightSource(315, 45)
    # rgb = ls.shade(data, cmap)

    fig, ax = plt.subplots()
    fig.set_size_inches(11.0, 8.5)
    cax = ax.imshow(data, interpolation=interpolate, cmap=cmap)

    def yFormatter(y, pos):
        if y < len(coordSeries):
            return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.)
        else:
            return ""

    def xFormatter(x, pos):
        if x < len(timeSeries):
            return timeSeries[int(x)].strftime('%b %Y')
        else:
            return ""

    ax.xaxis.set_major_formatter(FuncFormatter(xFormatter))
    ax.yaxis.set_major_formatter(FuncFormatter(yFormatter))

    ax.set_title(title)
    ax.set_ylabel(coordName)
    ax.set_xlabel('Date')

    fig.colorbar(cax)
    fig.autofmt_xdate()

    plt.show() 
Example #21
Source File: lat_hof_moeller.py    From incubator-sdap-nexus with Apache License 2.0 5 votes vote down vote up
def createHoffmueller(data, coordSeries, timeSeries, coordName, title, interpolate='nearest'):

    cmap = cm.coolwarm
    # ls = LightSource(315, 45)
    # rgb = ls.shade(data, cmap)

    fig, ax = plt.subplots()
    fig.set_size_inches(11.0, 8.5)
    cax = ax.imshow(data, interpolation=interpolate, cmap=cmap)

    def yFormatter(y, pos):
        if y < len(coordSeries):
            return "%s $^\circ$" % (int(coordSeries[int(y)] * 100.0) / 100.)
        else:
            return ""

    def xFormatter(x, pos):
        if x < len(timeSeries):
            return timeSeries[int(x)].strftime('%b %Y')
        else:
            return ""

    ax.xaxis.set_major_formatter(FuncFormatter(xFormatter))
    ax.yaxis.set_major_formatter(FuncFormatter(yFormatter))

    ax.set_title(title)
    ax.set_ylabel(coordName)
    ax.set_xlabel('Date')

    fig.colorbar(cax)
    fig.autofmt_xdate()

    plt.show() 
Example #22
Source File: read_NOM_maps.py    From xrt with MIT License 5 votes vote down vote up
def plot_NOM_3D(fname):
    from mpl_toolkits.mplot3d import Axes3D
    from matplotlib import cm
    from matplotlib.ticker import LinearLocator, FormatStrFormatter

    xL, yL, zL = np.loadtxt(fname+'.dat', unpack=True)
    nX = (yL == yL[0]).sum()
    nY = (xL == xL[0]).sum()
    x = xL.reshape((nY, nX))
    y = yL.reshape((nY, nX))
    z = zL.reshape((nY, nX))
    x1D = xL[:nX]
    y1D = yL[::nX]
#    z += z[::-1, :]
    zmax = abs(z).max()

    fig = plt.figure()
    ax = fig.gca(projection='3d')
    surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, cmap=cm.coolwarm,
                           linewidth=0, antialiased=False, alpha=0.5)
    ax.set_zlim(-zmax, zmax)
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

    fig.colorbar(surf, shrink=0.5, aspect=5)

    splineZ = ndimage.spline_filter(z.T)
    nrays = 1e3
    xnew = np.random.uniform(x1D[0], x1D[-1], nrays)
    ynew = np.random.uniform(y1D[0], y1D[-1], nrays)
    coords = np.array([(xnew-x1D[0]) / (x1D[-1]-x1D[0]) * (nX-1),
                       (ynew-y1D[0]) / (y1D[-1]-y1D[0]) * (nY-1)])
    znew = ndimage.map_coordinates(splineZ, coords, prefilter=True)
    ax.scatter(xnew, ynew, znew, c=znew, marker='o', color='gray', s=50,
               cmap=cm.coolwarm)

    fig.savefig(fname+'_3d.png')
    plt.show() 
Example #23
Source File: plot_utils.py    From copula-py with GNU General Public License v3.0 5 votes vote down vote up
def plot_3d(X,Y,Z, titleStr):
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
        linewidth=0, antialiased=False)
    fig.colorbar(surf, shrink=0.5, aspect=5)
    plt.xlabel('U1')
    plt.ylabel('U2')
    plt.title(titleStr)
    plt.show() 
Example #24
Source File: HookClass.py    From pySDC with BSD 2-Clause "Simplified" License 5 votes vote down vote up
def post_step(self, status):
        """
        Overwrite standard dump per step

        Args:
            status: status object per step
        """
        super(plot_solution,self).post_step(status)

        if False:
          yplot = self.level.uend.values
          xx    = self.level.prob.xc
          yy    = self.level.prob.yc
          self.fig.clear()
          plt.plot( xx[:,0], yplot[0,:,0])
          plt.ylim([-1.0, 1.0])
          plt.show(block=False)
          plt.pause(0.00001)        

            
        if True:
          yplot = self.level.uend.values
          xx    = self.level.prob.xc
          zz    = self.level.prob.yc
          self.fig.clear()
          CS = plt.contourf(xx, zz, yplot[0,:,:], rstride=1, cstride=1, cmap=cm.coolwarm, linewidth=0, antialiased=False)
          cbar = plt.colorbar(CS)
          #plt.axes().set_xlim(xmin = self.level.prob.x_b[0], xmax = self.level.prob.x_b[1])
          #plt.axes().set_ylim(ymin = self.level.prob.z_b[0], ymax = self.level.prob.z_b[1])
          #plt.axes().set_aspect('equal')
          plt.xlabel('x')
          plt.ylabel('z')
          #plt.tight_layout()
          plt.show(block=False)
          plt.pause(0.00001)

        return None 
Example #25
Source File: HookClass.py    From pySDC with BSD 2-Clause "Simplified" License 5 votes vote down vote up
def post_step(self, status):
        """
        Overwrite standard dump per step

        Args:
            status: status object per step
        """
        super(plot_solution,self).post_step(status)

        #yplot = self.level.uend.values
        #xx    = self.level.prob.xx
        #zz    = self.level.prob.zz
        #self.fig.clear()
        #plt.plot( xx[:,0], yplot[2,:,0])
        #plt.ylim([-1.1, 1.1])
        #plt.show(block=False)
        #plt.pause(0.00001)        
          
        if True:
          yplot = self.level.uend.values
          xx    = self.level.prob.xx
          zz    = self.level.prob.zz
          self.fig.clear()
          CS = plt.contourf(xx, zz, yplot[2,:,:], rstride=1, cstride=1, cmap=cm.coolwarm, linewidth=0, antialiased=False)
          cbar = plt.colorbar(CS)
          plt.axes().set_xlim(xmin = self.level.prob.x_bounds[0], xmax = self.level.prob.x_bounds[1])
          plt.axes().set_ylim(ymin = self.level.prob.z_bounds[0], ymax = self.level.prob.z_bounds[1])
          plt.axes().set_aspect('equal')
          plt.xlabel('x')
          plt.ylabel('z')
          #plt.tight_layout()
          plt.show(block=False)
          plt.pause(0.00001)

        return None 
Example #26
Source File: simple_linear_regression.py    From deep-learning-samples with The Unlicense 5 votes vote down vote up
def plot_cost_3D(x, y, costfunc, mb_history=None):
    """Plot cost as 3D and contour.

    x, y: arrays of data.
    costfunc: cost function with signature like compute_cost.
    mb_history:
        if provided, it's a sequence of (m, b) pairs that are added as
        crosshairs markers on top of the contour plot.
    """
    lim = 10.0
    N = 250
    ms = np.linspace(-lim, lim, N)
    bs = np.linspace(-lim, lim, N)
    cost = np.zeros((N, N))
    for m_idx in range(N):
        for b_idx in range(N):
            cost[m_idx, b_idx] = costfunc(x, y, ms[m_idx], bs[b_idx])
    # Configure 3D plot.
    fig = plt.figure()
    fig.set_tight_layout(True)
    ax1 = fig.add_subplot(1, 2, 1, projection='3d')
    ax1.set_xlabel('b')
    ax1.set_ylabel('m')
    msgrid, bsgrid = np.meshgrid(ms, bs)
    surf = ax1.plot_surface(msgrid, bsgrid, cost, cmap=cm.coolwarm)

    # Configure contour plot.
    ax2 = fig.add_subplot(1, 2, 2)
    ax2.contour(msgrid, bsgrid, cost)
    ax2.set_xlabel('b')
    ax2.set_ylabel('m')

    if mb_history:
        ms, bs = zip(*mb_history)
        plt.plot(bs, ms, 'rx', mew=3, ms=5)

    plt.show() 
Example #27
Source File: gif_gen.py    From pyGPGO with MIT License 5 votes vote down vote up
def plotFranke():
    x = np.linspace(0, 1, num=1000)
    y = np.linspace(0, 1, num=1000)
    X, Y = np.meshgrid(x, y)
    Z = f(X, Y)
    ax = fig.add_subplot(1, 2, 1, projection='3d')
    ax.set_title('Original function')

    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                           linewidth=0)
    fig.colorbar(surf, shrink=0.5, aspect=5) 
Example #28
Source File: drawing.py    From crappy with GNU General Public License v2.0 5 votes vote down vote up
def prepare(self):
    plt.switch_backend(self.backend)
    self.fig, self.ax = plt.subplots(figsize=self.window_size)
    image = self.ax.imshow(plt.imread(self.image), cmap=cm.coolwarm)
    image.set_clim(-0.5, 1)
    cbar = self.fig.colorbar(image, ticks=[-0.5, 1], fraction=0.061,
        orientation='horizontal', pad=0.04)
    cbar.set_label('Temperatures(C)')
    cbar.ax.set_xticklabels(self.crange)
    self.ax.set_title(self.title)
    self.ax.set_axis_off()

    self.elements = []
    for d in self.draw:
      self.elements.append(elements[d['type']](self,**d)) 
Example #29
Source File: plotting.py    From incubator-sdap-nexus with Apache License 2.0 4 votes vote down vote up
def createLatLonTimeAverageMap(res, meta, startTime=None, endTime=None):
    latSeries = [m[0]['lat'] for m in res][::-1]
    lonSeries = [m['lon'] for m in res[0]]

    data = np.zeros((len(latSeries), len(lonSeries)))

    for t in range(0, len(latSeries)):
        latSet = res[t]
        for l in range(0, len(lonSeries)):
            data[len(latSeries) - t - 1][l] = latSet[l]['avg']

    def yFormatter(y, pos):
        if y < len(latSeries):
            return '%s $^\circ$' % (int(latSeries[int(y)] * 100.0) / 100.)
        else:
            return ""

    def xFormatter(x, pos):
        if x < len(lonSeries):
            return "%s $^\circ$" % (int(lonSeries[int(x)] * 100.0) / 100.)
        else:
            return ""

    data[data == 0.0] = np.nan
    fig, ax = plt.subplots()
    fig.set_size_inches(11.0, 8.5)

    cmap = cm.coolwarm
    ls = LightSource(315, 45)
    masked_array = np.ma.array(data, mask=np.isnan(data))
    rgb = ls.shade(masked_array, cmap)

    cax = ax.imshow(rgb, interpolation='nearest', cmap=cmap)

    ax.yaxis.set_major_formatter(FuncFormatter(yFormatter))
    ax.xaxis.set_major_formatter(FuncFormatter(xFormatter))

    title = meta['title']
    source = meta['source']
    if startTime is not None and endTime is not None:
        if type(startTime) is not datetime.datetime:
            startTime = datetime.datetime.fromtimestamp(startTime / 1000)
        if type(endTime) is not datetime.datetime:
            endTime = datetime.datetime.fromtimestamp(endTime / 1000)
        dateRange = "%s - %s" % (startTime.strftime('%b %Y'), endTime.strftime('%b %Y'))
    else:
        dateRange = ""

    ax.set_title("%s\n%s\n%s" % (title, source, dateRange))
    ax.set_ylabel('Latitude')
    ax.set_xlabel('Longitude')

    fig.colorbar(cax)
    fig.autofmt_xdate()

    sio = StringIO()
    plt.savefig(sio, format='png')
    return sio.getvalue() 
Example #30
Source File: BaseConditionalDensity.py    From Conditional_Density_Estimation with MIT License 4 votes vote down vote up
def plot3d(self, xlim=(-5, 5), ylim=(-8, 8), resolution=100, show=False, numpyfig=False):
    """ Generates a 3d surface plot of the fitted conditional distribution if x and y are 1-dimensional each

    Args:
      xlim: 2-tuple specifying the x axis limits
      ylim: 2-tuple specifying the y axis limits
      resolution: integer specifying the resolution of plot
    """
    assert self.ndim_x + self.ndim_y == 2, "Can only plot two dimensional distributions"

    if show == False and mpl.is_interactive():
      plt.ioff()
      mpl.use('Agg')

    # prepare mesh
    linspace_x = np.linspace(xlim[0], xlim[1], num=resolution)
    linspace_y = np.linspace(ylim[0], ylim[1], num=resolution)
    X, Y = np.meshgrid(linspace_x, linspace_y)
    X, Y = X.flatten(), Y.flatten()

    # calculate values of distribution
    Z = self.pdf(X, Y)

    X, Y, Z = X.reshape([resolution, resolution]), Y.reshape([resolution, resolution]), Z.reshape(
      [resolution, resolution])
    fig = plt.figure(dpi=300)
    ax = fig.gca(projection='3d')
    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm, rcount=resolution, ccount=resolution,
                           linewidth=100, antialiased=True)
    plt.xlabel("x")
    plt.ylabel("y")
    if show:
      plt.show()

    if numpyfig:
      fig.tight_layout(pad=0)
      fig.canvas.draw()
      numpy_img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
      numpy_img = numpy_img.reshape(fig.canvas.get_width_height()[::-1] + (3,))
      return numpy_img

    return fig