Python matplotlib.ticker.LinearLocator() Examples
The following are 21
code examples of matplotlib.ticker.LinearLocator().
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Example #1
Source File: deforme.py From Image-Restoration with MIT License | 6 votes |
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 #2
Source File: lagrange.py From pyray with MIT License | 6 votes |
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 #3
Source File: mainwindow.py From Turing with MIT License | 5 votes |
def plot_window(xmin, xmax, ymin, ymax, xgrad=0, ygrad=0): GuiState.plot_axes.set_xlim(xmin, xmax) GuiState.plot_axes.set_ylim(ymin, ymax) GuiState.plot_axes.get_xaxis().set_major_locator( AutoLocator() if xgrad == 0 else LinearLocator(abs(int((xmax - xmin) / xgrad)) + 1)) GuiState.plot_axes.get_yaxis().set_major_locator( AutoLocator() if ygrad == 0 else LinearLocator(abs(int((ymax - ymin) / ygrad)) + 1))
Example #4
Source File: test_ticker.py From twitter-stock-recommendation with MIT License | 5 votes |
def test_set_params(self): """ Create linear locator with presets={}, numticks=2 and change it to something else. See if change was successful. Should not exception. """ loc = mticker.LinearLocator(numticks=2) loc.set_params(numticks=8, presets={(0, 1): []}) assert loc.numticks == 8 assert loc.presets == {(0, 1): []}
Example #5
Source File: test_ticker.py From twitter-stock-recommendation with MIT License | 5 votes |
def test_basic(self): loc = mticker.LinearLocator(numticks=3) test_value = np.array([-0.8, -0.3, 0.2]) assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
Example #6
Source File: tools.py From L2L with GNU General Public License v3.0 | 5 votes |
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 #7
Source File: plot_results.py From DeepLearningImplementations with MIT License | 5 votes |
def plot_tang(X, Y, Z, title, npts=None): fig = plt.figure() ax = fig.gca(projection='3d') # Plot the surface. surf = ax.plot_surface(X, Y, Z, cmap="viridis", linewidth=0, antialiased=False) # Customize the z axis. ax.set_zlim(-100, 250) ax.zaxis.set_tick_params(pad=8) ax.zaxis.set_major_locator(LinearLocator(5)) 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 "teacher" in title: plt.suptitle("Teacher model") if "student" in title and "sobolev" not in title: assert (npts is not None) plt.suptitle("Student model %s training pts" % npts) if "sobolev" in title: assert (npts is not None) plt.suptitle("Student model %s training pts + Sobolev" % npts) else: plt.suptitle("Styblinski Tang function") plt.savefig(title)
Example #8
Source File: test_ticker.py From coffeegrindsize with MIT License | 5 votes |
def test_set_params(self): """ Create linear locator with presets={}, numticks=2 and change it to something else. See if change was successful. Should not exception. """ loc = mticker.LinearLocator(numticks=2) loc.set_params(numticks=8, presets={(0, 1): []}) assert loc.numticks == 8 assert loc.presets == {(0, 1): []}
Example #9
Source File: test_ticker.py From coffeegrindsize with MIT License | 5 votes |
def test_basic(self): loc = mticker.LinearLocator(numticks=3) test_value = np.array([-0.8, -0.3, 0.2]) assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
Example #10
Source File: simulation.py From hypermax with BSD 3-Clause "New" or "Revised" License | 5 votes |
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 #11
Source File: simulation.py From hypermax with BSD 3-Clause "New" or "Revised" License | 5 votes |
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 #12
Source File: simulation.py From hypermax with BSD 3-Clause "New" or "Revised" License | 5 votes |
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 #13
Source File: simulation.py From hypermax with BSD 3-Clause "New" or "Revised" License | 5 votes |
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 #14
Source File: test_ticker.py From neural-network-animation with MIT License | 5 votes |
def test_LinearLocator(): loc = mticker.LinearLocator(numticks=3) test_value = np.array([-0.8, -0.3, 0.2]) assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
Example #15
Source File: test_ticker.py From ImageFusion with MIT License | 5 votes |
def test_LinearLocator(): loc = mticker.LinearLocator(numticks=3) test_value = np.array([-0.8, -0.3, 0.2]) assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
Example #16
Source File: read_NOM_maps.py From xrt with MIT License | 5 votes |
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 #17
Source File: test_surface.py From opticspy with MIT License | 5 votes |
def spherical_surf(l1): R = 1.02 l1 = l1 #surface matrix length theta = __np__.linspace(0, 2*__np__.pi, l1) rho = __np__.linspace(0, 1, l1) [u,r] = __np__.meshgrid(theta,rho) X = r*__cos__(u) Y = r*__sin__(u) Z = __sqrt__(R**2-r**2)-__sqrt__(R**2-1) v_1 = max(abs(Z.max()),abs(Z.min())) noise = (__np__.random.rand(len(Z),len(Z))*2-1)*0.05*v_1 Z = Z+noise fig = __plt__.figure(figsize=(12, 8), dpi=80) ax = fig.gca(projection='3d') surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=__cm__.RdYlGn,\ linewidth=0, antialiased=False, alpha = 0.6) v = max(abs(Z.max()),abs(Z.min())) ax.set_zlim(-1, 2) ax.zaxis.set_major_locator(__LinearLocator__(10)) ax.zaxis.set_major_formatter(__FormatStrFormatter__('%.02f')) cset = ax.contourf(X, Y, Z, zdir='z', offset=-1, cmap=__cm__.RdYlGn) fig.colorbar(surf, shrink=1, aspect=30) __plt__.title('Test Surface: Spherical surface with some noise',fontsize=16) __plt__.show() #Generate test surface matrix from a detector x = __np__.linspace(-1, 1, l1) y = __np__.linspace(-1, 1, l1) [X,Y] = __np__.meshgrid(x,y) Z = __sqrt__(R**2-(X**2+Y**2))-__sqrt__(R**2-1)+noise for i in range(len(Z)): for j in range(len(Z)): if x[i]**2+y[j]**2>1: Z[i][j]=0 return Z
Example #18
Source File: zernike_rec.py From opticspy with MIT License | 5 votes |
def zernikesurface(self): """ ------------------------------------------------ zernikesurface(self, label_1 = True): Return a 3D Zernike Polynomials surface figure label_1: default show label ------------------------------------------------ """ a = self.__a__ b = __sqrt__(1-a**2) x1 = __np__.linspace(-a, a, 50) y1 = __np__.linspace(-b, b, 50) [X,Y] = __np__.meshgrid(x1,y1) Z = __zernikecartesian__(self.__coefficients__,a,X,Y) fig = __plt__.figure(figsize=(12, 8), dpi=80) ax = fig.gca(projection='3d') surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=__cm__.RdYlGn, linewidth=0, antialiased=False, alpha = 0.6) ax.auto_scale_xyz([-1, 1], [-1, 1], [Z.max(), Z.min()]) # ax.set_xlim(-a, a) # ax.set_ylim(-b, b) # v = max(abs(Z.max()),abs(Z.min())) # ax.set_zlim(-v*5, v*5) # cset = ax.contourf(X, Y, Z, zdir='z', offset=-v*5, cmap=__cm__.RdYlGn) # ax.zaxis.set_major_locator(__LinearLocator__(10)) # ax.zaxis.set_major_formatter(__FormatStrFormatter__('%.02f')) fig.colorbar(surf, shrink=1, aspect=30) # p2v = round(__tools__.peak2valley(Z),5) # rms1 = round(__tools__.rms(Z),5) __plt__.show()
Example #19
Source File: test_ticker.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
def test_set_params(self): """ Create linear locator with presets={}, numticks=2 and change it to something else. See if change was successful. Should not exception. """ loc = mticker.LinearLocator(numticks=2) loc.set_params(numticks=8, presets={(0, 1): []}) assert loc.numticks == 8 assert loc.presets == {(0, 1): []}
Example #20
Source File: test_ticker.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
def test_basic(self): loc = mticker.LinearLocator(numticks=3) test_value = np.array([-0.8, -0.3, 0.2]) assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
Example #21
Source File: zernike.py From opticspy with MIT License | 4 votes |
def zernikesurface(self, label = True, zlim=[], matrix = False): """ ------------------------------------------------ zernikesurface(self, label_1 = True): Return a 3D Zernike Polynomials surface figure label_1: default show label ------------------------------------------------ """ theta = __np__.linspace(0, 2*__np__.pi, 100) rho = __np__.linspace(0, 1, 100) [u,r] = __np__.meshgrid(theta,rho) X = r*__cos__(u) Y = r*__sin__(u) Z = __interferometer__.__zernikepolar__(self.__coefficients__,r,u) fig = __plt__.figure(figsize=(12, 8), dpi=80) ax = fig.gca(projection='3d') surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=__cm__.RdYlGn, linewidth=0, antialiased=False, alpha = 0.6) if zlim == []: v = max(abs(Z.max()),abs(Z.min())) ax.set_zlim(-v*5, v*5) cset = ax.contourf(X, Y, Z, zdir='z', offset=-v*5, cmap=__cm__.RdYlGn) else: ax.set_zlim(zlim[0], zlim[1]) cset = ax.contourf(X, Y, Z, zdir='z', offset=zlim[0], cmap=__cm__.RdYlGn) ax.zaxis.set_major_locator(__LinearLocator__(10)) ax.zaxis.set_major_formatter(__FormatStrFormatter__('%.02f')) fig.colorbar(surf, shrink=1, aspect=30) p2v = round(__tools__.peak2valley(Z),5) rms1 = round(__tools__.rms(Z),5) label_1 = self.listcoefficient()[0]+"P-V: "+str(p2v)+"\n"+"RMS: "+str(rms1) if label == True: __plt__.title('Zernike Polynomials Surface',fontsize=18) ax.text2D(0.02, 0.1, label_1, transform=ax.transAxes,fontsize=14) else: pass __plt__.show() if matrix == True: return Z else: pass