def test_polar_box(): # Remove this line when this test image is regenerated. plt.rcParams['text.kerning_factor'] = 6 fig = plt.figure(figsize=(5, 5)) # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf)) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1) axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper().set_extremes(2, 12) ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1) axis.label.set_text("Test 2") axis.get_helper().set_extremes(-180, 90) # A parasite axes with given transform ax2 = ParasiteAxes(ax1, tr, viewlim_mode="equal") assert ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50)) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True)
def test_ParasiteAxesAuxTrans(): data = np.ones((6, 6)) data[2, 2] = 2 data[0, :] = 0 data[-2, :] = 0 data[:, 0] = 0 data[:, -2] = 0 x = np.arange(6) y = np.arange(6) xx, yy = np.meshgrid(x, y) funcnames = ['pcolor', 'pcolormesh', 'contourf'] fig = plt.figure() for i, name in enumerate(funcnames): ax1 = SubplotHost(fig, 1, 3, i+1) fig.add_subplot(ax1) ax2 = ParasiteAxesAuxTrans(ax1, IdentityTransform()) ax1.parasites.append(ax2) getattr(ax2, name)(xx, yy, data) ax1.set_xlim((0, 5)) ax1.set_ylim((0, 5)) ax2.contour(xx, yy, data, colors='k')
def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper) ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) ax1.axis["right"].get_helper().nth_coord_ticks=0 ax1.axis["bottom"].get_helper().nth_coord_ticks=1 fig.add_subplot(ax1) ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") ax1.parasites.append(ax2) intp = cbook.simple_linear_interpolation ax2.plot(intp(np.array([0, 30]), 50), intp(np.array([10., 10.]), 50)) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True)
def test_ParasiteAxesAuxTrans(): data = np.ones((6, 6)) data[2, 2] = 2 data[0, :] = 0 data[-2, :] = 0 data[:, 0] = 0 data[:, -2] = 0 x = np.arange(6) y = np.arange(6) xx, yy = np.meshgrid(x, y) funcnames = ['pcolor', 'pcolormesh', 'contourf'] fig = plt.figure() for i, name in enumerate(funcnames): ax1 = SubplotHost(fig, 1, 3, i + 1) fig.add_subplot(ax1) ax2 = ParasiteAxesAuxTrans(ax1, IdentityTransform()) ax1.parasites.append(ax2) getattr(ax2, name)(xx, yy, data) ax1.set_xlim((0, 5)) ax1.set_ylim((0, 5)) ax2.contour(xx, yy, data, colors='k')
def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle(50, 50, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) # Find a grid values appropriate for the coordinate (degree, # minute, second). tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) ax1.axis["left"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks=0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks=0 ax1.axis["left"].get_helper().nth_coord_ticks=0 fig.add_subplot(ax1) ax1.quiver(0,0,50,50,angles='xy',scale_units='xy',scale=1) ax1.set_aspect(1.) ax1.set_xlim(-100, 100) ax1.set_ylim(-100, 100) ax1.grid(True)
def test_ParasiteAxesAuxTrans(): # Remove this line when this test image is regenerated. plt.rcParams['pcolormesh.snap'] = False data = np.ones((6, 6)) data[2, 2] = 2 data[0, :] = 0 data[-2, :] = 0 data[:, 0] = 0 data[:, -2] = 0 x = np.arange(6) y = np.arange(6) xx, yy = np.meshgrid(x, y) funcnames = ['pcolor', 'pcolormesh', 'contourf'] fig = plt.figure() for i, name in enumerate(funcnames): ax1 = SubplotHost(fig, 1, 3, i + 1) fig.add_subplot(ax1) ax2 = ParasiteAxes(ax1, IdentityTransform()) ax1.parasites.append(ax2) if name.startswith('pcolor'): getattr(ax2, name)(xx, yy, data[:-1, :-1]) else: getattr(ax2, name)(xx, yy, data) ax1.set_xlim((0, 5)) ax1.set_ylim((0, 5)) ax2.contour(xx, yy, data, colors='k')
def test_custom_transform(): class MyTransform(Transform): input_dims = output_dims = 2 def __init__(self, resolution): """ Resolution is the number of steps to interpolate between each input line segment to approximate its path in transformed space. """ Transform.__init__(self) self._resolution = resolution def transform(self, ll): x, y = ll.T return np.column_stack([x, y - x]) transform_non_affine = transform def transform_path(self, path): ipath = path.interpolated(self._resolution) return Path(self.transform(ipath.vertices), ipath.codes) transform_path_non_affine = transform_path def inverted(self): return MyTransformInv(self._resolution) class MyTransformInv(Transform): input_dims = output_dims = 2 def __init__(self, resolution): Transform.__init__(self) self._resolution = resolution def transform(self, ll): x, y = ll.T return np.column_stack([x, y + x]) def inverted(self): return MyTransform(self._resolution) fig = plt.figure() SubplotHost = host_subplot_class_factory(Axes) tr = MyTransform(1) grid_helper = GridHelperCurveLinear(tr) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) ax2 = ParasiteAxes(ax1, tr, viewlim_mode="equal") ax1.parasites.append(ax2) ax2.plot([3, 6], [5.0, 10.]) ax1.set_aspect(1.) ax1.set_xlim(0, 10) ax1.set_ylim(0, 10) ax1.grid(True)
def curvelinear_test2(fig, rect=111): """ Polar projection, but in a rectangular box. """ # see demo_curvelinear_grid.py for details tr = Affine2D().translate(0, 90) + Affine2D().scale(np.pi / 180., 1.) + \ PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle( 10, 60, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(-90, np.inf), ) # Changes theta gridline count grid_locator1 = angle_helper.LocatorHMS(12) grid_locator2 = angle_helper.LocatorDMS(6) tick_formatter1 = angle_helper.FormatterHMS() tick_formatter2 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=grid_locator2, tick_formatter1=tick_formatter1, tick_formatter2=tick_formatter2) ax1 = SubplotHost(fig, rect, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) ax1.axis["bottom"].major_ticklabels.set_visible(True) # let right and bottom axis show ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 ax1.axis["bottom"].get_helper().nth_coord_ticks = 0 # fig.add_subplot(ax1) grid_helper = ax1.get_grid_helper() # You may or may not need these - they set the view window explicitly # rather than using the default as determined by matplotlib with extreme # finder. ax1.set_aspect(1.) ax1.set_xlim(-4, 25) # moves the origin left-right in ax1 ax1.set_ylim(-2.5, 30) # moves the origin up-down ax1.set_ylabel('$DEC\,(^{\circ})$') ax1.set_xlabel('$RA\,(h)$') ax1.grid(True) # ax1.grid(linestyle='--', which='x') # either keyword applies to both # ax1.grid(linestyle=':', which='y') # sets of gridlines return ax1, tr
def test_polar_box(): fig = plt.figure(figsize=(5, 5)) # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf)) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1) axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper()._extremes = 2, 12 ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1) axis.label.set_text("Test 2") axis.get_helper()._extremes = -180, 90 # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") assert ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50)) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True)
def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ global ax1 import numpy as np import mpl_toolkits.axisartist.angle_helper as angle_helper from matplotlib.projections import PolarAxes from matplotlib.transforms import Affine2D from mpl_toolkits.axisartist import SubplotHost from mpl_toolkits.axisartist import GridHelperCurveLinear # see demo_curvelinear_grid.py for details tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) # Now creates floating axis #grid_helper = ax1.get_grid_helper() # floating axis whose first coordinate (theta) is fixed at 60 ax1.axis["lat"] = axis = ax1.new_floating_axis(0, 60) axis.label.set_text(r"$\theta = 60^{\circ}$") axis.label.set_visible(True) # floating axis whose second coordinate (r) is fixed at 6 ax1.axis["lon"] = axis = ax1.new_floating_axis(1, 6) axis.label.set_text(r"$r = 6$") ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True)
def curvelinear_test2(fig): """ Polar projection, but in a rectangular box. """ # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi/180, 1) + PolarAxes.PolarTransform() # Polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). extreme_finder = angle_helper.ExtremeFinderCycle( nx=20, ny=20, # Number of sampling points in each direction. lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) # Find grid values appropriate for the coordinate (degree, minute, second). grid_locator1 = angle_helper.LocatorDMS(12) # Use an appropriate formatter. Note that the acceptable Locator and # Formatter classes are a bit different than that of Matplotlib, which # cannot directly be used here (this may be possible in the future). tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear( tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) ax1.set_aspect(1) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True, zorder=0) # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") # note that ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) ax2.plot(np.linspace(0, 30, 51), np.linspace(10, 10, 51), linewidth=2)
def curvelinear_test(fig): """Polar projection, but in a rectangular box. """ # 创建一个极坐标变换。PolarAxes.PolarTransform使用弧度,但本例 # 要设置的坐标系中角度的单位为度 tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # 极坐标投影涉及到周期,在坐标上也有限制,需要一种特殊的方法来找到 # 坐标的最小值和最大值 extreme_finder = angle_helper.ExtremeFinderCycle( 20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) # 找到适合坐标的网格值(度、分、秒) grid_locator1 = angle_helper.LocatorDMS(12) # 使用适当的Formatter。请注意,可接受的Locator和Formatter类 # 与Matplotlib中的相应类稍有不同,后者目前还不能直接在这里使用 tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) # 创建浮动坐标轴 # 浮动坐标轴的第一个坐标(theta)指定为60度 ax1.axis["lat"] = axis = ax1.new_floating_axis(0, 60) axis.label.set_text(r"$\theta = 60^{\circ}$") axis.label.set_visible(True) # 浮动坐标轴的第二个坐标(r)指定为6 ax1.axis["lon"] = axis = ax1.new_floating_axis(1, 6) axis.label.set_text(r"$r = 6$") ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True)
def SemiPolarPlot(fig): # see demo_curvelinear_grid.py for details tr = Affine2D().scale(pi/180., 1.) + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, 1), ) grid_locator1 = angle_helper.LocatorDMS(11) grid_locator2 = FixedLocator([0.25, 0.5, 1., 0.75]) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=grid_locator2, tick_formatter1=tick_formatter1, tick_formatter2=None ) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) ax1.axis["top"].set_visible(False) ax1.axis["right"].set_visible(False) ax1.axis["bottom"].set_visible(False) ax1.axis["lon"] = ax1.new_floating_axis(1, 1) ax1.set_aspect(1) ax1.set_xlim(0, 2) ax1.set_ylim(-1., 1.) ax1.grid(True) curved_ax = ax1.get_aux_axes(tr) curved_ax.patch = ax1.patch # for aux_ax to have a clip path as in ax ax1.patch.zorder=0.9 return ax1, curved_ax
def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) # Find a grid values appropriate for the coordinate (degree, # minute, second). tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") # note that ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) intp = cbook.simple_linear_interpolation ax2.plot(intp(np.array([0, 30]), 50), intp(np.array([10., 10.]), 50), linewidth=2.0) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True, zorder=0)
def plotGsrResidue(theta, phi, residue, optTheta, optPhi, mvabTheta=None, mvabPhi=None, mvubTheta=None, mvubPhi=None): fig = figure() fig.clf() # some matplotlib setup stuff which I don't fully understand but it works tr = Affine2D().scale(pi/180., 1.) + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) ax1.axis["right"].get_helper().nth_coord_ticks=0 ax1.axis["bottom"].get_helper().nth_coord_ticks=1 # draw the filled contoured map in polar coordinates ax1.contour(transpose(mat(theta))*mat(cos(phi*pi/180)), transpose(mat(theta))*mat(sin(phi*pi/180)), 1/transpose(reshape(residue, (phi.size,-1))), 100, lw=0.1) cc = ax1.contourf(transpose(mat(theta))*mat(cos(phi*pi/180)), transpose(mat(theta))*mat(sin(phi*pi/180)), 1/transpose(reshape(residue, (phi.size,-1))), 100) # remove gaps between the contour lines for c in cc.collections: c.set_antialiased(False) # show the MVAB direction if mvabTheta is not None and mvabPhi is not None: ax1.plot(mvabTheta*cos(mvabPhi*pi/180), mvabTheta*sin(mvabPhi*pi/180), 'sk', markersize=8) # show the MVUB direction if mvubTheta is not None and mvubPhi is not None: ax1.plot(mvubTheta*cos(mvubPhi*pi/180), mvubTheta*sin(mvubPhi*pi/180), 'dk', markersize=8) # show the optimal direction ax1.plot(optTheta*cos(optPhi*pi/180), optTheta*sin(optPhi*pi/180), '.k', markersize=15) # aspect and initial axes limits ax1.set_aspect(1.) ax1.set_xlim(-90, 90) ax1.set_ylim(-90, 90) # add grid ax1.grid(True) # add colobar cb = colorbar(cc, pad=0.07) cb.locator = MaxNLocator(14) cb.update_ticks() cb.set_label(r"$1/\tilde{\mathcal{R}}$") # save if toSave: savefig(resultsDir+'/eps/gsr_ResidualMap.eps', format='eps') savefig(resultsDir+'/png/gsr_ResidualMap.png', format='png')
def curvelinear_test2(fig, gs=None, xcenter=0.0, ycenter=17.3, xwidth=1.5, ywidth=1.5, xlabel=xlabel, ylabel=ylabel, xgrid_density=8, ygrid_density=5): """ polar projection, but in a rectangular box. """ tr = Affine2D().translate(0,90) tr += Affine2D().scale(np.pi/180., 1.) tr += PolarAxes.PolarTransform() tr += Affine2D().rotate(1.34) # This rotates the grid extreme_finder = angle_helper.ExtremeFinderCycle(10, 60, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (-90, np.inf), ) grid_locator1 = angle_helper.LocatorHMS(xgrid_density) #changes theta gridline count tick_formatter1 = angle_helper.FormatterHMS() grid_locator2 = angle_helper.LocatorDMS(ygrid_density) #changes theta gridline count tick_formatter2 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=grid_locator2, tick_formatter1=tick_formatter1, tick_formatter2=tick_formatter2 ) # ax1 = SubplotHost(fig, rect, grid_helper=grid_helper) if gs is None: ax1 = SubplotHost(fig, 111, grid_helper=grid_helper) else: ax1 = SubplotHost(fig, gs, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(False) ax1.axis["top"].major_ticklabels.set_visible(False) ax1.axis["bottom"].major_ticklabels.set_visible(True) #Turn off? # let right and bottom axis show ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks=0 ax1.axis["bottom"].get_helper().nth_coord_ticks=0 fig.add_subplot(ax1) grid_helper = ax1.get_grid_helper() # These move the grid ax1.set_xlim(xcenter-xwidth, xcenter+xwidth) # moves the origin left-right in ax1 ax1.set_ylim(ycenter-ywidth, ycenter+ywidth) # moves the origin up-down # ax1.set_xlim(-1.5, 1.4) # ax1.set_ylim(15.8, 18.8) if xlabel is not None: ax1.set_xlabel(xlabel) if ylabel is not None: ax1.set_ylabel(ylabel) # ax1.set_ylabel('Declination') # ax1.set_xlabel('Right Ascension') ax1.grid(True, linestyle='-') #ax1.grid(linestyle='--', which='x') # either keyword applies to both #ax1.grid(linestyle=':', which='y') # sets of gridlines return ax1,tr
def curvelinear_test2(fig): """ polar projection, but in a rectangular box. """ # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle( 20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) # Find a grid values appropriate for the coordinate (degree, # minute, second). tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") # note that ax2.transData == tr + ax1.transData # Anthing you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) intp = cbook.simple_linear_interpolation ax2.plot(intp(np.array([0, 30]), 50), intp(np.array([10., 10.]), 50), linewidth=2.0) ax1.set_aspect(1.) ax1.set_xlim(-5, 12) ax1.set_ylim(-5, 10) ax1.grid(True, zorder=0)
def curvelinear_test2(fig, gs=None, xcenter=0.0, ycenter=17.3, xwidth=1.5, ywidth=1.5, rot_angle=0.0, xlabel=xlabel, ylabel=ylabel, xgrid_density=8, ygrid_density=5): """ polar projection, but in a rectangular box. """ tr = Affine2D().translate(0,90) tr += Affine2D().scale(np.pi/180., 1.) tr += PolarAxes.PolarTransform() tr += Affine2D().rotate(rot_angle) # This rotates the grid extreme_finder = angle_helper.ExtremeFinderCycle(10, 60, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (-90, np.inf), ) grid_locator1 = angle_helper.LocatorHMS(xgrid_density) #changes theta gridline count tick_formatter1 = angle_helper.FormatterHMS() grid_locator2 = angle_helper.LocatorDMS(ygrid_density) #changes theta gridline count tick_formatter2 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=grid_locator2, tick_formatter1=tick_formatter1, tick_formatter2=tick_formatter2 ) # ax1 = SubplotHost(fig, rect, grid_helper=grid_helper) if gs is None: ax1 = SubplotHost(fig, 111, grid_helper=grid_helper) else: ax1 = SubplotHost(fig, gs, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(False) ax1.axis["top"].major_ticklabels.set_visible(False) ax1.axis["bottom"].major_ticklabels.set_visible(True) #Turn off? # let right and bottom axis show ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks=0 ax1.axis["bottom"].get_helper().nth_coord_ticks=0 fig.add_subplot(ax1) grid_helper = ax1.get_grid_helper() # These move the grid ax1.set_xlim(xcenter-xwidth, xcenter+xwidth) # moves the origin left-right in ax1 ax1.set_ylim(ycenter-ywidth, ycenter+ywidth) # moves the origin up-down if xlabel is not None: ax1.set_xlabel(xlabel) if ylabel is not None: ax1.set_ylabel(ylabel) ax1.grid(True, linestyle='-') return ax1,tr
def polar_stuff(fig, telescope): # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.).translate( +np.pi / 2., 0) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction n = 1 extreme_finder = angle_helper.ExtremeFinderCycle( n, n, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(-90, 90), ) grid_locator1 = angle_helper.LocatorDMS(12) # Find a grid values appropriate for the coordinate (degree, # minute, second). tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) # make ticklabels of right and top axis visible. ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) ax1.axis["right"].get_helper().nth_coord_ticks = 0 # let bottom axis shows ticklabels for 2nd coordinate (radius) ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 fig.add_subplot(ax1) # A parasite axes with given transform ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") # note that ax2.transData == tr + ax1.transData # Anything you draw in ax2 will match the ticks and grids of ax1. ax1.parasites.append(ax2) # intp = cbook.simple_linear_interpolation #ax2.plot(intp(np.array([0, 30]), 50), # intp(np.array([10., 10.]), 50), # linewidth=2.0) x = np.rad2deg(telescope.az.value) * np.cos(telescope.alt.value) y = np.rad2deg(telescope.alt.value) circle = plt.Circle( (np.rad2deg(telescope.az.value - np.pi) * np.sin(telescope.alt.value), np.rad2deg(-telescope.alt.value * np.cos( (telescope.az.value - np.pi)))), radius=7.7 / 2, color="red", alpha=0.2, ) circle = plt.Circle( (x, y), radius=7.7 / 2, color="red", alpha=0.2, ) ax1.add_artist(circle) # point = ax1.scatter(x, y, c="b", s=20, zorder=10, transform=ax2.transData) ax2.annotate(1, (x, y), fontsize=15, xytext=(4, 4), textcoords='offset pixels') ax1.set_xlim(-180, 180) ax1.set_ylim(0, 90) ax1.set_aspect(1.) ax1.grid(True, zorder=0) ax1.set_xlabel("Azimuth in degrees", fontsize=20) ax1.set_ylabel("Zenith in degrees", fontsize=20) plt.show() return fig
class PolarPlot: ''' plots heading angle and signal strength in polar coor in 2d''' def __init__(self): plt.ion() self.fig = plt.figure(num=2, figsize=(10,7)) tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform() # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle(50, 50, lon_cycle = 360, lat_cycle = None, lon_minmax = None, lat_minmax = (0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(15) tick_formatter1 = angle_helper.FormatterDMS() # And also uses an appropriate formatter. Note that,the # acceptable Locator and Formatter class is a bit different than # that of mpl's, and you cannot directly use mpl's Locator and # Formatter here (but may be possible in the future). grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1 ) self.ax1 = SubplotHost(self.fig, 1, 1, 1, grid_helper=grid_helper) # make ticklabels of right and top axis visible. self.ax1.axis["right"].major_ticklabels.set_visible(True) self.ax1.axis["top"].major_ticklabels.set_visible(True) self.ax1.axis["left"].major_ticklabels.set_visible(True) # let right axis shows ticklabels for 1st coordinate (angle) self.ax1.axis["right"].get_helper().nth_coord_ticks=0 # let bottom axis shows ticklabels for 1st coordinate (angle) self.ax1.axis["bottom"].get_helper().nth_coord_ticks=0 self.ax1.axis["left"].get_helper().nth_coord_ticks=0 temp = self.ax1.set_title('Signal strength & heading polar plots') temp.set_y(1.05) self.ax1.grid(True) # insert x and y axises self.ax = self.fig.add_subplot(self.ax1) self.ax1.spines['left'].set_position('center') self.ax1.spines['right'].set_color('red') self.ax1.spines['bottom'].set_position('center') self.ax1.spines['top'].set_color('none') self.ax1.spines['left'].set_smart_bounds(True) self.ax1.spines['bottom'].set_smart_bounds(True) self.ax1.xaxis.set_ticks_position('bottom') self.ax1.yaxis.set_ticks_position('left') self.ax1.axhline(linewidth=2, color='blue') self.ax1.axvline(linewidth=2, color='blue') # label x and y axises manually ticks = np.linspace(0, 255, 6) offset = np.zeros([1,255]) for i in range(1,5): self.ax1.annotate(str(ticks[i]),size=10, xy=(ticks[i], -15)) blah = self.ax1.plot(ticks[i],0, 'bo') self.ax1.annotate(str(ticks[i]),size=10, xy=(5, ticks[i])) blah = self.ax1.plot(0,ticks[i], 'bo') # annotate figure bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9) # self.annotation = self.ax1.annotate('init',size=20, xy=(100, 100), bbox = bbox_props) self.annotation = plt.figtext(0.02, 0.9, 'rssi = ', size=20, alpha = 0.9, bbox = bbox_props) self.Freq = plt.figtext(0.85, 0.85, 'freq = ???', size=10, alpha = 0.9, bbox = bbox_props) self.Freq = plt.figtext(0.85, 0.9, 'Horizontal Plane', size=10, alpha = 0.9, bbox = bbox_props) # initialize arrow self.quiverLine = self.ax1.quiver(0,0,50,50,angles='xy',scale_units='xy',scale=1) self.ax1.set_aspect(1.) self.ax1.set_xlim(-255, 255) self.ax1.set_ylim(-255, 255) # initialize mesh plot self.xdata = [] self.ydata = [] self.polarline, = self.ax1.plot(self.xdata,self.ydata) def update(self, signalStrength, yaw): U = signalStrength*cos(yaw*pi/180) V = signalStrength*sin(yaw*pi/180) self.xdata.append(U) self.ydata.append(V) self.polarline.set_data(self.xdata,self.ydata) self.quiverLine.set_UVC(U,V) self.annotation.set_text('rssi = ' + str(signalStrength)) plt.draw()
def test_axis_direction(): fig = plt.figure(figsize=(5, 5)) # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle( 20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) for axis in ax1.axis.values(): axis.set_visible(False) fig.add_subplot(ax1) ax1.axis["lat1"] = axis = grid_helper.new_floating_axis( 0, 130, axes=ax1, axis_direction="left") axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper()._extremes = 0.001, 10 ax1.axis["lat2"] = axis = grid_helper.new_floating_axis( 0, 50, axes=ax1, axis_direction="right") axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper()._extremes = 0.001, 10 ax1.axis["lon"] = axis = grid_helper.new_floating_axis( 1, 10, axes=ax1, axis_direction="bottom") axis.label.set_text("Test 2") axis.get_helper()._extremes = 50, 130 axis.major_ticklabels.set_axis_direction("top") axis.label.set_axis_direction("top") grid_helper.grid_finder.grid_locator1.den = 5 grid_helper.grid_finder.grid_locator2._nbins = 5 ax1.set_aspect(1.) ax1.set_xlim(-8, 8) ax1.set_ylim(-4, 12) ax1.grid(True)
def plotGsrResidue(theta, phi, residue, optTheta, optPhi, mvabTheta=None, mvabPhi=None, mvubTheta=None, mvubPhi=None): fig = figure() fig.clf() # some matplotlib setup stuff which I don't fully understand but it works tr = Affine2D().scale(pi / 180., 1.) + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle( 20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) ax1.axis["right"].major_ticklabels.set_visible(True) ax1.axis["top"].major_ticklabels.set_visible(True) ax1.axis["right"].get_helper().nth_coord_ticks = 0 ax1.axis["bottom"].get_helper().nth_coord_ticks = 1 # draw the filled contoured map in polar coordinates ax1.contour(transpose(mat(theta)) * mat(cos(phi * pi / 180)), transpose(mat(theta)) * mat(sin(phi * pi / 180)), 1 / transpose(reshape(residue, (phi.size, -1))), 100, lw=0.1) cc = ax1.contourf( transpose(mat(theta)) * mat(cos(phi * pi / 180)), transpose(mat(theta)) * mat(sin(phi * pi / 180)), 1 / transpose(reshape(residue, (phi.size, -1))), 100) # remove gaps between the contour lines for c in cc.collections: c.set_antialiased(False) # show the MVAB direction if mvabTheta is not None and mvabPhi is not None: ax1.plot(mvabTheta * cos(mvabPhi * pi / 180), mvabTheta * sin(mvabPhi * pi / 180), 'sk', markersize=8) # show the MVUB direction if mvubTheta is not None and mvubPhi is not None: ax1.plot(mvubTheta * cos(mvubPhi * pi / 180), mvubTheta * sin(mvubPhi * pi / 180), 'dk', markersize=8) # show the optimal direction ax1.plot(optTheta * cos(optPhi * pi / 180), optTheta * sin(optPhi * pi / 180), '.k', markersize=15) # aspect and initial axes limits ax1.set_aspect(1.) ax1.set_xlim(-90, 90) ax1.set_ylim(-90, 90) # add grid ax1.grid(True) # add colobar cb = colorbar(cc, pad=0.07) cb.locator = MaxNLocator(14) cb.update_ticks() cb.set_label(r"$1/\tilde{\mathcal{R}}$") # save if toSave: savefig(resultsDir + '/eps/gsr_ResidualMap.eps', format='eps') savefig(resultsDir + '/png/gsr_ResidualMap.png', format='png')
def test_axis_direction(): fig = plt.figure(figsize=(5, 5)) # PolarAxes.PolarTransform takes radian. However, we want our coordinate # system in degree tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform() # polar projection, which involves cycle, and also has limits in # its coordinates, needs a special method to find the extremes # (min, max of the coordinate within the view). # 20, 20 : number of sampling points along x, y direction extreme_finder = angle_helper.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(0, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(12) tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, tick_formatter1=tick_formatter1) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) for axis in ax1.axis.values(): axis.set_visible(False) fig.add_subplot(ax1) ax1.axis["lat1"] = axis = grid_helper.new_floating_axis( 0, 130, axes=ax1, axis_direction="left") axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper()._extremes = 0.001, 10 ax1.axis["lat2"] = axis = grid_helper.new_floating_axis( 0, 50, axes=ax1, axis_direction="right") axis.label.set_text("Test") axis.label.set_visible(True) axis.get_helper()._extremes = 0.001, 10 ax1.axis["lon"] = axis = grid_helper.new_floating_axis( 1, 10, axes=ax1, axis_direction="bottom") axis.label.set_text("Test 2") axis.get_helper()._extremes = 50, 130 axis.major_ticklabels.set_axis_direction("top") axis.label.set_axis_direction("top") grid_helper.grid_finder.grid_locator1.den = 5 grid_helper.grid_finder.grid_locator2._nbins = 5 ax1.set_aspect(1.) ax1.set_xlim(-8, 8) ax1.set_ylim(-4, 12) ax1.grid(True)
def test_custom_transform(): class MyTransform(Transform): input_dims = 2 output_dims = 2 is_separable = False def __init__(self, resolution): """ Resolution is the number of steps to interpolate between each input line segment to approximate its path in transformed space. """ Transform.__init__(self) self._resolution = resolution def transform(self, ll): x, y = ll.T return np.column_stack([x, y - x]) transform_non_affine = transform def transform_path(self, path): ipath = path.interpolated(self._resolution) return Path(self.transform(ipath.vertices), ipath.codes) transform_path_non_affine = transform_path def inverted(self): return MyTransformInv(self._resolution) class MyTransformInv(Transform): input_dims = 2 output_dims = 2 is_separable = False def __init__(self, resolution): Transform.__init__(self) self._resolution = resolution def transform(self, ll): x, y = ll.T return np.column_stack([x, y + x]) def inverted(self): return MyTransform(self._resolution) fig = plt.figure() SubplotHost = host_subplot_class_factory(Axes) tr = MyTransform(1) grid_helper = GridHelperCurveLinear(tr) ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper) fig.add_subplot(ax1) ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal") ax1.parasites.append(ax2) ax2.plot([3, 6], [5.0, 10.]) ax1.set_aspect(1.) ax1.set_xlim(0, 10) ax1.set_ylim(0, 10) ax1.grid(True)
def get_smith(fig, rect=111, plot_impedance=True, plot_ticks=False, plot_admittance=False, plot_labels=False): '''Function which returns an axis with a blank smith chart, provide a figure and optional rect coords''' #Example use: # fig3 = plt.figure(3) # ax31 = pySmith.get_smith(fig3, 221) # ax31.plot(np.real(filtsmatrix[0,:,0,0]),np.imag(filtsmatrix[0,:,0,0])) # ax32= pySmith.get_smith(fig3, 222) # ax32.plot(np.real(filtsmatrix[0,:,0,1]),np.imag(filtsmatrix[0,:,0,1])) # ax33 = pySmith.get_smith(fig3, 223) # ax33.plot(np.real(filtsmatrix[0,:,1,0]),np.imag(filtsmatrix[0,:,1,0])) # ax34 = pySmith.get_smith(fig3, 224) # ax34.plot(np.real(filtsmatrix[0,:,1,1]),np.imag(filtsmatrix[0,:,1,1])) try: #font definition font = { 'family': 'sans-serif', 'color': 'black', 'weight': 'normal', 'size': 16, } #plot radial tick marks tr = PolarAxes.PolarTransform() num_thetas = 8 #*3 #12 gives in 30 deg intervals, 8 in 45 deg, 24 in 15deg thetas = np.linspace(0.0, math.pi * (1 - 2.0 / num_thetas), num_thetas // 2) angle_ticks = [] #(0, r"$0$"), for theta in thetas: angle_info = [] angle_info.append(theta) deg = int(round(180.0 * theta / math.pi)) angle_info.append(r'%d$^{\circ}$' % deg) angle_ticks.append(angle_info) grid_locator1 = FixedLocator([v for v, s in angle_ticks]) tick_formatter1 = DictFormatter(dict(angle_ticks)) thetas2 = np.linspace(math.pi, 2 * math.pi * (1 - 1.0 / num_thetas), num_thetas // 2) angle_ticks2 = [] #(0, r"$0$"), for theta in thetas2: angle_info = [] angle_info.append(theta) deg = int(round(180.0 * theta / math.pi)) angle_info.append(r'%d$^{\circ}$' % deg) angle_ticks2.append(angle_info) grid_locator2 = FixedLocator([v for v, s in angle_ticks2]) tick_formatter2 = DictFormatter(dict(angle_ticks2)) grid_helper1 = floating_axes.GridHelperCurveLinear( tr, extremes=(math.pi, 0, 1, 0), grid_locator1=grid_locator1, #grid_locator2=grid_locator2, tick_formatter1=tick_formatter1 #, #tick_formatter2=None, ) grid_helper2 = floating_axes.GridHelperCurveLinear( tr, extremes=(2 * math.pi, math.pi, 1, 0), grid_locator1=grid_locator2, #grid_locator2=grid_locator2, tick_formatter1=tick_formatter2 #, #tick_formatter2=None, ) r1 = int(math.floor(rect / 100)) r2 = int(math.floor((rect - 100 * r1) / 10)) r3 = int(math.floor((rect - 100 * r1 - 10 * r2))) ax = SubplotHost(fig, r1, r2, r3, grid_helper=grid_helper1) ax2 = SubplotHost(fig, r1, r2, r3, grid_helper=grid_helper2) #ax.set_aspect(math.pi/180.0,'datalim') fig.add_subplot(ax) fig.add_subplot(ax2) ax.axis["bottom"].major_ticklabels.set_axis_direction("top") ax.axis["bottom"].major_ticklabels.set_fontsize(13) ax.axis["left"].set_visible(False) ax.axis["left"].toggle(all=False) ax.axis["right"].set_visible(False) ax.axis["right"].toggle(all=False) ax.axis["top"].set_visible(False) ax.axis["top"].toggle(all=False) ax.patch.set_visible(False) ax2.axis["bottom"].major_ticklabels.set_fontsize(13) ax2.axis["left"].set_visible(False) ax2.axis["left"].toggle(all=False) ax2.axis["right"].set_visible(False) ax2.axis["right"].toggle(all=False) ax2.axis["top"].set_visible(False) ax2.axis["top"].toggle(all=False) #ax = fig.add_subplot(rect) #remove axis labels ax.axis('off') #set aspect ratio to 1 ax.set_aspect(1) #, 'datalim') #set limits ax.set_xlim([-1.02, 1.02]) ax.set_ylim([-1.02, 1.02]) #remove axis labels ax2.axis('off') #set aspect ratio to 1 ax2.set_aspect(1) #,'datalim') #set limits ax2.set_xlim([-1.02, 1.02]) ax2.set_ylim([-1.02, 1.02]) ax2.patch.set_visible(False) if plot_impedance: #make lines of constant resistance res_log = np.linspace(-4, 4, 9) react_log = np.linspace(-5, 5, 2001) res = 2**res_log react = 10**react_log react2 = np.append(-1.0 * react[::-1], np.array([0])) react = np.append(react2, react) for r in res: z = 1j * react + r gam = (z - 1) / (z + 1) x = np.real(gam) y = np.imag(gam) if abs(r - 1) > 1e-6: ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25) else: ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4) #make lines of constant reactance react_log = np.linspace(-3, 3, 7) res_log = np.linspace(-5, 5, 2001) res = 10**res_log react = 2**react_log react2 = np.append(-1.0 * react[::-1], np.array([0])) react = np.append(react2, react) for chi in react: z = 1j * chi + res gam = (z - 1) / (z + 1) x = np.real(gam) y = np.imag(gam) if abs(chi - 1) > 1e-6 and abs(chi + 1) > 1e-6 and abs(chi) > 1e-6: ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25) else: ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4) if plot_admittance: #make lines of constant conductance res_log = np.linspace(-4, 4, 9) react_log = np.linspace(-5, 5, 2001) res = 2**res_log react = 10**react_log react = np.append(-1.0 * react[::-1], react) for r in res: y = 1.0 / r + 1.0 / (1j * react) gam = (1.0 / y - 1) / (1.0 / y + 1) x = np.real(gam) y = np.imag(gam) if abs(r - 1) > 1e-6: ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25) else: ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4) #make lines of constant susceptance react_log = np.linspace(-3, 3, 7) res_log = np.linspace(-5, 5, 2001) res = 10**res_log react = 2**react_log react = np.append(-1.0 * react[::-1], react) for chi in react: y = 1.0 / (1j * chi) + 1.0 / res gam = (1.0 / y - 1) / (1.0 / y + 1) x = np.real(gam) y = np.imag(gam) if abs(chi - 1) > 1e-6 and abs(chi + 1) > 1e-6: ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25) else: ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4) y = 1.0 / res gam = (1.0 / y - 1) / (1.0 / y + 1) x = np.real(gam) y = np.imag(gam) ax.plot(x, y, c='k', linewidth=1.0, alpha=0.75) if plot_labels: #naive text placement only works for default python figure size with 1 subplot ax.text(-0.15, 1.04, r'$\Gamma$ = 1j', fontdict=font) ax.text(-1.4, -0.035, r'$\Gamma$ = -1', fontdict=font) ax.text(-0.17, -1.11, r'$\Gamma$ = -1j', fontdict=font) ax.text(1.04, -0.035, r'$\Gamma$ = 1', fontdict=font) if plot_ticks: num_minorticks = 3 num_thetas = num_thetas * (num_minorticks + 1) thetas = np.linspace(0, 2.0 * math.pi * (1.0 - 1.0 / num_thetas), num_thetas) r_inner = 0.985 r_outer = 1.0 rads = np.linspace(r_inner, r_outer, 2) ticknum = 0 for theta in thetas: x = rads * np.cos(theta) y = rads * np.sin(theta) if ticknum % (num_minorticks + 1) != 0: ax.plot(x, y, c='k', linewidth=1.0, alpha=1.0) ticknum = ticknum + 1 return ax except Exception as e: print('\nError in %s' % inspect.stack()[0][3]) print(e) exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] print(exc_type, fname, exc_tb.tb_lineno)