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 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_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 create_axes_nonorthogonal(self, transform): self.clear_figure() self.set_nonorthogonal_transform(transform) self.ax = CurveLinearSubPlot(self.fig, 1, 1, 1, grid_helper=GridHelperCurveLinear( (transform.tr, transform.inv_tr))) # don't redraw on zoom as the data is rebinned and has to be redrawn again anyway self.enable_zoom_on_mouse_scroll(redraw=False) self.set_grid_on() self.fig.add_subplot(self.ax) self.plot_MDH = self.plot_MDH_nonorthogonal self.canvas.draw_idle()
def curvelinear_test2(fig): """Polar projection, but in a rectangular box.""" # 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 = fig.add_subplot(axes_class=HostAxes, grid_helper=grid_helper) # Now creates floating axis # 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 create_cg(fig=None, subplot=111, rot=-450, scale=-1, angular_spacing=10, radial_spacing=10, latmin=0, lon_cycle=360): """ Helper function to create curvelinear grid The function makes use of the Matplotlib AXISARTIST namespace `mpl_toolkits.axisartist \ <https://matplotlib.org/mpl_toolkits/axes_grid/users/axisartist.html>`_. Here are some limitations to normal Matplotlib Axes. While using the Matplotlib `AxesGrid Toolkit \ <https://matplotlib.org/mpl_toolkits/axes_grid/index.html>`_ most of the limitations can be overcome. See `Matplotlib AxesGrid Toolkit User’s Guide \ <https://matplotlib.org/mpl_toolkits/axes_grid/users/index.html>`_. Parameters ---------- fig : matplotlib Figure object If given, the PPI/RHI will be plotted into this figure object. Axes are created as needed. If None a new figure object will be created or current figure will be used, depending on "subplot". subplot : :class:`matplotlib:matplotlib.gridspec.GridSpec`, \ matplotlib grid definition nrows/ncols/plotnumber, see examples section defaults to '111', only one subplot rot : float Rotation of the source data in degrees, defaults to -450 for PPI, use 0 for RHI scale : float Scale of source data, defaults to -1. for PPI, use 1 for RHI angular_spacing : float Spacing of the angular grid, defaults to 10. radial_spacing : float Spacing of the radial grid, defaults to 10. latmin : float Startvalue for radial grid, defaults to 0. lon_cycle : float Angular cycle, defaults to 360. Returns ------- cgax : matplotlib toolkit axisartist Axes object curvelinear Axes (r-theta-grid) caax : matplotlib Axes object (twin to cgax) Cartesian Axes (x-y-grid) for plotting cartesian data paax : matplotlib Axes object (parasite to cgax) The parasite axes object for plotting polar data """ # create transformation # rotate tr_rotate = Affine2D().translate(rot, 0) # scale tr_scale = Affine2D().scale(scale * np.pi / 180, 1) # polar tr_polar = PolarAxes.PolarTransform() tr = tr_rotate + tr_scale + tr_polar # build up curvelinear grid extreme_finder = ah.ExtremeFinderCycle( 360, 360, lon_cycle=lon_cycle, lat_cycle=None, lon_minmax=None, lat_minmax=(latmin, np.inf), ) # locator and formatter for angular annotation grid_locator1 = ah.LocatorDMS(lon_cycle // angular_spacing) tick_formatter1 = ah.FormatterDMS() # grid_helper for curvelinear grid grid_helper = GridHelperCurveLinear( tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=None, tick_formatter1=tick_formatter1, tick_formatter2=None, ) # try to set nice locations for radial gridlines grid_locator2 = grid_helper.grid_finder.grid_locator2 grid_locator2._nbins = (radial_spacing * 2 + 1) // np.sqrt(2) # if there is no figure object given if fig is None: # create new figure if there is only one subplot if subplot == 111: fig = pl.figure() # otherwise get current figure or create new figure else: fig = pl.gcf() # generate Axis cgax = SubplotHost(fig, subplot, grid_helper=grid_helper) fig.add_axes(cgax) # get twin axis for cartesian grid caax = cgax.twin() # move axis annotation from right to left and top to bottom for # cartesian axis caax.toggle_axisline() # make right and top axis visible and show ticklabels (curvelinear axis) cgax.axis["top", "right"].set_visible(True) cgax.axis["top", "right"].major_ticklabels.set_visible(True) # make ticklabels of left and bottom axis invisible (curvelinear axis) cgax.axis["left", "bottom"].major_ticklabels.set_visible(False) # and also set tickmarklength to zero for better presentation # (curvelinear axis) cgax.axis["top", "right", "left", "bottom"].major_ticks.set_ticksize(0) # show theta (angles) on top and right axis cgax.axis["top"].get_helper().nth_coord_ticks = 0 cgax.axis["right"].get_helper().nth_coord_ticks = 0 # generate and add parasite axes with given transform paax = ParasiteAxesAuxTrans(cgax, tr, "equal") # note that paax.transData == tr + cgax.transData # Anything you draw in paax will match the ticks and grids of cgax. cgax.parasites.append(paax) return cgax, caax, paax
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 curvelinear_plot(rayon_max=1000): """Fonction pour créer un repère cartésien avec en décoration les coordonnées polaire pour mieux repérer les angles Cette fonction est basée sur un exemple matplotlib : see demo_curvelinear_grid.py for details Args: rayon_max (float, optional): Rayon amximal du plot dans lequel afficher le robot. Defaults to 1000. Returns: matplotlib.fig, matplotlib.ax : figure et axe matplotlib dans lequel on fait l'affichage """ tr_rotate = Affine2D().translate(90, 0) tr_scale = Affine2D().scale(np.pi / 180., 1.) tr = tr_rotate + tr_scale + PolarAxes.PolarTransform() extreme_finder = angle_helper.ExtremeFinderCycle( 20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=None, lat_minmax=(-np.inf, np.inf), ) grid_locator1 = angle_helper.LocatorDMS(8) # tick_formatter1 = angle_helper.FormatterDMS() grid_helper = GridHelperCurveLinear( tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, # tick_formatter1=tick_formatter1 ) fig = plt.figure() ax1 = fig.add_subplot(axes_class=HostAxes, grid_helper=grid_helper) # Now creates floating axis # ax1.scatter(5, 5) # floating axis whose first coordinate (theta) is fixed at 60 ax1.axis["ax"] = axis = ax1.new_floating_axis(0, 0) axis.set_axis_direction("top") axis.major_ticklabels.set_axis_direction("left") ax1.axis["ax1"] = axis = ax1.new_floating_axis(0, -90) axis.set_axis_direction("left") axis.major_ticklabels.set_axis_direction("top") # 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, 150) axis.label.set_pad(10) # axis.label.set_text(r"$r = 1$") ax1.set_aspect(1.) ax1.set_xlim(-rayon_max, rayon_max) ax1.set_ylim(-rayon_max, rayon_max) ax1.grid(True) return fig, ax1
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 __init__(self, fig=None, max_normed_std=2.5, std_ratios=[1], \ bias_vmin=None, bias_vmax=None, \ normalized=True, cmap=plt.cm.jet, s=80, title_expected=r'expected'): """ Set up Taylor diagram axes. """ self.title_polar = r'Correlation' self.title_xy = r'Normalized Standard Deviation' self.max_normed_std = max_normed_std self.s_min = 0 self.std_ratios = std_ratios self.bias_vmin = bias_vmin self.bias_vmax = bias_vmax self.normalized = normalized self.cmap = cmap self.s = s # marker size self.title_expected = title_expected # Define polar coordinate tr = 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) # figure self.fig = fig if self.fig is None: self.fig = plt.figure() # setup axes ax = SubplotHost(self.fig, 111, grid_helper=grid_helper) self.ax = self.fig.add_subplot(ax) # set x and y axis self._setup_axes() # attach the polar axes and plot the correlation lines self.polar_ax = self.ax.get_aux_axes(tr) self.polar_ax.plot([np.pi / 2.135, np.pi / 2.135], [self.s_min, self.max_normed_std * 2], color='grey') self.polar_ax.plot([np.pi / 2.484, np.pi / 2.484], [self.s_min, self.max_normed_std * 2], color='grey') self.polar_ax.plot([np.pi / 3, np.pi / 3], [self.s_min, self.max_normed_std * 2], color='grey') self.polar_ax.plot([np.pi / 3.95, np.pi / 3.95], [self.s_min, self.max_normed_std * 2], color='grey') self.polar_ax.plot([np.pi / 6.95, np.pi / 6.95], [self.s_min, self.max_normed_std * 2], color='grey') # Add norm stddev ratio contours self._plot_req_cont(self.std_ratios) self.points = []
def create_cg(st, fig=None, subplot=111): """ Helper function to create curvelinear grid The function makes use of the Matplotlib AXISARTIST namespace `mpl_toolkits.axisartist \ <https://matplotlib.org/mpl_toolkits/axes_grid/users/axisartist.html>`_. Here are some limitations to normal Matplotlib Axes. While using the Matplotlib `AxesGrid Toolkit \ <https://matplotlib.org/mpl_toolkits/axes_grid/index.html>`_ most of the limitations can be overcome. See `Matplotlib AxesGrid Toolkit User’s Guide \ <https://matplotlib.org/mpl_toolkits/axes_grid/users/index.html>`_. Parameters ---------- st : string scan type, 'PPI' or 'RHI' fig : matplotlib Figure object If given, the PPI will be plotted into this figure object. Axes are created as needed. If None a new figure object will be created or current figure will be used, depending on "subplot". subplot : :class:`matplotlib:matplotlib.gridspec.GridSpec`, \ matplotlib grid definition nrows/ncols/plotnumber, see examples section defaults to '111', only one subplot Returns ------- cgax : matplotlib toolkit axisartist Axes object curvelinear Axes (r-theta-grid) caax : matplotlib Axes object (twin to cgax) Cartesian Axes (x-y-grid) for plotting cartesian data paax : matplotlib Axes object (parasite to cgax) The parasite axes object for plotting polar data """ if st == 'RHI': # create transformation tr = Affine2D().scale(np.pi / 180, 1) + PolarAxes.PolarTransform() # build up curvelinear grid extreme_finder = ah.ExtremeFinderCycle(20, 20, lon_cycle=100, lat_cycle=None, lon_minmax=(0, np.inf), lat_minmax=(0, np.inf), ) # locator and formatter for angular annotation grid_locator1 = ah.LocatorDMS(10.) tick_formatter1 = ah.FormatterDMS() # grid_helper for curvelinear grid grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=None, tick_formatter1=tick_formatter1, tick_formatter2=None, ) # try to set nice locations for range gridlines grid_helper.grid_finder.grid_locator2._nbins = 30.0 grid_helper.grid_finder.grid_locator2._steps = [0, 1, 1.5, 2, 2.5, 5, 10] if st == 'PPI': # Set theta start to north tr_rotate = Affine2D().translate(-90, 0) # set theta running clockwise tr_scale = Affine2D().scale(-np.pi / 180, 1) # create transformation tr = tr_rotate + tr_scale + PolarAxes.PolarTransform() # build up curvelinear grid extreme_finder = ah.ExtremeFinderCycle(20, 20, lon_cycle=360, lat_cycle=None, lon_minmax=(360, 0), lat_minmax=(0, np.inf), ) # locator and formatter for angle annotation locs = [i for i in np.arange(0., 359., 10.)] grid_locator1 = FixedLocator(locs) tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs])) # grid_helper for curvelinear grid grid_helper = GridHelperCurveLinear(tr, extreme_finder=extreme_finder, grid_locator1=grid_locator1, grid_locator2=None, tick_formatter1=tick_formatter1, tick_formatter2=None, ) # try to set nice locations for range gridlines grid_helper.grid_finder.grid_locator2._nbins = 15.0 grid_helper.grid_finder.grid_locator2._steps = [0, 1, 1.5, 2, 2.5, 5, 10] # if there is no figure object given if fig is None: # create new figure if there is only one subplot if subplot is 111: fig = pl.figure() # otherwise get current figure or create new figure else: fig = pl.gcf() # generate Axis cgax = SubplotHost(fig, subplot, grid_helper=grid_helper) fig.add_axes(cgax) # PPIs always plottetd with equal aspect if st == 'PPI': cgax.set_aspect('equal', adjustable='box') # get twin axis for cartesian grid caax = cgax.twin() # move axis annotation from right to left and top to bottom for # cartesian axis caax.toggle_axisline() # make right and top axis visible and show ticklabels (curvelinear axis) cgax.axis["top", "right"].set_visible(True) cgax.axis["top", "right"].major_ticklabels.set_visible(True) # make ticklabels of left and bottom axis invisible (curvelinear axis) cgax.axis["left", "bottom"].major_ticklabels.set_visible(False) # and also set tickmarklength to zero for better presentation # (curvelinear axis) cgax.axis["top", "right", "left", "bottom"].major_ticks.set_ticksize(0) # show theta (angles) on top and right axis cgax.axis["top"].get_helper().nth_coord_ticks = 0 cgax.axis["right"].get_helper().nth_coord_ticks = 0 # generate and add parasite axes with given transform paax = ParasiteAxesAuxTrans(cgax, tr, "equal") # note that paax.transData == tr + cgax.transData # Anything you draw in paax will match the ticks and grids of cgax. cgax.parasites.append(paax) return cgax, caax, paax