def setup_axes(fig, rect):
"""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)
grid_locator2 = grid_finder.MaxNLocator(5)
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)
ax1 = fig.add_subplot(rect,
axes_class=axisartist.Axes,
grid_helper=grid_helper)
ax1.axis[:].set_visible(False)
ax1.set_aspect(1.)
ax1.set_xlim(-5, 12)
ax1.set_ylim(-5, 10)
return ax1
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 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 create_axes(self, rect=111):
"""
Create a special AxisArtist to overlay grid coordinates.
Much of this taken from the examples here:
http://matplotlib.org/mpl_toolkits/axes_grid/users/axisartist.html
"""
# from curved coordinate to rectlinear coordinate.
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return self(x, y)
# from rectlinear coordinate to curved coordinate.
def inv_tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return self(x, y, inverse=True)
# Cycle the coordinates
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20)
# Find a grid values appropriate for the coordinate.
# The argument is a approximate number of grid lines.
grid_locator1 = angle_helper.LocatorD(8, include_last=False)
grid_locator2 = angle_helper.LocatorD(6, include_last=False)
# Format the values of the grid
tick_formatter1 = FormatterFgcm()
tick_formatter2 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(
(tr, inv_tr),
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
grid_locator2=grid_locator2,
tick_formatter1=tick_formatter1,
tick_formatter2=tick_formatter2,
)
fig = plt.gcf()
ax = axisartist.Subplot(fig, rect, grid_helper=grid_helper)
fig.add_subplot(ax)
ax.axis['left'].major_ticklabels.set_visible(True)
ax.axis['right'].major_ticklabels.set_visible(True)
ax.axis['bottom'].major_ticklabels.set_visible(True)
ax.axis['top'].major_ticklabels.set_visible(True)
ax.set_xlabel("Right Ascension")
ax.set_ylabel("Declination")
return fig, 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).
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 curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
sgn = np.sign(x)
x, y = np.abs(np.asarray(x)), np.asarray(y)
return sgn * x**.5, y
def inv_tr(x, y):
sgn = np.sign(x)
x, y = np.asarray(x), np.asarray(y)
return sgn * x**2, y
extreme_finder = angle_helper.ExtremeFinderCycle(
20,
20,
lon_cycle=None,
lat_cycle=None,
# (0, np.inf),
lon_minmax=None,
lat_minmax=None,
)
grid_helper = GridHelperCurveLinear((tr, inv_tr),
extreme_finder=extreme_finder)
ax1 = Subplot(fig, 111, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
ax1.imshow(np.arange(25).reshape(5, 5),
vmax=50,
cmap=plt.cm.gray_r,
interpolation="nearest",
origin="lower")
# tick density
grid_helper.grid_finder.grid_locator1._nbins = 6
grid_helper.grid_finder.grid_locator2._nbins = 6
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 setup_axes(fig, rect):
"""
polar projection, but in a rectangular box.
"""
# 细节可以参考前面“曲线网格”的例子
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)
grid_locator2 = grid_finder.MaxNLocator(5)
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
)
ax1 = axisartist.Subplot(fig, rect, grid_helper=grid_helper)
ax1.axis[:].toggle(ticklabels=False)
fig.add_subplot(ax1)
ax1.set_aspect(1.)
ax1.set_xlim(-5, 12)
ax1.set_ylim(-5, 10)
return ax1
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 create_axes(self, rect=111):
"""
Create a special AxisArtist to overlay grid coordinates.
Much of this taken from the examples here:
http://matplotlib.org/mpl_toolkits/axes_grid/users/axisartist.html
"""
# from curved coordinate to rectlinear coordinate.
def tr(x, y):
return self(x, y)
# from rectlinear coordinate to curved coordinate.
def inv_tr(x, y):
return self(x, y, inverse=True)
# Cycle the coordinates
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20)
# Find a grid values appropriate for the coordinate.
# The argument is a approximate number of grid lines.
grid_locator1 = angle_helper.LocatorD(9, include_last=False)
# grid_locator1 = angle_helper.LocatorD(8, include_last=False)
grid_locator2 = angle_helper.LocatorD(6, include_last=False)
# Format the values of the grid
tick_formatter1 = self.create_tick_formatter()
tick_formatter2 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(
(tr, inv_tr),
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
grid_locator2=grid_locator2,
tick_formatter1=tick_formatter1,
tick_formatter2=tick_formatter2,
)
fig = plt.gcf()
rect = self.ax.get_position()
ax = axisartist.Axes(fig, rect, grid_helper=grid_helper, frameon=False)
fig.add_axes(ax)
# Coordinate formatter
def format_coord(x, y):
return 'lon=%1.4f, lat=%1.4f' % inv_tr(x, y)
ax.format_coord = format_coord
ax.axis['left'].major_ticklabels.set_visible(True)
ax.axis['right'].major_ticklabels.set_visible(False)
ax.axis['bottom'].major_ticklabels.set_visible(True)
ax.axis['top'].major_ticklabels.set_visible(True)
ax.axis['bottom'].label.set(text="Right Ascension", size=18)
ax.axis['left'].label.set(text="Declination", size=18)
self.aa = ax
# Set the current axis back to the SkyAxes
fig.sca(self.ax)
return fig, 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
# 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 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 make_polar_axis(figure):
"""
Generate a polar axis.
Examples
--------
>>> from pylab import *
>>> f = figure()
>>> ax1,ax2 = make_polar_axis(f)
>>> f.add_subplot(ax1)
"""
# 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(
40,
40,
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,
#tick_formatter2=matplotlib.ticker.FuncFormatter(lambda x: x * kpc_per_pix)
)
ax1 = SubplotHost(figure,
1,
1,
1,
grid_helper=grid_helper,
axisbg='#333333')
# 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
ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
ax1.parasites.append(ax2)
return ax1, ax2
def make_mw_plot(fig=None, mw_img_name = "Milky_Way_2005.jpg",
solar_rad=8.5, fignum=5):
"""
Generate a "Milky Way" plot with Robert Hurt's Milky Way illustration as
the background.
.. TODO:
Figure out how to fix the axis labels. They don't work now!
Parameters
----------
fig : matplotlib.figure instance
If you want to start with a figure instance, can specify it
mw_img_name: str
The name of the image on disk
solar_rad : float
The assumed Galactocentric orbital radius of the sun
fignum : int
If Figure not specified, use this figure number
"""
# load image
mw = np.array(PIL.Image.open(mw_img_name))[:,::-1]
# set some constants
npix = mw.shape[0] # must be symmetric
# Galactic Center in middle of image
gc_loc = [x/2 for x in mw.shape]
# Sun is at 0.691 (maybe really 0.7?) length of image
sun_loc = mw.shape[0]/2,int(mw.shape[1]*0.691)
# determine scaling
kpc_per_pix = solar_rad / (sun_loc[1]-gc_loc[1])
boxsize = npix*kpc_per_pix
# most of the code below is taken from:
# http://matplotlib.sourceforge.net/examples/axes_grid/demo_curvelinear_grid.html
# and http://matplotlib.sourceforge.net/examples/axes_grid/demo_floating_axis.html
if fig is None:
fig = plt.figure(fignum)
plt.clf()
# PolarAxes.PolarTransform takes radian. However, we want our coordinate
# system in degree
# this defines the polar coordinate system @ Galactic center
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).
# grid helper stuff, I think (grid is off by default)
# This may not apply to the image *at all*, but would if you
# used the grid
# 40, 40 : number of sampling points along x, y direction
extreme_finder = angle_helper.ExtremeFinderCycle(40, 40,
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,
#tick_formatter2=matplotlib.ticker.FuncFormatter(lambda x: x * kpc_per_pix)
)
ax = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper, axisbg='#333333')
fig.add_subplot(ax)
# ax.transData is still a (rectlinear) pixel coordinate. Only the
# grids are done in galactocentric coordinate.
# show the image
ax.imshow(mw,extent=[-boxsize/2,boxsize/2,-boxsize/2,boxsize/2])
ax_pixgrid = ax.twin() # simple twin will give you a twin axes,
# but with normal grids.
# to draw heliocentric grids, it is best to update the grid_helper
# with new transform.
# need to rotate by -90 deg to get into the standard convention
tr_helio = Affine2D().scale(np.pi/180., 1.).translate(-np.pi/2.,0) + \
PolarAxes.PolarTransform() + \
Affine2D().translate(0,solar_rad)
# Note that the transform is from the heliocentric coordinate to
# the pixel coordinate of ax (i.e., ax.transData).
ax.get_grid_helper().update_grid_finder(aux_trans=tr_helio)
# Now we defina parasite axes with galactocentric & heliocentric
# coordinates.
# A parasite axes with given transform
gc_polar = ParasiteAxesAuxTrans(ax, tr, "equal")
ax.parasites.append(gc_polar)
# note that ax2.transData == tr + galactocentric_axis.transData
# Anthing you draw in ax2 will match the ticks and grids of galactocentric_axis.
hc_polar = ParasiteAxesAuxTrans(ax, tr_helio, "equal")
ax.parasites.append(hc_polar)
return ax, ax_pixgrid, gc_polar, hc_polar
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 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
def create_axes(self,rect=111):
"""
Create a special AxisArtist to overlay grid coordinates.
Much of this taken from the examples here:
http://matplotlib.org/mpl_toolkits/axes_grid/users/axisartist.html
"""
# from curved coordinate to rectlinear coordinate.
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return self(x,y)
# from rectlinear coordinate to curved coordinate.
def inv_tr(x,y):
x, y = np.asarray(x), np.asarray(y)
return self(x,y,inverse=True)
# Cycle the coordinates
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20)
# Find a grid values appropriate for the coordinate.
# The argument is a approximate number of grid lines.
grid_locator1 = angle_helper.LocatorD(9,include_last=False)
#grid_locator1 = angle_helper.LocatorD(8,include_last=False)
grid_locator2 = angle_helper.LocatorD(6,include_last=False)
# Format the values of the grid
tick_formatter1 = self.create_tick_formatter()
tick_formatter2 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear((tr, inv_tr),
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
grid_locator2=grid_locator2,
tick_formatter1=tick_formatter1,
tick_formatter2=tick_formatter2,
)
fig = plt.gcf()
if rect is None:
# This doesn't quite work. Need to remove the existing axis...
rect = plt.gca().get_position()
plt.gca().axis('off')
ax = axisartist.Axes(fig,rect,grid_helper=grid_helper)
fig.add_axes(ax)
else:
ax = axisartist.Subplot(fig,rect,grid_helper=grid_helper)
fig.add_subplot(ax)
## Coordinate formatter
def format_coord(x, y):
return 'lon=%1.4f, lat=%1.4f'%inv_tr(x,y)
ax.format_coord = format_coord
ax.axis['left'].major_ticklabels.set_visible(True)
ax.axis['right'].major_ticklabels.set_visible(False)
ax.axis['bottom'].major_ticklabels.set_visible(True)
ax.axis['top'].major_ticklabels.set_visible(True)
ax.set_xlabel("Right Ascension")
ax.set_ylabel("Declination")
#self.set_axes_limits()
self.axisartist = ax
return fig,ax
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
