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 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 __init__(self,
refstd,
fig=None,
rect=111,
label=None,
cors=[0.3, 0.6, 0.9]):
"""Set up Taylor diagram axes, i.e. single quadrant polar
plot, using mpl_toolkits.axisartist.floating_axes. refstd is
the reference standard deviation to be compared to.
"""
from matplotlib.projections import PolarAxes
import mpl_toolkits.axisartist.floating_axes as FA
import mpl_toolkits.axisartist as axisartist
import mpl_toolkits.axisartist.grid_finder as GF
self.refstd = refstd # Reference standard deviation
tr = PolarAxes.PolarTransform()
# Correlation labels
rlocs = NP.concatenate((NP.arange(10) / 10., [0., 0.99]))
tlocs = NP.arccos(rlocs) # Conversion to polar angles
gl1 = GF.FixedLocator(tlocs) # Positions
tf1 = GF.DictFormatter(dict(zip(tlocs, map(str, rlocs))))
# Standard deviation axis extent
self.smin = 0.0
self.smax = 1.6 * self.refstd
gl2 = GF.MaxNLocator(10) #[0, 0.2,0.4,0.6, 0.8,1.0,1.2,1.4]
ghelper = FA.GridHelperCurveLinear(
tr,
extremes=(
0,
NP.pi / 2.0, # 1st quadrant
self.smin,
self.smax),
grid_locator1=gl1,
grid_locator2=gl2,
tick_formatter1=tf1,
tick_formatter2=None,
)
ghelper.grid_finder.grid_locator2._nbins = 4
if fig is None:
fig = PLT.figure()
ax = FA.FloatingSubplot(fig, rect, grid_helper=ghelper)
fig.add_subplot(ax)
# Adjust axes
PLT.setp(ax.spines.values(), visible=False)
ax.axis["top"].set_axis_direction("bottom") # "Angle axis"
ax.axis["top"].toggle(ticklabels=True, label=True)
ax.axis["top"].major_ticklabels.set_axis_direction("top")
ax.axis["top"].label.set_axis_direction("top")
ax.axis["top"].label.set_text("Correlation")
ax.axis["top"].label.set_fontsize(9)
ax.axis[:].major_ticklabels.set_fontsize(12)
ax.axis["left"].set_axis_direction("right") # "X axis"
ax.axis["left"].toggle(ticklabels=True, label=True)
ax.axis["left"].toggle(ticklabels=False, label=False)
ax.axis["left"].label.set_text("Normalized std.")
ax.axis["left"].label.set_fontsize(9)
ax.axis["right"].set_axis_direction("top") # "Y axis"
ax.axis["right"].toggle(ticklabels=True, label=True)
ax.axis["right"].major_ticklabels.set_axis_direction("left")
ax.axis["right"].label.set_fontsize(9)
ax.axis["bottom"].set_visible(False) # Useless
# Contours along standard deviations
ax.grid(False)
self._ax = ax # Graphical axes
self.ax = ax.get_aux_axes(tr) # Polar coordinates
# Add reference point and stddev contour
l, = self.ax.plot([0],
self.refstd,
color='black',
marker='o',
ls='',
ms=10,
label="OBS")
t = NP.linspace(0, NP.pi / 2.0)
r = NP.zeros_like(t) + self.refstd
lines = self.ax.plot(t,
r,
color='darkgray',
ls='--',
label='_',
zorder=0,
lw=0.8)
for isec in cors:
rad = NP.arccos(isec)
stds = NP.linspace(self.smin, self.smax)
rad0 = [rad for x in stds]
lines = self.ax.plot(rad0,
stds,
color='darkgray',
ls='--',
zorder=0,
lw=0.8)
self.samplePoints = [l]
def taylor_ax(fig, *args, **kw):
#th1=0., th2=np.pi/3, rd1=0., rd2=1.2, tloc1=None, tloc2=None)
tr = PolarAxes.PolarTransform()
# Correlation labels
if kw.has_key("tloc1"):
rlocs = kw["tloc1"]
else:
rlocs = np.concatenate((np.arange(10) / 10., [0.95, 0.99]))
tlocs = np.arccos(rlocs)
gl1 = GF.FixedLocator(tlocs)
tf1 = GF.DictFormatter(dict(zip(tlocs, map(str, rlocs))))
if kw.has_key("tloc2"):
gl2 = GF.FixedLocator(kw["tloc2"])
else:
gl2 = GF.MaxNLocator(10)
if kw.has_key("th1"):
th1 = kw["th1"]
else:
th1 = 0.
if kw.has_key("th2"):
th2 = kw["th2"]
else:
th2 = np.pi / 2
if kw.has_key("rd1"):
rd1 = kw["rd1"]
else:
rd1 = 0.
if kw.has_key("rd2"):
rd2 = kw["rd2"]
else:
rd2 = 1.65
ghelper = FA.GridHelperCurveLinear(
tr,
extremes=(th1, th2, rd1, rd2),
grid_locator1=gl1,
grid_locator2=gl2,
tick_formatter1=tf1,
tick_formatter2=None,
)
ax = FA.FloatingSubplot(fig, *args, grid_helper=ghelper)
fig.add_subplot(ax)
# Adjust axes
fontsize = 9
ax.axis["top"].set_axis_direction("bottom") # "Angle axis"
ax.axis["top"].toggle(ticklabels=True, label=True)
ax.axis["top"].major_ticklabels.set_size('xx-small')
ax.axis["top"].major_ticklabels.set_axis_direction("top")
ax.axis["top"].label.set_axis_direction("top")
ax.axis["top"].label.set_text("Correlation")
ax.axis["top"].label.set_fontsize(fontsize)
ax.axis["left"].set_axis_direction("right") # "X axis"
ticks_font = 2
ax.axis["left"].major_ticklabels.set_size('xx-small')
ax.axis["left"].major_ticks.set_ticksize(ticks_font) # "X axis"
ax.axis["left"].label.set_text("Normalized standard deviation")
ax.axis["left"].label.set_fontsize(fontsize)
ax.axis["right"].major_ticklabels.set_size('xx-small')
ax.axis["right"].set_axis_direction("top") # "Y axis"
ax.axis["right"].toggle(ticklabels=True)
ax.axis["right"].major_ticks.set_ticksize(ticks_font) # "Y axis"
ax.axis["right"].major_ticklabels.set_axis_direction("left")
ax.axis["right"].label.set_fontsize(fontsize)
ax.axis["bottom"].set_visible(False) # turn off overlaying tickmark
ax.grid(linewidth=0.5, color='gray')
aux_ax = ax.get_aux_axes(tr) # Polar coordinates
aux_ax.th1 = th1
aux_ax.th2 = th2
aux_ax.rd1 = rd1
aux_ax.rd2 = rd2
ax.th1 = th1
ax.th2 = th2
ax.rd1 = rd1
ax.rd2 = rd2
return ax, aux_ax
def __init__(self, refstd, fig=None, rect=None, label='_',
srange=(0, 1.5), extend=False):
"""
Set up Taylor diagram axes, i.e. single quadrant polar
plot, using `mpl_toolkits.axisartist.floating_axes`.
Parameters:
* refstd: reference standard deviation to be compared to
* fig: input Figure or None
* rect: subplot definition
* label: reference label
* srange: stddev axis extension, in units of *refstd*
* extend: extend diagram to negative correlations
"""
self.refstd = refstd # Reference standard deviation
tr = PolarAxes.PolarTransform()
# Correlation labels
rlocs = numpy.array([0, 0.2, 0.4, 0.6, 0.7, 0.8, 0.9, 0.95, 0.99, 1])
if extend:
# Diagram extended to negative correlations
self.tmax = numpy.pi
rlocs = numpy.concatenate((-rlocs[:0:-1], rlocs))
else:
# Diagram limited to positive correlations
self.tmax = numpy.pi / 2
tlocs = numpy.arccos(rlocs) # Conversion to polar angles
gl1 = grid_finder.FixedLocator(tlocs) # Positions
tf1 = grid_finder.DictFormatter(dict(zip(tlocs, map(str, rlocs))))
# set s locator
gl2 = grid_finder.MaxNLocator(7) # Max 7 ticks
# Standard deviation axis extent (in units of reference stddev)
self.smin = srange[0] * self.refstd
self.smax = srange[1] * self.refstd
ghelper = floating_axes.GridHelperCurveLinear(
tr,
extremes=(0, self.tmax, self.smin, self.smax),
grid_locator1=gl1, tick_formatter1=tf1,
grid_locator2=gl2)
self.fig = plt.figure() if fig is None else fig
if rect is None:
rect = 111
ax = floating_axes.FloatingSubplot(self.fig, rect, grid_helper=ghelper)
self.fig.add_subplot(ax)
# Adjust axes
ax.axis["top"].set_axis_direction("bottom") # "Angle axis"
ax.axis["top"].toggle(ticklabels=True, label=True)
ax.axis["top"].major_ticklabels.set_axis_direction("top")
ax.axis["top"].label.set_axis_direction("top")
ax.axis["top"].label.set_text("Correlation")
ax.axis["left"].set_axis_direction("bottom") # "X axis"
ax.axis["left"].label.set_text("Standard deviation")
ax.axis["right"].set_axis_direction("top") # "Y-axis"
ax.axis["right"].toggle(ticklabels=True)
ax.axis["right"].major_ticklabels.set_axis_direction(
"bottom" if extend else "left")
if self.smin:
ax.axis["bottom"].toggle(ticklabels=False, label=False)
else:
ax.axis["bottom"].set_visible(False) # Unused
self._ax = ax # Graphical axes
self.ax = ax.get_aux_axes(tr) # Polar coordinates
# Add reference point and stddev contour
l, = self.ax.plot([0], self.refstd, 'k*',
ls='', ms=10, label=label)
t = numpy.linspace(0, self.tmax)
r = numpy.zeros_like(t) + self.refstd
self.ax.plot(t, r, 'k--', label='_', zorder=1)
# Collect sample points for latter use (e.g. legend)
self.sample_points = [l]
# set color and marker styles
self.ax.set_prop_cycle(get_point_style_cycler())
