def axesRight(fig, rect, ternaryinfo, grid=False, debug=False):
xname = ternaryinfo.right.name
vminx, vmaxx = ternaryinfo.right.max, ternaryinfo.right.min
yname = ternaryinfo.top.name
vminy, vmaxy = ternaryinfo.top.min, ternaryinfo.top.max
ox = vminx
oy = vminy
sx = float(vmaxx - vminx)
sy = float(vmaxy - vminy)
M = plttransforms.Affine2D()
M += plttransforms.Affine2D().translate(-ox, -oy)
M += plttransforms.Affine2D().scale(1, sx / sy)
M += plttransforms.Affine2D().skew_deg(-15, -15)
M += plttransforms.Affine2D().rotate_deg(15)
f, fi = transformations(M)
grid_helper = pltahelper.GridHelperCurveLinear((f, fi))
ax = plta.Axes(fig, rect, grid_helper=grid_helper, frameon=False)
ax.axis["top", "right", "left", "bottom"].set_visible(False)
ax.axis["X"] = ax.new_floating_axis(1, oy)
ax.axis["X"].label.set_text(xname)
ax.axis["X"].label.set_color(ternaryinfo.right.color)
xmax1, ymin1 = f(vminx, vminy)
xmax1, ymin1 = xmax1[0], ymin1[0]
xmin1, _ = f(vmaxx, vminy)
xmin1 = xmin1[0]
_, ymax1 = f(vminx, vmaxy)
ymax1 = ymax1[0]
ax.set_xlim(xmin1, xmax1)
ax.set_ylim(ymin1, ymax1)
if debug:
ax.axis["Y"] = ax.new_floating_axis(0, ox)
ax.axis["Y"].label.set_text(yname)
ax.plot(*f([vminx, vmaxx], [vminy, vminy]), marker="o", markersize=10)
ax.plot(*f([vminx, vminx], [vminy, vmaxy]), marker="+", markersize=10)
if grid:
ax.grid(True, axis="x", zorder=0, color=ternaryinfo.right.color)
return ax
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
import mpl_toolkits.axisartist as AA import matplotlib.pyplot as plt import numpy as np fig = plt.figure(1) ax = AA.Axes(fig, [0.1, 0.1, 0.8, 0.8]) fig.add_axes(ax) ax.axis["right"].set_visible(False) ax.axis["top"].set_visible(False) plt.show()
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 main():
origin = [0, 0]
xCoord = [1, -1]
yCoord = [1, 2]
transformation = [[1, 3], [5, 2]]
[eigenvalue1, eigenvalue2], [eigenvector1,
eigenvector2] = LA.eig(transformation)
print eigenvalue1, eigenvalue2, (3 - sqrt(61)) / 2, (3 + sqrt(61)) / 2
eigenvector1 = eigenvector1 / dot(eigenvector1, eigenvector1)
eigenvector2 = eigenvector2 / dot(eigenvector2, eigenvector2)
eigenCoord1 = zip(origin, 3 * eigenvalue1 * eigenvector1)
print eigenvector1
fig, ax = plt.subplots()
x_grid_locator = MaxNLocator(3 // 0.0125)
y_grid_locator = MaxNLocator(3 // 0.00625)
ax = AA.Axes(
fig, [0.1, 0.1, 0.8, 0.8],
grid_helper=GridHelperCurveLinear(
(tr, inv_tr),
grid_locator1=x_grid_locator,
grid_locator2=y_grid_locator)) # This appears to be your margins
fig.add_axes(ax)
ax.axis["right"].set_visible(False)
ax.axis["top"].set_visible(False)
ax.axis["left"].set_visible(False)
ax.axis["bottom"].set_visible(False)
ax.grid(True, zorder=0)
# ax.set_xticks([0.01, 0.02, 0.03])
ax.axis["t"] = ax.new_floating_axis(
0, 0
) # first argument appears to be slope, second argument appears to be starting point on vertical
ax.axis["t2"] = ax.new_floating_axis(1, 0)
# ax.axis["t"].set_xticks([1, 2, 3, 4, 5, 6])
# ax.axis["t"].label.set_pad(2)
ax.plot([0, 1], [0, 1])
# ax.axis["y=0"] = ax.new_floating_axis(nth_coord=0, value=0)
# # ax.axis["x=0"] = ax.new_floating_axis(nth_coord=0, value=0)
# ax.axis["right2"] = ax.new_fixed_axis(loc="right", offset=(-184, 0))
# ax.axis["t"] = ax.new_floating_axis(0, 0) # first argument appears to be slope, second argument appears to be starting point on vertical
# ax.axis["t2"] = ax.new_floating_axis(1, 0)
scalingFactor = (24 * sqrt(29)) / 5
otherFactor = 12 * sqrt(5)
print scalingFactor / 3
print otherFactor / 3
ax.set_xlim(-scalingFactor, scalingFactor)
ax.set_ylim(-otherFactor, otherFactor)
ax.quiver(origin,
origin,
xCoord,
yCoord,
color=[colorDefault(0), colorDefault(3)],
angles='xy',
scale_units='xy',
scale=1)
ax.grid(True, which='both')
ax.axhline(y=0, color='k')
ax.axvline(x=0, color='k')
# axis_to_data = ax.transAxes + ax.transData.inverted()
# points_data = axis_to_data.transform((2, 3))
# data_to_axis = axis_to_data.inverted()
# numpy.testing.assert_allclose((2, 3), data_to_axis.transform(points_data))
plt.xlim(-8, 8)
plt.ylim(-8, 8)
plt.figure()
plt.quiver(origin,
origin,
xCoord,
yCoord,
color=[colorDefault(0), colorDefault(3)],
angles='xy',
scale_units='xy',
scale=1)
plt.grid(True, which='both')
plt.axhline(y=0, color='k')
plt.axvline(x=0, color='k')
# axis_to_data = ax.transAxes + ax.transData.inverted()
# points_data = axis_to_data.transform((2, 3))
# data_to_axis = axis_to_data.inverted()
# numpy.testing.assert_allclose((2, 3), data_to_axis.transform(points_data))
plt.xlim(-8, 8)
plt.ylim(-8, 8)
fig = plt.figure()
x_grid_locator = MaxNLocator(3 // 0.0125)
y_grid_locator = MaxNLocator(3 // 0.00625)
ax = AA.Axes(
fig, [0.1, 0.1, 0.8, 0.8],
grid_helper=GridHelperCurveLinear(
(tr, inv_tr),
grid_locator1=x_grid_locator,
grid_locator2=y_grid_locator)) # This appears to be your margins
fig.add_axes(ax)
ax.axis["right"].set_visible(False)
ax.axis["top"].set_visible(False)
ax.axis["left"].set_visible(False)
ax.axis["bottom"].set_visible(False)
ax.grid(True, zorder=0)
# ax.set_xticks([0.01, 0.02, 0.03])
ax.axis["t"] = ax.new_floating_axis(
0, 0
) # first argument appears to be slope, second argument appears to be starting point on vertical
ax.axis["t2"] = ax.new_floating_axis(1, 0)
# ax.axis["t"].set_xticks([1, 2, 3, 4, 5, 6])
# ax.axis["t"].label.set_pad(2)
ax.plot([0, 1], [0, 1])
# ax.axis["y=0"] = ax.new_floating_axis(nth_coord=0, value=0)
# # ax.axis["x=0"] = ax.new_floating_axis(nth_coord=0, value=0)
# ax.axis["right2"] = ax.new_fixed_axis(loc="right", offset=(-184, 0))
# ax.axis["t"] = ax.new_floating_axis(0, 0) # first argument appears to be slope, second argument appears to be starting point on vertical
# ax.axis["t2"] = ax.new_floating_axis(1, 0)
scalingFactor = (24 * sqrt(29)) / 5
otherFactor = 12 * sqrt(5)
print scalingFactor / 3
print otherFactor / 3
ax.set_xlim(-scalingFactor, scalingFactor)
ax.set_ylim(-otherFactor, otherFactor)
plt.show()
axGrad.set_xlim(x1, x2)
axGrad.set_ylim(-0.2, 0.5)
# Löschen der Einträge xdata und ydata und anschließendes initialisieren der Daten von line
line.set_data([], [])
lineGrad.set_data([], [])
axGrad.add_patch(patch)
return
# Fenster erstellen
fig = plt.figure(figsize=(8, 8))
ax = AA.Axes(fig, [0.1, 0.25, 0.8, 0.7])
axGrad = AA.Axes(fig, [0.1, 0.1, 0.8, 0.05])
fig.add_axes(ax)
fig.add_axes(axGrad)
axGrad.set_xticks(np.array([x1, x2]))
axGrad.axis["right"].set_visible(False)
axGrad.axis["top"].set_visible(False)
axGrad.axis["left"].set_visible(False)
# Plotten der Originalen Funktion
xOrig = np.arange(x1, x2, 0.01)
yOrig = f(xOrig)
ax.plot(xOrig, yOrig)
# Erzeugung des Gitters vom Koordinatensystem mit grid() und Deklaration der Daten