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%matplotlib inline
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from mplstereonet import subplots
from attitude.orientation.pca import random_pca
from attitude.plot.stereonet import stereonet_errors, stereonet_pole_error
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fit = random_pca()
fit
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In [4]:
fig, ax = subplots()
ax.grid()
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stereonet_errors(ax,fit, facecolor='purple', edgecolor='black', alpha=0.8)
ax.plane(*fit.strike_dip(), color='black')
fig
Out[5]:
In [6]:
stereonet_pole_error(ax, fit, facecolor='purple',
edgecolor='black', alpha=0.8)
ax.pole(*fit.strike_dip(), color='black')
fig
Out[6]:
In [7]:
fig2, axea = subplots(projection='equal_angle')
axea.grid()
kw = dict(facecolor='purple', edgecolor='black', alpha=0.8)
stereonet_errors(axea,fit, **kw)
stereonet_pole_error(axea, fit, **kw)
axea.plane(*fit.strike_dip(), color='black')
axea.pole(*fit.strike_dip(), color='black')
Out[7]:
In [8]:
fit = random_pca()
kw = dict(facecolor='teal', edgecolor='black', zorder=3, alpha=0.8)
stereonet_pole_error(ax, fit, **kw)
stereonet_errors(ax,fit, **kw)
kw = dict(color='black', zorder=3)
ax.plane(*fit.strike_dip(), **kw)
ax.pole(*fit.strike_dip(), **kw)
fig
Out[8]: