예제 #1
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 def test_fit_girdle(self):
     for strike in range(0, 370, 10):
         for dip in range(0, 100, 10):
             lon, lat = mplstereonet.plane(strike, dip)
             strikes, dips = mplstereonet.geographic2pole(lon, lat)
             s, d = mplstereonet.fit_girdle(strikes, dips)
             self.compare_strikedip(strike, dip, s, d)
예제 #2
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 def test_fit_girdle(self):
     for strike in range(0, 370, 10):
         for dip in range(0, 100, 10):
             lon, lat = mplstereonet.plane(strike, dip)
             strikes, dips = mplstereonet.geographic2pole(lon, lat)
             s, d = mplstereonet.fit_girdle(strikes, dips)
             self.compare_strikedip(strike, dip, s, d)
예제 #3
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 def test_fit_girdle_noisy(self):
     np.random.seed(1)
     for strike in range(0, 370, 10):
         for dip in range(0, 100, 10):
             lon, lat = mplstereonet.plane(strike, dip)
             lon += np.radians(np.random.normal(0, 1, lon.shape))
             lat += np.radians(np.random.normal(0, 1, lat.shape))
             s_noisy, d_noisy = mplstereonet.geographic2pole(lon, lat)
             s, d = mplstereonet.fit_girdle(s_noisy, d_noisy)
             ang_dist = self.cos_distance(strike, dip, s, d)
             assert ang_dist < 2 or (180 - ang_dist) < 2
예제 #4
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 def test_fit_girdle_noisy(self):
     np.random.seed(1)
     for strike in range(0, 370, 10):
         for dip in range(0, 100, 10):
             lon, lat = mplstereonet.plane(strike, dip)
             lon += np.radians(np.random.normal(0, 1, lon.shape))
             lat += np.radians(np.random.normal(0, 1, lat.shape))
             s_noisy, d_noisy = mplstereonet.geographic2pole(lon, lat)
             s, d = mplstereonet.fit_girdle(s_noisy, d_noisy)
             ang_dist = self.cos_distance(strike, dip, s, d)
             assert ang_dist < 2 or (180 - ang_dist) < 2
예제 #5
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This example simulates finding the plunge and bearing of a cylindrical fold
axis from strike/dip measurements of bedding in the fold limbs.
"""
import numpy as np
import matplotlib.pyplot as plt
import mplstereonet
np.random.seed(1)

# Generate a random girdle distribution from the plunge/bearing of a fold hinge
# In the end, we'll have strikes and dips as measured from bedding in the fold.
# *strike* and *dip* below would normally be your input.
num_points = 200
real_bearing, real_plunge = 300, 5
s, d = mplstereonet.plunge_bearing2pole(real_plunge, real_bearing)
lon, lat = mplstereonet.plane(s, d, segments=num_points)
lon += np.random.normal(0, np.radians(15), lon.shape)
lat += np.random.normal(0, np.radians(15), lat.shape)
strike, dip = mplstereonet.geographic2pole(lon, lat)

# Plot the raw data and contour it:
fig, ax = mplstereonet.subplots()
ax.density_contourf(strike, dip, cmap='gist_earth')
ax.density_contour(strike, dip, colors='black')
ax.pole(strike, dip, marker='.', color='black')

# Fit a plane to the girdle of the distribution and display it.
fit_strike, fit_dip = mplstereonet.fit_girdle(strike, dip)
ax.plane(fit_strike, fit_dip, color='red', lw=2)
ax.pole(fit_strike, fit_dip, marker='o', color='red', markersize=14)
예제 #6
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This example simulates finding the plunge and bearing of a cylindrical fold
axis from strike/dip measurements of bedding in the fold limbs.
"""
import numpy as np
import matplotlib.pyplot as plt
import mplstereonet
np.random.seed(1)

# Generate a random girdle distribution from the plunge/bearing of a fold hinge
# In the end, we'll have strikes and dips as measured from bedding in the fold.
# *strike* and *dip* below would normally be your input.
num_points = 200
real_bearing, real_plunge = 300, 5
s, d = mplstereonet.plunge_bearing2pole(real_plunge, real_bearing)
lon, lat = mplstereonet.plane(s, d, segments=num_points)
lon += np.random.normal(0, np.radians(15), lon.shape)
lat += np.random.normal(0, np.radians(15), lat.shape)
strike, dip = mplstereonet.geographic2pole(lon, lat)

# Plot the raw data and contour it:
fig, ax = mplstereonet.subplots()
ax.density_contourf(strike, dip, cmap='gist_earth')
ax.density_contour(strike, dip, colors='black')
ax.pole(strike, dip, marker='.', color='black')

# Fit a plane to the girdle of the distribution and display it.
fit_strike, fit_dip = mplstereonet.fit_girdle(strike, dip)
ax.plane(fit_strike, fit_dip, color='red', lw=2)
ax.pole(fit_strike, fit_dip, marker='o', color='red', markersize=14)