if __name__ == '__main__':
ela_elevations = np.arange(4000, 5100, 100)
ela_changes = np.arange(100, 510, 100)
slopes = np.arange(0.05, 0.30, 0.05)
glacier = Glacier(max_bed_height=5500)
fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(nrows=3,
ncols=2,
figsize=(14, 10))
# Length change with varying ELA
for slope in slopes:
glacier.slope = slope
length_change = [
glacier.linear_equilibrium_length(elevation)
for elevation in ela_elevations
]
ax1.plot(ela_elevations, length_change, label=slope.round(2))
ax1.set_title('Length change with varying ELA')
ax1.legend(title='Slope')
# Change of length over change of ELA
for slope in slopes:
lengths = [
glacier.length_change(ela_change, slope)
for ela_change in ela_changes
]
ax3.plot(ela_changes, lengths, label=slope.round(2))
ax3.set_title('Length change with varying ELA change')
ax3.legend(title='Slope')
mean_thickness = []
static_thickness = []
for basin, data in BASINS.items():
glacier.max_bed_height = data['bed_height']
glacier.length = data['length_of_segment']
glacier.slope = calc_slope(data['min_surface'], data['max_surface'],
data['length_of_segment'])
max_surfaces.append(data['max_surface'])
ela.append(glacier.ela_from_length())
critical_ela.append(glacier.critical_ela())
measured_length.append(data['length_of_segment'] / 1000)
linear_equilibrium_length.append(
glacier.linear_equilibrium_length(
ela[-1], thickness=data['mean_ice_thickness']) / 1000)
measured_thickness.append(data['mean_ice_thickness'])
mean_thickness.append(glacier.mean_thickness())
static_thickness.append(glacier.static_mean_thickness())
fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(14, 6))
x_axis = [1, 2, 3, 4]
labels = dict(textcoords='offset points',
ha='right',
va='bottom',
bbox=dict(boxstyle='round,pad=0.4', fc='wheat', alpha=0.8))
ax1.scatter(x_axis, critical_ela, label='critical ELA', s=100)
ax1.scatter(x_axis, ela, label='ELA from Length', marker='*', s=100)
