Surface roughness is a library that processes 3D surface STL data and produces oriented roughness metrics.
If you wish to use this work, please cite this paper according to CITATION.cff.
Installation is completed by
pip install surface-roughness
from surface_roughness import Surface, SampleWindow, roughness_map
# Load Surface STL File into Python
surface = Surface(path="example_surface.stl")
# Specify SampleWindow parameters
w = SampleWindow(is_circle=True,radius=2) # in units of STL mesh
# Generate roughness map object based on method presented in Magsipoc & Grasselli (2023) with parameters
map = roughness_map(
surface, # surface object required to interact with library
'delta_t', # Method for analyzing roughness
w, # SampleWindow object
0.5, # Distance between windows in mesh units
1 # Number of vertices for mesh facet to be included in window sampling
)
# Start subsampling process
map.sample()
# Evaluate roughness of subsamples
map.evaluate()
# Analyze directional roughness statistics
map.analyze_directional_roughness('delta_t')
map.analyze_directional_roughness('delta*_t')
# Pickle map to save analysis (optional)
with ('example_surface_r2_s0.5.pickle','wb') as f:
pickle.dump(map, f)
# Save data to VTK for visualization
map.to_vtk('example_surface_r2_s0.5','delta_t')from surface_roughness import Surface
import matplotlib.pyplot as plt # For plotting graphs
surface = Surface('example_surface.stl')
# Calculate roughness from Tatone and Grasselli (2009) doi: 10.1063/1.3266964
surface.evaluate_thetamax_cp1()
az = surface.thetamax_cp1('az') # Get azimuth correlating with analysis
thetamaxcp1_roughness = surface.thetamax_cp1('thetamax_cp1')
# Plot surface roughness
plt.figure()
plt.polar(az,thetamaxcp1_roughness,label=r'$\theta^*_{max}/(C+1)$')
plt.legend()
# Calculate roughness from Babanouri and Karami Nasab (2017) doi: 10.1007/s00603-016-1139-1
surface.evaluate_delta_t()
az_t = s.delta_t('az')
delta_t = s.delta_t('delta_t')
az_a = s.delta_a('az')
delta_a = s.delta_a('delta_a')
az_n = s.delta_n('az')
delta_n = s.delta_n('delta_n')
plt.figure()
plt.polar(az_t,delta_t,label='$\Delta_T$')
plt.polar(az_a,delta_a,label='$\Delta_A$')
plt.polar(az_n,delta_n,label='$\Delta_N$')
plt.legend()