diff options
author | Christian C <cc@localhost> | 2024-11-11 12:29:32 -0800 |
---|---|---|
committer | Christian C <cc@localhost> | 2024-11-11 12:29:32 -0800 |
commit | b85ee9d64a536937912544c7bbd5b98b635b7e8d (patch) | |
tree | cef7bc17d7b29f40fc6b1867d0ce0a742d5583d0 /code/sunlab/common/mathlib/base.py |
Initial commit
Diffstat (limited to 'code/sunlab/common/mathlib/base.py')
-rw-r--r-- | code/sunlab/common/mathlib/base.py | 57 |
1 files changed, 57 insertions, 0 deletions
diff --git a/code/sunlab/common/mathlib/base.py b/code/sunlab/common/mathlib/base.py new file mode 100644 index 0000000..38ab14c --- /dev/null +++ b/code/sunlab/common/mathlib/base.py @@ -0,0 +1,57 @@ +import numpy as np + + +def angle(a, b): + """# Get Angle Between Row Vectors""" + from numpy import arctan2, pi + + theta_a = arctan2(a[:, 1], a[:, 0]) + theta_b = arctan2(b[:, 1], b[:, 0]) + d_theta = theta_b - theta_a + assert (-pi <= d_theta) and (d_theta <= pi), "Theta difference outside of [-π,π]" + return d_theta + + +def normalize(column): + """# Normalize Column Vector""" + from numpy.linalg import norm + + return column / norm(column, axis=0) + + +def winding(xy_grid, trajectory_start, trajectory_end): + """# Get Winding Number on Grid""" + from numpy import zeros, cross, clip, arcsin + + trajectories = trajectory_end - trajectory_start + winding = zeros((xy_grid.shape[0])) + for idx, trajectory in enumerate(trajectories): + r = xy_grid - trajectory_start[idx] + cross = cross(normalize(trajectory), normalize(r)) + cross = clip(cross, -1, 1) + theta = arcsin(cross) + winding += theta + return winding + + +def vorticity(xy_grid, trajectory_start, trajectory_end): + """# Get Vorticity Number on Grid""" + from numpy import zeros, cross + + trajectories = trajectory_end - trajectory_start + vorticity = zeros((xy_grid.shape[0])) + for idx, trajectory in enumerate(trajectories): + r = xy_grid - trajectory_start[idx] + vorticity += cross(normalize(trajectory), normalize(r)) + return vorticity + + +def data_range(data): + """# Get the range of values for each row""" + from numpy import min, max + + return min(data, axis=0), max(data, axis=0) + + +np.normalize = normalize +np.range = data_range |