- Renamed devo to devo_numpy.

- drx_numba rename, and updates due to some hpc.geometry renames.
- EvoPlotter went missing.
- Some __init__ updates.
- Added beam stiffness to mass matrix calcs, updated drx_numpy _create_arrays().

Author: andrewtliew

src/compas/hpc/__init__.py

@@ -13,58 +13,62 @@
     For now, don't use it for anything important :)
 
 
+algorithms
+==========
+
+.. autosummary::
+    :toctree: generated/
+
+    drx_numba
+
+
+geometry
+========
+
+.. autosummary::
+    :toctree: generated/
+
+    sum_vectors_numba
+    norm_vector_numba
+    norm_vectors_numba
+    length_vector_numba
+    length_vector_xy_numba
+    length_vector_sqrd_numba
+    length_vector_sqrd_xy_numba
+    scale_vector_numba
+    scale_vector_xy_numba
+    scale_vectors_numba
+    scale_vectors_xy_numba
+    normalize_vector_numba
+    normalize_vector_xy_numba
+    normalize_vectors_numba
+    normalize_vectors_xy_numba
+    power_vector_numba
+    power_vectors_numba
+    square_vector_numba
+    square_vectors_numba
+    add_vectors_numba
+    add_vectors_xy_numba
+    subtract_vectors_numba
+    subtract_vectors_xy_numba
+    multiply_vectors_numba
+    multiply_vectors_xy_numba
+    divide_vectors_numba
+    divide_vectors_xy_numba
+    cross_vectors_numba
+    cross_vectors_xy_numba
+    dot_vectors_numba
+    dot_vectors_xy_numba
+    multiply_matrices_numba
+    multiply_matrix_vector_numba
+
+
 cuda
 ====
 
 .. autosummary::
     :toctree: generated/
 
-    cuda_diag
-    cuda_eye
-    cuda_get
-    cuda_give
-    cuda_ones
-    cuda_random
-    cuda_real
-    cuda_reshape
-    cuda_flatten
-    cuda_tile
-    cuda_zeros
-    cuda_conj
-    cuda_cross
-    cuda_det
-    cuda_dot
-    cuda_eig
-    cuda_hermitian
-    cuda_inv
-    cuda_normrow
-    cuda_pinv
-    cuda_svd
-    cuda_trace
-    cuda_transpose
-    cuda_abs
-    cuda_argmax
-    cuda_argmin
-    cuda_acos
-    cuda_asin
-    cuda_atan
-    cuda_ceil
-    cuda_cos
-    cuda_cosh
-    cuda_exp
-    cuda_floor
-    cuda_log
-    cuda_max
-    cuda_min
-    cuda_mean
-    cuda_sin
-    cuda_sinh
-    cuda_sqrt
-    cuda_sum
-    cuda_tan
-    cuda_tanh
-    cuda_device
-
 
 euler
 =====
@@ -87,20 +91,6 @@
     sync_folder_to_euler
 
 
-numba
-=====
-
-.. autosummary::
-    :toctree: generated/
-
-    numba_devo
-    numba_drx
-    numba_cross
-    numba_vdot
-    numba_dot
-    numba_length
-
-
 opencl
 ======
 
@@ -110,14 +100,12 @@
 
 """
 
-from .cuda import *
-from .numba import *
-# from .opencl import *
+from .geometry import *
 from .euler import *
+from .algorithms import *
 
-from .cuda import __all__ as a
-from .numba import __all__ as b
-# from .opencl import __all__ as c
-from .euler import __all__ as d
+from .geometry import __all__ as a
+from .euler import __all__ as b
+from .algorithms import __all__ as c
 
-__all__ = a + b  + d
+__all__ = a + b + c

src/compas/hpc/algorithms/__init__.py

@@ -0,0 +1,5 @@
+from .drx_numba import drx_numba
+
+from .drx_numba import __all__ as a
+
+__all__ = a

src/compas/hpc/numba/drx.py renamed to src/compas/hpc/algorithms/drx_numba.py

@@ -16,9 +16,9 @@
 from compas.numerical.algorithms.drx_numpy import _beam_data
 from compas.numerical.algorithms.drx_numpy import _create_arrays
 
-from compas.hpc.numba.geometry import numba_cross
-from compas.hpc.numba.geometry import numba_vdot
-from compas.hpc.numba.geometry import numba_length
+from compas.hpc import cross_vectors_numba
+from compas.hpc import dot_vectors_numba
+from compas.hpc import length_vector_numba
 
 
 from time import time
@@ -31,11 +31,11 @@
 
 
 __all__ = [
-    'numba_drx',
+    'drx_numba',
 ]
 
 
-def numba_drx(network, factor=1.0, tol=0.1, steps=10000, summary=0, update=False):
+def drx_numba(network, factor=1.0, tol=0.1, steps=10000, summary=0, update=False):
     """ Run Numba accelerated dynamic relaxation analysis.
 
     Parameters:
@@ -198,33 +198,33 @@ def drx_solver(tol, steps, factor, u, v, X, ks, l0, f0, ind_c, ind_t, rows, cols
                 Qa = Xi - Xs
                 Qb = Xf - Xi
                 Qc = Xf - Xs
-                Qn = numba_cross(Qa, Qb)
+                Qn = cross_vectors_numba(Qa, Qb)
                 mu = 0.5 * (Xf - Xs)
-                La = numba_length(Qa)
-                Lb = numba_length(Qb)
-                Lc = numba_length(Qc)
-                LQn = numba_length(Qn)
-                Lmu = numba_length(mu)
+                La = length_vector_numba(Qa)
+                Lb = length_vector_numba(Qb)
+                Lc = length_vector_numba(Qc)
+                LQn = length_vector_numba(Qn)
+                Lmu = length_vector_numba(mu)
                 a = arccos((La**2 + Lb**2 - Lc**2) / (2 * La * Lb))
                 k = 2 * sin(a) / Lc
                 ex = Qn / LQn
                 ez = mu / Lmu
-                ey = numba_cross(ez, ex)
+                ey = cross_vectors_numba(ez, ex)
                 K = k * Qn / LQn
-                Kx = numba_vdot(K, ex) * ex
-                Ky = numba_vdot(K, ey) * ey
+                Kx = dot_vectors_numba(K, ex) * ex
+                Ky = dot_vectors_numba(K, ey) * ey
                 Mc = EIx[i] * Kx + EIy[i] * Ky
-                cma = numba_cross(Mc, Qa)
-                cmb = numba_cross(Mc, Qb)
-                ua = cma / numba_length(cma)
-                ub = cmb / numba_length(cmb)
-                c1 = numba_cross(Qa, ua)
-                c2 = numba_cross(Qb, ub)
-                Lc1 = numba_length(c1)
-                Lc2 = numba_length(c2)
+                cma = cross_vectors_numba(Mc, Qa)
+                cmb = cross_vectors_numba(Mc, Qb)
+                ua = cma / length_vector_numba(cma)
+                ub = cmb / length_vector_numba(cmb)
+                c1 = cross_vectors_numba(Qa, ua)
+                c2 = cross_vectors_numba(Qb, ub)
+                Lc1 = length_vector_numba(c1)
+                Lc2 = length_vector_numba(c2)
                 Ms = Mc[0]**2 + Mc[1]**2 + Mc[2]**2
-                Sa = ua * Ms * Lc1 / (La * numba_vdot(Mc, c1))
-                Sb = ub * Ms * Lc2 / (Lb * numba_vdot(Mc, c2))
+                Sa = ua * Ms * Lc1 / (La * dot_vectors_numba(Mc, c1))
+                Sb = ub * Ms * Lc2 / (Lb * dot_vectors_numba(Mc, c2))
                 S[inds[i], :] += Sa
                 S[indi[i], :] -= Sa + Sb
                 S[indf[i], :] += Sb