[python] Remove dead code

src/python/pffdtd/common/myasserts.py → src/python/pffdtd/common/asserts.py

@@ -13,15 +13,13 @@
 ##############################################################################
 
 import numpy as np
+
+
 def assert_np_array_float(x):
-    assert isinstance(x,np.ndarray)
-    assert x.dtype in [np.dtype('float32'),np.dtype('float64')]
+    assert isinstance(x, np.ndarray)
+    assert x.dtype in [np.dtype('float32'), np.dtype('float64')]
 
-def assert_np_array_complex(x):
-    assert isinstance(x,np.ndarray)
-    #allow float or complex
-    assert x.dtype in [np.dtype('complex64'),np.dtype('complex128'),np.dtype('float32'),np.dtype('float64')]
 
-#python 'int' is arbitrary size
+# python 'int' is arbitrary size
 def assert_is_int(x):
-    assert isinstance(x,(int,np.integer))
+    assert isinstance(x, (int, np.integer))

src/python/pffdtd/common/misc.py

@@ -0,0 +1,32 @@
+import multiprocessing as mp
+from pathlib import Path
+
+
+def get_default_nprocs():
+    return max(1, int(0.8*mp.cpu_count()))
+
+
+def clear_dat_folder(dat_folder_str=None):
+    # clear dat folder
+    dat_path = Path(dat_folder_str)
+    if not dat_path.exists():
+        dat_path.mkdir(parents=True)
+    else:
+        assert dat_path.is_dir()
+
+    assert dat_path.exists()
+    assert dat_path.is_dir()
+    for f in dat_path.glob('*'):
+        try:
+            f.unlink()
+        except OSError as e:
+            print("Error: %s : %s" % (f, e.strerror))
+
+
+def yes_or_no(question):
+    while "the answer is invalid":
+        reply = str(input(question+' (y/n): ')).lower().strip()
+        if reply[:1] == 'y':
+            return True
+        if reply[:1] == 'n':
+            return False

src/python/pffdtd/common/wavfile.py

@@ -0,0 +1,18 @@
+import numpy as np
+import scipy.io.wavfile
+
+
+def wavread(fname):
+    fs, data = scipy.io.wavfile.read(fname)  # reads in (Nsamples,Nchannels)
+    if data.dtype == np.int16:
+        data = data/32768.0
+        fs = np.float64(fs)
+    return fs, np.float64(data.T)
+
+
+def wavwrite(fname, fs, data):
+    # expects (Nchannels,Nsamples), this will also assert that
+    data = np.atleast_2d(data)
+    # reads in (Nsamples,Nchannels)
+    scipy.io.wavfile.write(fname, int(fs), np.float32(data.T))
+    print(f'wrote {fname} at fs={fs/1000:.2f} kHz')

src/python/pffdtd/geometry/box.py

@@ -1,61 +1,75 @@
 # SPDX-License-Identifier: MIT
+from typing import Any
 
 import numpy as np
-from numpy import array as npa
 import numpy.random as npr
-from pffdtd.geometry.math import mydefault,rotmatrix_ax_ang
+from pffdtd.geometry.math import rotmatrix_ax_ang
+
+
+def mydefault(a: Any, default: Any):
+    # only used in box
+    if a is None:
+        a = default
+    return a
+
 
 class Box:
     """This is a class for a box. Used in a few places (vox_grid, tri_box).
     """
-    def __init__(self,Lx=None,Ly=None,Lz=None,Rax=None,Rang=None,shift=None,centered=True):
-        #defaults
-        Lx = mydefault(Lx,1.0)
-        Ly = mydefault(Ly,1.0)
-        Lz = mydefault(Lz,1.0)
-        Rax = mydefault(Rax,npa([1.,1.,1.]))
-        Rang = mydefault(Rang,0.)
-        shift = mydefault(shift,npa([0.,0.,0.]))
+
+    def __init__(self, Lx=None, Ly=None, Lz=None, Rax=None, Rang=None, shift=None, centered=True):
+        # defaults
+        Lx = mydefault(Lx, 1.0)
+        Ly = mydefault(Ly, 1.0)
+        Lz = mydefault(Lz, 1.0)
+        Rax = mydefault(Rax, np.array([1., 1., 1.]))
+        Rang = mydefault(Rang, 0.)
+        shift = mydefault(shift, np.array([0., 0., 0.]))
 
         self.centered = centered
 
-        self.init(Lx,Ly,Lz,Rax,Rang,shift)
+        self.init(Lx, Ly, Lz, Rax, Rang, shift)
 
-    def init(self,Lx,Ly,Lz,Rax,Rang,shift):
+    def init(self, Lx, Ly, Lz, Rax, Rang, shift):
 
-        verts = npa([[0.,0.,0.],[0.,0.,Lz],[0.,Ly,0.],[0.,Ly,Lz],[Lx,0.,0.],[Lx,0.,Lz],[Lx,Ly,0.],[Lx,Ly,Lz]])
+        verts = np.array([[0., 0., 0.], [0., 0., Lz], [0., Ly, 0.], [0., Ly, Lz], [
+                    Lx, 0., 0.], [Lx, 0., Lz], [Lx, Ly, 0.], [Lx, Ly, Lz]])
         if self.centered:
-            verts -= 0.5*npa([Lx,Ly,Lz])
+            verts -= 0.5*np.array([Lx, Ly, Lz])
 
-        A = npa([[-1.,0.,0.],[0.,-1.,0.],[0.,0.,-1.],[1.,0.,0.],[0.,1.,0.],[0.,0.,1.]])
+        A = np.array([[-1., 0., 0.], [0., -1., 0.], [0., 0., -1.],
+                [1., 0., 0.], [0., 1., 0.], [0., 0., 1.]])
 
         if self.centered:
-            b = 0.5*npa([Lx,Ly,Lz,Lx,Ly,Lz])
+            b = 0.5*np.array([Lx, Ly, Lz, Lx, Ly, Lz])
         else:
-            b = npa([0,0,0,Lx,Ly,Lz])
+            b = np.array([0, 0, 0, Lx, Ly, Lz])
 
-        #rotate verts
-        R = rotmatrix_ax_ang(Rax,Rang)
+        # rotate verts
+        R = rotmatrix_ax_ang(Rax, Rang)
         verts = verts.dot(R.T) + shift
 
-        #get AABB min/max
-        bmin = np.amin(verts,0)
-        bmax = np.amax(verts,0)
+        # get AABB min/max
+        bmin = np.amin(verts, 0)
+        bmax = np.amax(verts, 0)
 
-        #update A,b
+        # update A,b
         A = A.dot(R.T)
         b += shift.dot(A.T)
 
-        #set member variables
+        # set member variables
         self.A = A
         self.b = b
         self.verts = verts
         self.bmin = bmin
         self.bmax = bmax
 
-        self.edges = npa([[0,1],[0,2],[0,4],[1,3],[1,5],[2,3],[2,6],[4,5],[4,6],[3,7],[5,7],[6,7]])
-        self.tris = npa([[0,1,3],[0,3,2],[1,7,3],[1,5,7],[0,2,6],[0,6,4],[4,7,5],[4,6,7],[2,3,7],[2,7,6],[0,5,1],[0,4,5]])
-        self.quads = npa([[0,1,3,2],[0,4,5,1],[4,6,7,5],[1,5,7,3],[2,3,7,6],[0,2,6,4]])
+        self.edges = np.array([[0, 1], [0, 2], [0, 4], [1, 3], [1, 5], [2, 3], [
+                         2, 6], [4, 5], [4, 6], [3, 7], [5, 7], [6, 7]])
+        self.tris = np.array([[0, 1, 3], [0, 3, 2], [1, 7, 3], [1, 5, 7], [0, 2, 6], [
+                        0, 6, 4], [4, 7, 5], [4, 6, 7], [2, 3, 7], [2, 7, 6], [0, 5, 1], [0, 4, 5]])
+        self.quads = np.array([[0, 1, 3, 2], [0, 4, 5, 1], [4, 6, 7, 5], [
+                         1, 5, 7, 3], [2, 3, 7, 6], [0, 2, 6, 4]])
 
     def randomise(self):
         Lx = 10*npr.random()
@@ -64,111 +78,128 @@ def randomise(self):
         Rax = npr.rand(3)
         Rang = (-1.0 + 2.0*npr.random())*90
         shift = npr.randn(3)*2 - 1
-        self.init(Lx,Ly,Lz,Rax,Rang,shift)
+        self.init(Lx, Ly, Lz, Rax, Rang, shift)
 
-    #just draw (no show)
-    def _draw(self,backend='mayavi',r=None,color=(0,1,0)):
+    # just draw (no show)
+    def _draw(self, backend='mayavi', r=None, color=(0, 1, 0)):
         box = self
 
         if backend == 'mayavi':
             from mayavi import mlab
             for edge in box.edges:
-                mlab.plot3d(box.verts[edge,0],box.verts[edge,1],box.verts[edge,2],color=color,tube_radius=r)
+                mlab.plot3d(box.verts[edge, 0], box.verts[edge, 1],
+                            box.verts[edge, 2], color=color, tube_radius=r)
             mlab.draw()
             print('drawing box..')
         else:
             raise
 
-    #draw and show
-    def draw(self,backend='mayavi',r=None,color=(0,1,0)):
+    # draw and show
+    def draw(self, backend='mayavi', r=None, color=(0, 1, 0)):
         box = self
         if backend == 'mayavi':
             from mayavi import mlab
             from tvtk.api import tvtk
             fig = mlab.gcf()
             box._draw()
             box._draw_faces()
-            fake_verts = np.c_[box.bmin,box.bmax] #stacks as column vectors 2x3
-            mlab.plot3d(fake_verts[0],fake_verts[1],fake_verts[2],transparent=True,opacity=0)
+            # stacks as column vectors 2x3
+            fake_verts = np.c_[box.bmin, box.bmax]
+            mlab.plot3d(fake_verts[0], fake_verts[1],
+                        fake_verts[2], transparent=True, opacity=0)
             mlab.axes(xlabel='x', ylabel='y', zlabel='z', color=(0., 0., 0.))
             fig.scene.interactor.interactor_style = tvtk.InteractorStyleTerrain()
             mlab.show()
         else:
             raise
 
-    def show(self,backend='mayavi'):
+    def show(self, backend='mayavi'):
         if backend == 'mayavi':
             from mayavi import mlab
             mlab.show()
         elif backend == 'mplot3d':
             import matplotlib.pyplot as plt
             plt.show()
 
-    #draw faces without show()
-    def _draw_faces(self,backend='mayavi'):
+    # draw faces without show()
+    def _draw_faces(self, backend='mayavi'):
         box = self
 
         if backend == 'mayavi':
             from mayavi import mlab
-            x = box.verts[:,0]; y = box.verts[:,1]; z = box.verts[:,2]
-            mlab.triangular_mesh(x,y,z,box.tris,color=(0,0,0),opacity=0.6)
+            x = box.verts[:, 0]
+            y = box.verts[:, 1]
+            z = box.verts[:, 2]
+            mlab.triangular_mesh(
+                x, y, z, box.tris, color=(0, 0, 0), opacity=0.6)
             mlab.draw()
             print('drawing box faces..')
         else:
             raise
 
+
 def main():
-    #no shift, no rotation
+    # no shift, no rotation
     Lx = npr.random()
     Ly = npr.random()
     Lz = npr.random()
     print(f'Lx = {Lx:.2f}, Ly = {Ly:.2f}, Lz = {Lz:.2f}')
 
-    box = Box(Lx,Ly,Lz)
-    print('box 0 ... bmin = %.2f,%.2f,%.2f' % (box.bmin[0],box.bmin[1],box.bmin[2]))
-    print('box 0 ... bmax =  %.2f,%.2f,%.2f' % (box.bmax[0],box.bmax[1],box.bmax[2]))
-    assert np.all(np.mean(box.verts,0).dot(box.A.T) < box.b)
+    box = Box(Lx, Ly, Lz)
+    print('box 0 ... bmin = %.2f,%.2f,%.2f' %
+          (box.bmin[0], box.bmin[1], box.bmin[2]))
+    print('box 0 ... bmax =  %.2f,%.2f,%.2f' %
+          (box.bmax[0], box.bmax[1], box.bmax[2]))
+    assert np.all(np.mean(box.verts, 0).dot(box.A.T) < box.b)
     assert np.all((box.verts*(1-1e-4)).dot(box.A.T) < box.b)
     assert np.any((box.verts*(1+1e-4)).dot(box.A.T) > box.b)
 
-    #rotated
+    # rotated
     Lx = npr.random()
     Ly = npr.random()
     Lz = npr.random()
-    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx,Ly,Lz))
+    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx, Ly, Lz))
     Rax = npr.rand(3)
     Rang = (-1.0 + 2.0*npr.random())*90
-    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' % (Rax[0],Rax[1],Rax[2],Rang))
+    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' %
+          (Rax[0], Rax[1], Rax[2], Rang))
     print()
 
-    box = Box(Lx,Ly,Lz,Rax,Rang)
-    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx,Ly,Lz))
-    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' % (Rax[0],Rax[1],Rax[2],Rang))
-    print('box 1 ... bmin = %.2f,%.2f,%.2f' % (box.bmin[0],box.bmin[1],box.bmin[2]))
-    print('box 1 ... bmax =  %.2f,%.2f,%.2f' % (box.bmax[0],box.bmax[1],box.bmax[2]))
-    assert np.all(np.mean(box.verts,0).dot(box.A.T) < box.b)
+    box = Box(Lx, Ly, Lz, Rax, Rang)
+    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx, Ly, Lz))
+    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' %
+          (Rax[0], Rax[1], Rax[2], Rang))
+    print('box 1 ... bmin = %.2f,%.2f,%.2f' %
+          (box.bmin[0], box.bmin[1], box.bmin[2]))
+    print('box 1 ... bmax =  %.2f,%.2f,%.2f' %
+          (box.bmax[0], box.bmax[1], box.bmax[2]))
+    assert np.all(np.mean(box.verts, 0).dot(box.A.T) < box.b)
     assert np.all((box.verts*(1-1e-4)).dot(box.A.T) < box.b)
     assert np.any((box.verts*(1+1e-4)).dot(box.A.T) > box.b)
     print()
 
-    #shifted and rotated
+    # shifted and rotated
     Lx = npr.random()
     Ly = npr.random()
     Lz = npr.random()
-    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx,Ly,Lz))
+    print('Lx = %.2f, Ly = %.2f, Lz = %.2f' % (Lx, Ly, Lz))
     Rax = npr.rand(3)
     Rang = (-1.0 + 2.0*npr.random())*90
-    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' % (Rax[0],Rax[1],Rax[2],Rang))
+    print('Rax = %.2f,%.2f,%.2f, Rang = %.2f degrees' %
+          (Rax[0], Rax[1], Rax[2], Rang))
     shift = npr.rand(3)*100
-    print('shift = %.2f,%.2f,%.2f' % (shift[0],shift[1],shift[2]))
-
-    box = Box(Lx,Ly,Lz,Rax,Rang,shift)
-    print('box 2 ... bmin = %.2f,%.2f,%.2f' % (box.bmin[0],box.bmin[1],box.bmin[2]))
-    print('box 2 ... bmax =  %.2f,%.2f,%.2f' % (box.bmax[0],box.bmax[1],box.bmax[2]))
-    assert np.all(np.mean(box.verts,0).dot(box.A.T) < box.b)
+    print('shift = %.2f,%.2f,%.2f' % (shift[0], shift[1], shift[2]))
+
+    box = Box(Lx, Ly, Lz, Rax, Rang, shift)
+    print('box 2 ... bmin = %.2f,%.2f,%.2f' %
+          (box.bmin[0], box.bmin[1], box.bmin[2]))
+    print('box 2 ... bmax =  %.2f,%.2f,%.2f' %
+          (box.bmax[0], box.bmax[1], box.bmax[2]))
+    assert np.all(np.mean(box.verts, 0).dot(box.A.T) < box.b)
     assert np.all((((box.verts-shift)*(1-1e-4))+shift).dot(box.A.T) < box.b)
     assert np.any((((box.verts-shift)*(1+1e-4))+shift).dot(box.A.T) > box.b)
     box.draw()
 
+
 if __name__ == '__main__':
     main()