1.4.0 Upgrade

Added Shapely Support

PyMieScatt.egg-info/PKG-INFO

@@ -1,13 +1,13 @@
 Metadata-Version: 1.1
 Name: PyMieScatt
-Version: 1.3.7
+Version: 1.4.0
 Summary: A collection of forward and inverse Mie solving routines based on Bohren and Huffman's Mie Theory derivations.
 Home-page: http://air.eece.wustl.edu/people/ben-sumlin/
 Author: Benjamin Sumlin
 Author-email: bsumlin@wustl.edu
 License: GPL
 Description-Content-Type: UNKNOWN
-Description: 1.3.7 - Added error bounds as an option for the graphical inversion method. Added new automatic inversion methods Inversion() and Inversion_SD(). Significantly improved the iterative methods.
+Description: 1.4.0 - Added error bounds as an option for the graphical inversion method. Added new automatic inversion methods Inversion() and Inversion_SD(). Significantly improved the iterative methods.
         Docs are hosted at `ReadTheDocs <http://pymiescatt.readthedocs.io/>`_.
 Keywords: Mie Rayleigh scattering absorption extinction light refraction
 Platform: UNKNOWN

PyMieScatt.egg-info/requires.txt

@@ -1,3 +1,4 @@
 numpy
 scipy
 matplotlib
+shapely

PyMieScatt/Inverse.py

@@ -6,6 +6,7 @@
 from matplotlib.offsetbox import AnchoredText
 from scipy.ndimage import zoom
 from scipy.integrate import trapz
+from shapely import geometry
 import warnings
 
 def coerceDType(d):
@@ -161,31 +162,10 @@ def ContourIntersection(Qsca,Qabs,wavelength,diameter,Qback=None,nMin=1,nMax=3,k
     ax.contourf(n,k,QbackList,backErrorLevels,origin='lower',colors=('green'),alpha=0.15)
     ax.contour(n,k,QbackList,backErrorLevels,origin='lower',linewidths=0.5,colors=('green'),alpha=0.5)
 
-  distinctScaPaths = len(scaChart.collections[0].get_paths())
-  distinctAbsPaths = len(absChart.collections[0].get_paths())
-  if Qback is not None:
-    distinctBackPaths = len(backChart.collections[0].get_paths())
-  scaVertices = []
-  absVertices = []
-  if Qback is not None:
-    backVertices = []
-  for i in range(distinctScaPaths):
-    scaVertices.append(scaChart.collections[0].get_paths()[i].vertices)
-  for i in range(distinctAbsPaths):
-    absVertices.append(absChart.collections[0].get_paths()[i].vertices)
-  if Qback is not None:
-    for i in range(distinctBackPaths):
-      backVertices.append(backChart.collections[0].get_paths()[i].vertices)
-
-  scaVertices = np.concatenate(scaVertices)
-  absVertices = np.concatenate(absVertices)
-  if Qback is not None:
-    backVertices = np.concatenate(backVertices)
-
-  nSolution,kSolution = find_intersections(scaVertices,absVertices)
+  nSolution,kSolution = find_intersections(scaChart,absChart)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
   if Qback is not None:
-    oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
+    oneTrueN,oneTrueK = find_intersections(backChart,absChart)
     _these = [np.round(x+y*1j,3) for x,y in zip(oneTrueN,oneTrueK)]
     _match = list(set(np.round(trials,3)).intersection(np.round(_these,3)))
     if len(_match) > 0:
@@ -385,31 +365,10 @@ def ContourIntersection_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.0000
     ax.contourf(n,k,BbackList,backErrorLevels,origin='lower',colors=('green'),alpha=0.15)
     ax.contour(n,k,BbackList,backErrorLevels,origin='lower',linewidths=0.5,colors=('green'),alpha=0.5)
 
-  distinctScaPaths = len(scaChart.collections[0].get_paths())
-  distinctAbsPaths = len(absChart.collections[0].get_paths())
-  if Bback is not None:
-    distinctBackPaths = len(backChart.collections[0].get_paths())
-  scaVertices = []
-  absVertices = []
-  if Bback is not None:
-    backVertices = []
-  for i in range(distinctScaPaths):
-    scaVertices.append(scaChart.collections[0].get_paths()[i].vertices)
-  for i in range(distinctAbsPaths):
-    absVertices.append(absChart.collections[0].get_paths()[i].vertices)
-  if Bback is not None:
-    for i in range(distinctBackPaths):
-      backVertices.append(backChart.collections[0].get_paths()[i].vertices)
-
-  scaVertices = np.concatenate(scaVertices)
-  absVertices = np.concatenate(absVertices)
-  if Bback is not None:
-    backVertices = np.concatenate(backVertices)
-
-  nSolution,kSolution = find_intersections(scaVertices,absVertices)
+  nSolution,kSolution = find_intersections(scaChart,absChart)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
   if Bback is not None:
-    oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
+    oneTrueN,oneTrueK = find_intersections(backChart,absChart)
     _these = [np.round(x+y*1j,3) for x,y in zip(oneTrueN,oneTrueK)]
     _match = list(set(np.round(trials,3)).intersection(np.round(_these,3)))
     if len(_match) > 0:
@@ -523,29 +482,23 @@ def ContourIntersection_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.0000
   return solutionSet,forwardCalculations,solutionErrors, fig, ax, graphElements
 
 def find_intersections(A,B):
-  arrayMinimum = lambda x1, x2: np.where(x1<x2, x1, x2)
-  arrayMaximum = lambda x1, x2: np.where(x1>x2, x1, x2)
-  arrayAll = lambda abools: np.dstack(abools).all(axis=2)
-  slope = lambda line: (lambda d: d[:,1]/d[:,0])(np.diff(line, axis=0))
-
-  x11, x21 = np.meshgrid(A[:-1, 0], B[:-1, 0])
-  x12, x22 = np.meshgrid(A[1:, 0], B[1:, 0])
-  y11, y21 = np.meshgrid(A[:-1, 1], B[:-1, 1])
-  y12, y22 = np.meshgrid(A[1:, 1], B[1:, 1])
-
-  m1, m2 = np.meshgrid(slope(A), slope(B))
-  # Here we use masked arrays to properly treat the rare case where a line segment is perfectly vertical
-  _m1 = np.ma.masked_array(m1,m1==-np.inf)
-  _m2 = np.ma.masked_array(m2,m2==-np.inf)
-  yi = (_m1*(x21-x11-y21/_m2)+y11)/(1-_m1/_m2)
-  xi = (yi-y21)/_m2+x21
-
-  xconds = (arrayMinimum(x11, x12) < xi, xi <= arrayMaximum(x11, x12),
-            arrayMinimum(x21, x22) < xi, xi <= arrayMaximum(x21, x22) )
-  yconds = (arrayMinimum(y11, y12) < yi, yi <= arrayMaximum(y11, y12),
-            arrayMinimum(y21, y22) < yi, yi <= arrayMaximum(y21, y22) )
-
-  return xi[arrayAll(xconds)], yi[arrayAll(yconds)]
+  X = []
+  Y = []
+  for p1 in A.collections[0].get_paths():
+    for p2 in B.collections[0].get_paths():
+      v1 = p1.vertices
+      v2 = p2.vertices
+
+      poly1 = geometry.LineString(v1)
+      poly2 = geometry.LineString(v2)
+
+      sol = poly1.intersection(poly2)
+
+      for s in sol:
+        X.append(s.x)
+        Y.append(s.y)
+
+  return X,Y
 
 def SurveyIteration(Qsca,Qabs,wavelength,diameter,tolerance=0.0005):
 #  http://pymiescatt.readthedocs.io/en/latest/inverse.html#IterativeInversion

PyMieScatt/_version.py

@@ -1 +1 @@
-__version__ = "1.3.7"
+__version__ = "1.4.0"

build/lib/PyMieScatt/Inverse.py

@@ -6,6 +6,7 @@
 from matplotlib.offsetbox import AnchoredText
 from scipy.ndimage import zoom
 from scipy.integrate import trapz
+from shapely import geometry
 import warnings
 
 def coerceDType(d):
@@ -161,31 +162,10 @@ def ContourIntersection(Qsca,Qabs,wavelength,diameter,Qback=None,nMin=1,nMax=3,k
     ax.contourf(n,k,QbackList,backErrorLevels,origin='lower',colors=('green'),alpha=0.15)
     ax.contour(n,k,QbackList,backErrorLevels,origin='lower',linewidths=0.5,colors=('green'),alpha=0.5)
 
-  distinctScaPaths = len(scaChart.collections[0].get_paths())
-  distinctAbsPaths = len(absChart.collections[0].get_paths())
-  if Qback is not None:
-    distinctBackPaths = len(backChart.collections[0].get_paths())
-  scaVertices = []
-  absVertices = []
-  if Qback is not None:
-    backVertices = []
-  for i in range(distinctScaPaths):
-    scaVertices.append(scaChart.collections[0].get_paths()[i].vertices)
-  for i in range(distinctAbsPaths):
-    absVertices.append(absChart.collections[0].get_paths()[i].vertices)
-  if Qback is not None:
-    for i in range(distinctBackPaths):
-      backVertices.append(backChart.collections[0].get_paths()[i].vertices)
-
-  scaVertices = np.concatenate(scaVertices)
-  absVertices = np.concatenate(absVertices)
-  if Qback is not None:
-    backVertices = np.concatenate(backVertices)
-
-  nSolution,kSolution = find_intersections(scaVertices,absVertices)
+  nSolution,kSolution = find_intersections(scaChart,absChart)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
   if Qback is not None:
-    oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
+    oneTrueN,oneTrueK = find_intersections(backChart,absChart)
     _these = [np.round(x+y*1j,3) for x,y in zip(oneTrueN,oneTrueK)]
     _match = list(set(np.round(trials,3)).intersection(np.round(_these,3)))
     if len(_match) > 0:
@@ -385,31 +365,10 @@ def ContourIntersection_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.0000
     ax.contourf(n,k,BbackList,backErrorLevels,origin='lower',colors=('green'),alpha=0.15)
     ax.contour(n,k,BbackList,backErrorLevels,origin='lower',linewidths=0.5,colors=('green'),alpha=0.5)
 
-  distinctScaPaths = len(scaChart.collections[0].get_paths())
-  distinctAbsPaths = len(absChart.collections[0].get_paths())
-  if Bback is not None:
-    distinctBackPaths = len(backChart.collections[0].get_paths())
-  scaVertices = []
-  absVertices = []
-  if Bback is not None:
-    backVertices = []
-  for i in range(distinctScaPaths):
-    scaVertices.append(scaChart.collections[0].get_paths()[i].vertices)
-  for i in range(distinctAbsPaths):
-    absVertices.append(absChart.collections[0].get_paths()[i].vertices)
-  if Bback is not None:
-    for i in range(distinctBackPaths):
-      backVertices.append(backChart.collections[0].get_paths()[i].vertices)
-
-  scaVertices = np.concatenate(scaVertices)
-  absVertices = np.concatenate(absVertices)
-  if Bback is not None:
-    backVertices = np.concatenate(backVertices)
-
-  nSolution,kSolution = find_intersections(scaVertices,absVertices)
+  nSolution,kSolution = find_intersections(scaChart,absChart)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
   if Bback is not None:
-    oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
+    oneTrueN,oneTrueK = find_intersections(backChart,absChart)
     _these = [np.round(x+y*1j,3) for x,y in zip(oneTrueN,oneTrueK)]
     _match = list(set(np.round(trials,3)).intersection(np.round(_these,3)))
     if len(_match) > 0:
@@ -523,29 +482,23 @@ def ContourIntersection_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.0000
   return solutionSet,forwardCalculations,solutionErrors, fig, ax, graphElements
 
 def find_intersections(A,B):
-  arrayMinimum = lambda x1, x2: np.where(x1<x2, x1, x2)
-  arrayMaximum = lambda x1, x2: np.where(x1>x2, x1, x2)
-  arrayAll = lambda abools: np.dstack(abools).all(axis=2)
-  slope = lambda line: (lambda d: d[:,1]/d[:,0])(np.diff(line, axis=0))
-
-  x11, x21 = np.meshgrid(A[:-1, 0], B[:-1, 0])
-  x12, x22 = np.meshgrid(A[1:, 0], B[1:, 0])
-  y11, y21 = np.meshgrid(A[:-1, 1], B[:-1, 1])
-  y12, y22 = np.meshgrid(A[1:, 1], B[1:, 1])
-
-  m1, m2 = np.meshgrid(slope(A), slope(B))
-  # Here we use masked arrays to properly treat the rare case where a line segment is perfectly vertical
-  _m1 = np.ma.masked_array(m1,m1==-np.inf)
-  _m2 = np.ma.masked_array(m2,m2==-np.inf)
-  yi = (_m1*(x21-x11-y21/_m2)+y11)/(1-_m1/_m2)
-  xi = (yi-y21)/_m2+x21
-
-  xconds = (arrayMinimum(x11, x12) < xi, xi <= arrayMaximum(x11, x12),
-            arrayMinimum(x21, x22) < xi, xi <= arrayMaximum(x21, x22) )
-  yconds = (arrayMinimum(y11, y12) < yi, yi <= arrayMaximum(y11, y12),
-            arrayMinimum(y21, y22) < yi, yi <= arrayMaximum(y21, y22) )
-
-  return xi[arrayAll(xconds)], yi[arrayAll(yconds)]
+  X = []
+  Y = []
+  for p1 in A.collections[0].get_paths():
+    for p2 in B.collections[0].get_paths():
+      v1 = p1.vertices
+      v2 = p2.vertices
+
+      poly1 = geometry.LineString(v1)
+      poly2 = geometry.LineString(v2)
+
+      sol = poly1.intersection(poly2)
+
+      for s in sol:
+        X.append(s.x)
+        Y.append(s.y)
+
+  return X,Y
 
 def SurveyIteration(Qsca,Qabs,wavelength,diameter,tolerance=0.0005):
 #  http://pymiescatt.readthedocs.io/en/latest/inverse.html#IterativeInversion

build/lib/PyMieScatt/_version.py

@@ -1 +1 @@
-__version__ = "1.3.7"
+__version__ = "1.4.0"

docs/index.rst

@@ -21,7 +21,7 @@ Documentation is currently under development, but almost complete. A manuscript
 Install PyMieScatt
 ------------------
 
-The current version is 1.3.7. You can install PyMieScatt from `The Python Package Index (PyPI) <https://pypi.python.org/pypi/PyMieScatt>`_ with ::
+The current version is 1.4.0. You can install PyMieScatt from `The Python Package Index (PyPI) <https://pypi.python.org/pypi/PyMieScatt>`_ with ::
 
    $ pip install PyMieScatt
 
@@ -30,14 +30,18 @@ or from `GitHub <https://github.com/bsumlin/PyMieScatt>`_. Clone the repository
 
    $ python setup.py install
 
-Revision Notes - version 1.3.7
+Revision Notes - version 1.4.0
 ------------------------------
 
-- Fixed a major bug in :py:func:`ContourIntersection` and :py:func:`ContourIntersection_SD` that prevented them from using the actual input values to derive solutions.
+  - Added `Shapely <https://shapely.readthedocs.io/>`_ support! Shapely is a geometric manipulation ana analysis package. I wrote it in as a slightly faster, more robust way to look for intersections in n-k space when doing inversions. It also makes the code more readable and makes it clearer how the intersection method works.
 
 Revision History
 ----------------
 
+- 1.3.7
+
+  - Fixed a major bug in :py:func:`ContourIntersection` and :py:func:`ContourIntersection_SD` that prevented them from using the actual input values to derive solutions.
+
 - 1.3.6
 
   - Added new normalization options to :py:func:`ScatteringFunction` and :py:func:`SF_SD`. Docs for those functions have details.
@@ -74,9 +78,9 @@ Revision History
 Revisions in Progress
 ---------------------
 
-- Would like to re-write the inverse functions to take any two of scattering, absorption, or backscatter for the non-compact inverse problem. Still need all three for a fully-constrained inversion.
-- Would like to be able to pass array objects directly to all functions (within reason).
-- Would like to include auto-graphing capabilities for sacttering functions.
+- Would like to re-write the inversion functions to be as general as possible, i.e., if I pass scattering, absorption, particle size, and refractive index, it would solve for the wavelength.
+- Ablility to pass array objects directly to all functions (within reason).
+- Auto-graphing capabilities for sacttering functions.
 
 Documentation To-Do List
 ------------------------

setup.py

@@ -29,5 +29,5 @@
       packages=['PyMieScatt'],
       keywords=['Mie Rayleigh scattering absorption extinction light refraction'],
       classifiers = ['Development Status :: 5 - Production/Stable','Intended Audience :: Science/Research','Programming Language :: Python :: 3 :: Only','Topic :: Scientific/Engineering :: Physics'],
-      install_requires=['numpy','scipy','matplotlib'],
+      install_requires=['numpy','scipy','matplotlib','shapely'],
       zip_safe=False)