minor

docs, changed some variable names

PyMieScatt/Inverse.py

@@ -72,36 +72,36 @@ def Inversion_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0,kMax=1,scatter
 
   return np.intersect1d(validScattering,validAbsorption)
 
-def ContourIntersection(QscaMeasured,QabsMeasured,wavelength,diameter,nMin=1,nMax=3,kMin=0.00001,kMax=1,QbackMeasured=None,gridPoints=100,interpolationFactor=2,maxError=0.005,fig=None,ax=None,axisOption=0):
+def ContourIntersection(Qsca,Qabs,wavelength,diameter,nMin=1,nMax=3,kMin=0.00001,kMax=1,Qback=None,gridPoints=100,interpolationFactor=2,maxError=0.005,fig=None,ax=None,axisOption=0):
 #  http://pymiescatt.readthedocs.io/en/latest/inverse.html#ContourIntersection
   error = lambda measured,calculated: np.abs((calculated-measured)/measured)
-  if QbackMeasured is not None:
+  if Qback is not None:
     if gridPoints*interpolationFactor<400:
       gridPoints = 2*gridPoints
   labels = []
   incErrors = False
-  if type(QscaMeasured) in [list, tuple, np.ndarray]:
+  if type(Qsca) in [list, tuple, np.ndarray]:
     incErrors = True
-    scaError = QscaMeasured[1]
-    QscaMeasured = QscaMeasured[0]
-    labels.append("Qsca = {b:1.3f}±{e:1.3f}".format(b=QscaMeasured,e=scaError))
+    scaError = Qsca[1]
+    Qsca = Qsca[0]
+    labels.append("Qsca = {b:1.3f}±{e:1.3f}".format(b=Qsca,e=scaError))
   else:
     scaError = None
-    labels.append("Qsca = {b:1.3f}".format(b=QscaMeasured))
-  if type(QabsMeasured) in [list, tuple, np.ndarray]:
-    absError = QabsMeasured[1]
-    QabsMeasured = QabsMeasured[0]
-    labels.append("Qabs = {b:1.3f}±{e:1.3f}".format(b=QabsMeasured,e=absError))
+    labels.append("Qsca = {b:1.3f}".format(b=Qsca))
+  if type(Qabs) in [list, tuple, np.ndarray]:
+    absError = Qabs[1]
+    Qabs = Qabs[0]
+    labels.append("Qabs = {b:1.3f}±{e:1.3f}".format(b=Qabs,e=absError))
   else:
     absError = None
-    labels.append("Qabs = {b:1.3f}".format(b=QabsMeasured))
-  if type(QbackMeasured) in [list, tuple, np.ndarray]:
-    backError = QbackMeasured[1]
-    QbackMeasured = QbackMeasured[0]
-    labels.append("Qback = {b:1.3f}±{e:1.3f}".format(b=QbackMeasured,e=backError))
-  elif QbackMeasured is not None:
+    labels.append("Qabs = {b:1.3f}".format(b=Qabs))
+  if type(Qback) in [list, tuple, np.ndarray]:
+    backError = Qback[1]
+    Qback = Qback[0]
+    labels.append("Qback = {b:1.3f}±{e:1.3f}".format(b=Qback,e=backError))
+  elif Qback is not None:
     backError = None
-    labels.append("Qback - {b:1.3f}".format(b=QbackMeasured))
+    labels.append("Qback - {b:1.3f}".format(b=Qback))
   else:
     backError = None
 
@@ -133,58 +133,58 @@ def ContourIntersection(QscaMeasured,QabsMeasured,wavelength,diameter,nMin=1,nMa
   elif ax is None:
     ax = fig.gca()
 
-  scaLevels = np.array([QscaMeasured])
-  absLevels = np.array([QabsMeasured])
+  scaLevels = np.array([Qsca])
+  absLevels = np.array([Qabs])
 
-  if QbackMeasured is not None:
-    backLevels = np.array([QbackMeasured])
+  if Qback is not None:
+    backLevels = np.array([Qback])
     if backError is not None:
-      backErrorLevels = np.array([QbackMeasured+x for x in [-backError,backError]])
+      backErrorLevels = np.array([Qback+x for x in [-backError,backError]])
 
   scaChart = ax.contour(n,k,QscaList,scaLevels,origin='lower',linestyles='dashdot',linewidths=1.5,colors=('red'))
   absChart = ax.contour(n,k,QabsList,absLevels,origin='lower',linewidths=1.5,colors=('blue'))
-  if QbackMeasured is not None:
+  if Qback is not None:
     backChart = ax.contour(n,k,QbackList,backLevels,origin='lower',linestyles='dotted',linewidths=1.5,colors=('green'))
 
   if scaError is not None:
-    scaErrorLevels = np.array([QscaMeasured+x for x in [-scaError, scaError]])
+    scaErrorLevels = np.array([Qsca+x for x in [-scaError, scaError]])
     ax.contourf(n,k,QscaList,scaErrorLevels,origin='lower',colors=('red'),alpha=0.15)
     ax.contour(n,k,QscaList,scaErrorLevels,origin='lower',linewidths=0.5,colors=('red'),alpha=0.5)
 
   if absError is not None:
-    absErrorLevels = np.array([QabsMeasured+x for x in [-absError, absError]])
+    absErrorLevels = np.array([Qabs+x for x in [-absError, absError]])
     ax.contourf(n,k,QabsList,absErrorLevels,origin='lower',colors=('blue'),alpha=0.15)
     ax.contour(n,k,QabsList,absErrorLevels,origin='lower',linewidths=0.5,colors=('blue'),alpha=0.5)
 
   if backError is not None:
-    backErrorLevels = np.array([QbackMeasured+x for x in [-backError, backError]])
+    backErrorLevels = np.array([Qback+x for x in [-backError, backError]])
     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 QbackMeasured is not None:
+  if Qback is not None:
     distinctBackPaths = len(backChart.collections[0].get_paths())
   scaVertices = []
   absVertices = []
-  if QbackMeasured is not None:
+  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 QbackMeasured is not None:
+  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 QbackMeasured is not None:
+  if Qback is not None:
     backVertices = np.concatenate(backVertices)
 
   nSolution,kSolution = find_intersections(scaVertices,absVertices)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
-  if QbackMeasured is not None:
+  if Qback is not None:
     oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
     _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)))
@@ -204,7 +204,7 @@ def ContourIntersection(QscaMeasured,QabsMeasured,wavelength,diameter,nMin=1,nMa
     forwardCalculations.append([_s,_a])
   solutionErrors = []
   for f in forwardCalculations:
-    solutionErrors.append([error(f[0],QscaMeasured),error(f[1],QabsMeasured)])
+    solutionErrors.append([error(f[0],Qsca),error(f[1],Qabs)])
 
   solutionSet = np.array(solutionSet)
   forwardCalculations = np.array(forwardCalculations)
@@ -256,7 +256,7 @@ def ContourIntersection(QscaMeasured,QabsMeasured,wavelength,diameter,nMin=1,nMa
     pass
 
   _c = ax.get_children()
-  if QbackMeasured is None:
+  if Qback is None:
     if incErrors:
       # no Qback, with error bounds
       graphElements = {'Qsca':_c[0],'Qabs':_c[1], # contours
@@ -294,36 +294,36 @@ def ContourIntersection(QscaMeasured,QabsMeasured,wavelength,diameter,nMin=1,nMa
 
   return solutionSet,forwardCalculations,solutionErrors, fig, ax, graphElements
 
-def ContourIntersection_SD(BscaMeasured,BabsMeasured,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.00001,kMax=1,BbackMeasured=None,gridPoints=60,interpolationFactor=2,maxError=0.005,fig=None,ax=None,axisOption=0):
+def ContourIntersection_SD(Bsca,Babs,wavelength,dp,ndp,nMin=1,nMax=3,kMin=0.00001,kMax=1,Bback=None,gridPoints=60,interpolationFactor=2,maxError=0.005,fig=None,ax=None,axisOption=0):
 #  http://pymiescatt.readthedocs.io/en/latest/inverse.html#ContourIntersection_SD
   error = lambda measured,calculated: np.abs((calculated-measured)/measured)
-  if BbackMeasured is not None:
+  if Bback is not None:
     if gridPoints*interpolationFactor<120:
       gridPoints = 2*gridPoints
   labels = []
   incErrors = False
-  if type(BscaMeasured) in [list, tuple, np.ndarray]:
+  if type(Bsca) in [list, tuple, np.ndarray]:
     incErrors = True
-    scaError = BscaMeasured[1]
-    BscaMeasured = BscaMeasured[0]
-    labels.append("Bsca = {b:1.1f}±{e:1.1f}".format(b=BscaMeasured,e=scaError))
+    scaError = Bsca[1]
+    Bsca = Bsca[0]
+    labels.append("Bsca = {b:1.1f}±{e:1.1f}".format(b=Bsca,e=scaError))
   else:
     scaError = None
-    labels.append("Bsca = {b:1.1f}".format(b=BscaMeasured))
-  if type(BabsMeasured) in [list, tuple, np.ndarray]:
-    absError = BabsMeasured[1]
-    BabsMeasured = BabsMeasured[0]
-    labels.append("Babs = {b:1.1f}±{e:1.1f}".format(b=BabsMeasured,e=absError))
+    labels.append("Bsca = {b:1.1f}".format(b=Bsca))
+  if type(Babs) in [list, tuple, np.ndarray]:
+    absError = Babs[1]
+    Babs = Babs[0]
+    labels.append("Babs = {b:1.1f}±{e:1.1f}".format(b=Babs,e=absError))
   else:
     absError = None
-    labels.append("Babs = {b:1.1f}".format(b=BabsMeasured))
-  if type(BbackMeasured) in [list, tuple, np.ndarray]:
-    backError = BbackMeasured[1]
-    BbackMeasured = BbackMeasured[0]
-    labels.append("Bback = {b:1.1f}±{e:1.1f}".format(b=BbackMeasured,e=backError))
-  elif BbackMeasured is not None:
+    labels.append("Babs = {b:1.1f}".format(b=Babs))
+  if type(Bback) in [list, tuple, np.ndarray]:
+    backError = Bback[1]
+    Bback = Bback[0]
+    labels.append("Bback = {b:1.1f}±{e:1.1f}".format(b=Bback,e=backError))
+  elif Bback is not None:
     backError = None
-    labels.append("Bback - {b:1.1f}".format(b=BbackMeasured))
+    labels.append("Bback - {b:1.1f}".format(b=Bback))
   else:
     backError = None
 
@@ -357,58 +357,58 @@ def ContourIntersection_SD(BscaMeasured,BabsMeasured,wavelength,dp,ndp,nMin=1,nM
   elif ax is None:
     ax = fig.gca()
 
-  scaLevels = np.array([BscaMeasured])
-  absLevels = np.array([BabsMeasured])
+  scaLevels = np.array([Bsca])
+  absLevels = np.array([Babs])
 
-  if BbackMeasured is not None:
-    backLevels = np.array([BbackMeasured])
+  if Bback is not None:
+    backLevels = np.array([Bback])
     if backError is not None:
-      backErrorLevels = np.array([BbackMeasured+x for x in [-backError,backError]])
+      backErrorLevels = np.array([Bback+x for x in [-backError,backError]])
 
   scaChart = ax.contour(n,k,BscaList,scaLevels,origin='lower',linestyles='dashdot',linewidths=1.5,colors=('red'))
   absChart = ax.contour(n,k,BabsList,absLevels,origin='lower',linewidths=1.5,colors=('blue'))
-  if BbackMeasured is not None:
+  if Bback is not None:
     backChart = ax.contour(n,k,BbackList,backLevels,origin='lower',linestyles='dotted',linewidths=1.5,colors=('green'))
 
   if scaError is not None:
-    scaErrorLevels = np.array([BscaMeasured+x for x in [-scaError, scaError]])
+    scaErrorLevels = np.array([Bsca+x for x in [-scaError, scaError]])
     ax.contourf(n,k,BscaList,scaErrorLevels,origin='lower',colors=('red'),alpha=0.15)
     ax.contour(n,k,BscaList,scaErrorLevels,origin='lower',linewidths=0.5,colors=('red'),alpha=0.5)
 
   if absError is not None:
-    absErrorLevels = np.array([BabsMeasured+x for x in [-absError, absError]])
+    absErrorLevels = np.array([Babs+x for x in [-absError, absError]])
     ax.contourf(n,k,BabsList,absErrorLevels,origin='lower',colors=('blue'),alpha=0.15)
     ax.contour(n,k,BabsList,absErrorLevels,origin='lower',linewidths=0.5,colors=('blue'),alpha=0.5)
 
   if backError is not None:
-    backErrorLevels = np.array([BbackMeasured+x for x in [-backError, backError]])
+    backErrorLevels = np.array([Bback+x for x in [-backError, backError]])
     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 BbackMeasured is not None:
+  if Bback is not None:
     distinctBackPaths = len(backChart.collections[0].get_paths())
   scaVertices = []
   absVertices = []
-  if BbackMeasured is not None:
+  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 BbackMeasured is not None:
+  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 BbackMeasured is not None:
+  if Bback is not None:
     backVertices = np.concatenate(backVertices)
 
   nSolution,kSolution = find_intersections(scaVertices,absVertices)
   trials = [(x+y*1j) for x,y in zip(nSolution,kSolution)]
-  if BbackMeasured is not None:
+  if Bback is not None:
     oneTrueN,oneTrueK = find_intersections(backVertices,absVertices)
     _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)))
@@ -428,7 +428,7 @@ def ContourIntersection_SD(BscaMeasured,BabsMeasured,wavelength,dp,ndp,nMin=1,nM
     forwardCalculations.append([_s,_a])
   solutionErrors = []
   for f in forwardCalculations:
-    solutionErrors.append([error(f[0],BscaMeasured),error(f[1],BabsMeasured)])
+    solutionErrors.append([error(f[0],Bsca),error(f[1],Babs)])
 
   solutionSet = np.array(solutionSet)
   forwardCalculations = np.array(forwardCalculations)
@@ -480,7 +480,7 @@ def ContourIntersection_SD(BscaMeasured,BabsMeasured,wavelength,dp,ndp,nMin=1,nM
     pass
 
   _c = ax.get_children()
-  if BbackMeasured is None:
+  if Bback is None:
     if incErrors:
       # no Bback, with error bounds
       graphElements = {'Bsca':_c[0],'Babs':_c[1], # contours

docs/index.rst

@@ -7,9 +7,9 @@
 Online user's guide for the Python Mie Scattering package (PyMieScatt)
 ======================================================================
 
-Welcome AAAR 2017 Attendees! You can find Ben at posters 2CA.18, 2CA.21 (Tuesday) and 8IM.44 (Thursday). I'm happy to answer any questions.
+Welcome AAAR 2017 Attendees! You can find Ben at posters 2CA.18, 2CA.21 (Tuesday) and 8IM.44 (Thursday). I'm happy to answer any questions, and you can always `e-mail me <http://pymiescatt.readthedocs.io/en/latest/#author-contact-information>`_.
 
-Documentation is currently under development. This documentation includes a brief discussion of Mie theory and the development of the functions included in the package. A manuscript communicating the development and use of this package was submitted to the `Journal of Quantative Spectroscopy and Radiative Transfer <http://www.sciencedirect.com/science/journal/00224073>`_. It has been accepted and is currently being proofed for publication. The preprint is `available online now <https://doi.org/10.1016/j.jqsrt.2017.10.012>`_.
+Documentation is currently under development. This documentation includes a brief discussion of Mie theory and the development of the functions included in the package. A manuscript communicating the development and use of this package was submitted to the `Journal of Quantative Spectroscopy and Radiative Transfer <http://www.sciencedirect.com/science/journal/00224073>`_. It has been accepted and is currently being proofed for publication. The JQSRT preprint is `available now <https://doi.org/10.1016/j.jqsrt.2017.10.012>`_.
 
 
 Install PyMieScatt
@@ -21,9 +21,10 @@ You can install PyMieScatt from `The Python Package Index (PyPI) <https://pypi.p
 
 
 or from `GitHub <https://github.com/bsumlin/PyMieScatt>`_. Clone the repository and then run ::
+
    $ python setup.py install
    
-The current version is 1.3.1.
+The current version is 1.3.2.
 
 
 .. toctree::
@@ -38,10 +39,16 @@ The current version is 1.3.1.
 
 
 
-Revision Notes - version 1.3.1
+Revision Notes - version 1.3.2
 ------------------------------
 
-- Optimizations to the resolution of the survey-intersection inversion method
+- Renamed GraphicalInversion() and GraphicalInversion_SD() to ContourIntersection() and ContourIntersection_SD(), respectively.
+
+Revision History
+----------------
+
+- 1.3.1
+  - Optimizations to the resolution of the survey-intersection inversion method
 
 Revisions in Progress
 ---------------------
@@ -65,6 +72,8 @@ Publications Using PyMieScatt
 
 - Sumlin BJ, Pandey A, Walker MJ, Pattison RS, Williams BJ, Chakrabarty RK. Atmospheric Photooxidation Diminishes Light Absorption by Primary Brown Carbon Aerosol from Biomass Burning. Environ Sci Tech Let. 2017. DOI: `10.1021/acs.estlett.7b00393 <http://doi.org/10.1021/acs.estlett.7b00393>`_
 
+- Sumlin BJ, Heinson WR, Chakrabarty RK. Retrieving the Aerosol Complex Refractive Index using PyMieScatt: A Mie Computational Package with Visualization Capabilities. J. Quant. Spectros. Rad. Trans. 2017. DOI: `10.1016/j.jqsrt.2017.10.012 <https://doi.org/10.1016/j.jqsrt.2017.10.012>`_
+
 Author Contact Information
 --------------------------
 PyMieScatt was written by `Benjamin Sumlin <https://air.eece.wustl.edu/people/ben-sumlin/>`_. Special thanks to Dr. William Heinson, Dr. Rajan Chakrabarty, Claire Fortenberry, and Apoorva Pandey for their insights and support.