From 53e5508642e8f0136f16f67c17b4c10b59aa99b4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Marek=20Ne=C4=8Dada?= <marek@necada.org>
Date: Mon, 11 Sep 2017 03:05:49 +0300
Subject: [PATCH] Mathematica script for calculating the 2D Bessel transforms.

Former-commit-id: 6371433778d3b7ee2f0a286f2f3e2cbddc53c917
---
 besseltransforms/runit.sh | 11 +++++++++++
 besseltransforms/vzor.m   |  6 ++++++
 qpms/tmatrices.py         |  7 +++++--
 3 files changed, 22 insertions(+), 2 deletions(-)
 create mode 100755 besseltransforms/runit.sh
 create mode 100644 besseltransforms/vzor.m

diff --git a/besseltransforms/runit.sh b/besseltransforms/runit.sh
new file mode 100755
index 0000000..d277388
--- /dev/null
+++ b/besseltransforms/runit.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+K=$1
+Q=$2
+N=$3
+module load mathematica
+cat - vzor.m <<<"
+kk=$K;
+qq=$Q;
+nn=$N;
+" | math -noprompt > "${K}-${Q}-${N}"
+
diff --git a/besseltransforms/vzor.m b/besseltransforms/vzor.m
new file mode 100644
index 0000000..85ce73d
--- /dev/null
+++ b/besseltransforms/vzor.m
@@ -0,0 +1,6 @@
+$Assumptions = k >= 0 && k0 >= 0 && c >= 0 && n >= 0 ;
+Refine[Integrate[(1 - Exp[-c x])^\[Kappa] (k0 x)^(-q) Exp[
+    I k0 x] x BesselJ[n, k x] Exp[-c x], {x, 
+       0, \[Infinity]}], {\[Kappa] == kk, q == qq, n == nn}]
+Series[%, {k, \[Infinity], 10}]
+Quit[ ]
diff --git a/qpms/tmatrices.py b/qpms/tmatrices.py
index 9b765d7..7546595 100644
--- a/qpms/tmatrices.py
+++ b/qpms/tmatrices.py
@@ -152,7 +152,7 @@ def _scuffTMatrixConvert_EM_01(EM):
     else:
         return None
 
-def loadScuffTMatrices(fileName):
+def loadScuffTMatrices(fileName, normalisation = 1):
     """
     TODO doc
     """
@@ -182,7 +182,10 @@ def loadScuffTMatrices(fileName):
         for outc_type in [0,1]:
             TMatrices[:,1-outc_type,:,1-inc_type,:] = TMatrices_tmp_real[:,:,outc_type,:,inc_type]+1j*TMatrices_tmp_imag[:,:,outc_type,:,inc_type]
     # IMPORTANT: now we are going from Reid's/Kristensson's/Jackson's/whoseever convention to Taylor's convention
-    TMatrices[:,:,:,:,:] = TMatrices[:,:,:,:,:] * np.sqrt(ny*(ny+1))[ň,ň,ň,ň,:] / np.sqrt(ny*(ny+1))[ň,ň,:,ň,ň]
+    if normalisation == 1:
+        TMatrices[:,:,:,:,:] = TMatrices[:,:,:,:,:] * np.sqrt(ny*(ny+1))[ň,ň,ň,ň,:] / np.sqrt(ny*(ny+1))[ň,ň,:,ň,ň]
+    elif normalisation == 2: # Kristensson?
+        pass
     return (TMatrices, freqs, freqs_weirdunits, lMax)