From 7c7def13662ec846f4454fee6e72098f19951975 Mon Sep 17 00:00:00 2001
From: "Veronica K. B. Olsen" <1619840+vkbo@users.noreply.github.com>
Date: Tue, 12 Nov 2019 16:38:10 +0100
Subject: [PATCH] Clanup and spell checking

---
 buildFucntions.py => buildFunctions.py |  0
 nightlyBuildSixTrack.py                |  2 +-
 randtest.py                            | 39 --------------------------
 3 files changed, 1 insertion(+), 40 deletions(-)
 rename buildFucntions.py => buildFunctions.py (100%)
 delete mode 100755 randtest.py

diff --git a/buildFucntions.py b/buildFunctions.py
similarity index 100%
rename from buildFucntions.py
rename to buildFunctions.py
diff --git a/nightlyBuildSixTrack.py b/nightlyBuildSixTrack.py
index 0a2b308..e3df6d6 100755
--- a/nightlyBuildSixTrack.py
+++ b/nightlyBuildSixTrack.py
@@ -19,7 +19,7 @@
 import logging
 from os import path, chdir, mkdir, listdir, system
 from datetime import datetime
-from buildFucntions import *
+from buildFunctions import *
 
 logger = logging.getLogger("SixTrackTestBuild")
 
diff --git a/randtest.py b/randtest.py
deleted file mode 100755
index 9b9d000..0000000
--- a/randtest.py
+++ /dev/null
@@ -1,39 +0,0 @@
-#!/usr/bin/env python3
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-nPart = 1000000
-
-nRnd = np.random.uniform(0.0, 1.0, nPart)
-pDist = np.zeros(nPart)
-
-cMax = 2.0
-cMin = 0.0
-
-# CCC = ONEONE -EXP( -(CMAX+CMIN)*(CMAX-CMIN)/TWOTWO )
-# BOXMUL = SQRT( CMIN**2 -TWOTWO*LOG( ONEONE-CCC*RAND() ) )
-
-cFac = 1.0 - np.exp(-(cMax+cMin)*(cMax-cMin)/2.0)
-# for i in range(nPart):
-#   pDist[i] = np.sqrt(cMin**2 - 2.0*np.log(1.0-cFac*nRnd[i]))
-
-# CCC = ONEONE -EXP( -CMAX**2/TWOTWO )
-# BOXMUL = SQRT( -TWOTWO*LOG( ONEONE-CCC*RAND() ) )
-cFac = 1.0 - np.exp(-cMax**2/2.0)
-for i in range(int(nPart/2)):
-  rad = np.sqrt(-2.0*np.log(1.0-cFac*nRnd[2*i]))
-  # rad = np.sqrt(cMin**2 - 2.0*np.log(1.0-cFac*nRnd[2*i]))
-  # rad = np.sqrt(1.0-2.0*np.log(nRnd[2*i]))
-  pDist[2*i]   = rad*np.cos(2.0*np.pi*nRnd[2*i+1])
-  pDist[2*i+1] = rad*np.sin(2.0*np.pi*nRnd[2*i+1])
-
-# Plot
-figOne = plt.figure(1,figsize=(10, 8),dpi=100)
-figOne.clf()
-
-pHist, pG = np.histogram(pDist, bins=200, density=True)
-pC = (pG[:-1] + pG[1:])/2
-plt.step(pC,pHist,where="mid")
-
-plt.show(block=True)