inches_per_pt = 3.4/246.0 # Convert pt to inches
golden_mean = (sqrt(5)-1.0)/2.0 # Aesthetic ratio
fig_width = 10 # width in inches
fig_height = 5 # height in inches
fig_size = [fig_width,fig_height]
params = {'backend': 'GTKAgg','axes.labelsize': 16,'font.size': 16,'legend.fontsize': 16'xtick.labelsize': 16,'ytick.labelsize': 16, 'text.usetex': Falls,'figure.figsize': fig_size}
rcParams.update(params)
#rapidly plot simulation over simulated gatesweep data
try:
delta = double(sys.argv[1])
l = double(sys.argv[2])
shift0 = double(sys.argv[3])
cutoff = int(sys.argv[4])
nrange = arange(double(sys.argv[5]),double(sys.argv[6]),double(sys.argv[7]))
e0 = M.convert(shift0,2)
B = double(sys.argv[8])
savefile = sys.argv[9]
except:
print 'Usage: ', sys.argv[0], ' delta lambda energy0 cutoff n-low n-high n-step n'
sys.exit(1)
width = 0.001
#----------------------------------------------------------------
FitDataPath='C:/Users/Owner/research/graphene/graphene_hf/results/2009_MagnetoPhonons_121/EXP20090309_121_raman-12_6T-Fit_DoubleLorentz_Intraband.txt'
FitData = loadtxt(FitDataPath)
mask1 = array([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,17,18,19,20,21,24,25,26,27,30,31,32,33,36,37,38,39,42,43,44,47,48,49,52,53,54,55,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79])
filepath = 'C:/Users/Owner/research/graphene/data/samples/b_field_samples/121_200902/'
transportpath = '20090309_121_raman/20090310_121_06h56.txt'
fig_width = 5 # width in inches
fig_height = 5 # height in inches
fig_size = [fig_width,fig_height]
params = {'backend': 'GTKAgg','axes.labelsize': 16,'font.size': 16,'legend.fontsize':16,'xtick.labelsize':16,'ytick.labelsize':16, 'text.usetex': False,'figure.figsize': fig_size}
rcParams.update(params)
#B-field sweeps for different n
#Set the parameters
delta = 0.03
l = 4.5e-3
shift0 = 1582.5
cutoff = 100
Brange = arange(2.4,4.0,0.01)#arange(1.0,5.5,0.02)#
e0 = M.convert(shift0,2)
n = 0.61e12
savefile = "C:/Users/Owner/research/publications/sr-papers/2013-ElectrostaticControlOfMagnetophononResonanceInGraphene/images/"
Brange = Brange**2
fig,ax1 = subplots()
ax2=ax1.twinx()
#----------------------------------------------------------------
SolPlus = []
SolMinus = []
for B in Brange:
x1 = M.FPlus(e0,n,l,e0,B,delta,cutoff)
x2 = M.FMinus(e0,n,l,e0,B,delta,cutoff)
