"""
import scipy.io as spio
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rc('font',family='Times New Roman')
matplotlib.rc('xtick', labelsize=18)
matplotlib.rc('ytick', labelsize=18)
import sys
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
dataopal = mplt.load('46grid1mill.stat')
#dataopal = mplt.load('1nCR0pt75LaserAstraM273.stat', 57)
datagpt = mplt.loadgpt('OUTAnlysGun2.mat')
astrax = np.loadtxt('awa_gunSCon.Xemit.001', skiprows=0)
astray = np.loadtxt('awa_gunSCon.Yemit.001', skiprows=0)
astraz = np.loadtxt('awa_gunSCon.Zemit.001', skiprows=0)
# Four axes, returned as a 2-d array
f, axarr = plt.subplots(2, 2, figsize=(7.5,6))
f.subplots_adjust(hspace=.6)
f.subplots_adjust(wspace=.4)
#==============================================================================
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import sys
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
#matplotlib.rc('font',family='Times New Roman')
matplotlib.rc('xtick', labelsize=18)
matplotlib.rc('ytick', labelsize=18)
dataopal1 = mplt.load('1nCR0pt75LaserAstraM273.stat')
fig, ax1 = plt.subplots()
ax1.plot(dataopal1['z'], dataopal1['Ez'], 'k-', label='Electric field, Ez')
ax1.set_xlabel('Z [m]', size=18)
ax1.axis([0.0, 0.5, -60, 5.0])
# Make the y-axis label, ticks and tick labels match the line color.
ax1.set_ylabel('Electric Field [MV/m]', color='k', size=18)
ax1.tick_params('y', colors='k')
ax2 = ax1.twinx()
ax2.plot(dataopal1['z'], dataopal1['Bz'], 'b--', label='Magnetic field, Bz')
ax2.set_ylabel('Magnetic Field [T]', color='b', size=18)
ax2.tick_params('y', colors='b')
ax2.axis([0.0, 0.5, -0.4, 0.05])
lines, labels = ax1.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc='lower right')
#import matplotlib.pyplot as plt
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
#Making a list of SDDS files
files = glob.glob(
'C:/Users/nneveu/Desktop/Scripts/benchmark/gridcompare/*3D*.stat')
emittanceMin = 1000000
filemin = '.'
#Looping through every .stat file
for filename in files:
#filename = 'optLinac.stat'
#print filename.split('.')[0]
data = mplt.load(filename)
zloc = np.argmax(data['z'] > 0.3)
#zloc = np.where(data['z']>0.3)[0][0]
tempmin = np.min(data['xemit'][zloc:])
print(filename)
print(tempmin)
#print tempmin
if tempmin < emittanceMin:
emittanceMin = tempmin
filemin = filename
#print data['z'][np.where(data['xemit']==emittanceMin)[0]]
#print emittanceMin
#print filemin.split('\\')[1]
@author: nneveu
"""
import scipy.io as spio
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rc('font', family='Times New Roman')
matplotlib.rc('xtick', labelsize=18)
matplotlib.rc('ytick', labelsize=18)
import sys
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
dataopal = mplt.load('46grid1mill.stat')
#dataopal2 = mplt.load('RFphotoinjector.stat', 57)
dataopal2 = mplt.load('optgun_273_0_0.00075.stat')
datagpt = mplt.loadgpt('OUTAnlysGun2.mat')
#==============================================================================
# astrax = np.loadtxt('awa_gunSCon.Xemit.001', skiprows=0)
# astray = np.loadtxt('awa_gunSCon.Yemit.001', skiprows=0)
# astraz = np.loadtxt('awa_gunSCon.Zemit.001', skiprows=0)
#
#
#
# # Four axes, returned as a 2-d array
# f, axarr = plt.subplots(2, 2, figsize=(7.5,6))
# f.subplots_adjust(hspace=.6)
# f.subplots_adjust(wspace=.4)
@author: nneveu
"""
import scipy.io as spio
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
#matplotlib.rc('font',family='Times New Roman')
matplotlib.rc('xtick', labelsize=18)
matplotlib.rc('ytick', labelsize=18)
import sys
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
dataopal1 = mplt.load('tba_guass1.stat')
dataopal2 = mplt.load('tba_guass.stat')
v1 = 'tba 1' #str(1.4)
v2 = 'tba 2' #str(1.9)
# Four axes, returned as a 2-d array
f, axarr = plt.subplots(2, 2, figsize=(7.5, 6))
f.subplots_adjust(hspace=.6)
f.subplots_adjust(wspace=.4)
#==============================================================================
# axarr[0, 0].plot(astrax[:,0], astrax[:,3], 'g-', label = 'ASTRA', markevery=5) #xrms
# axarr[0, 0].plot(datagpt['z'], datagpt['xrms']*10.0**3.0, 'k-o', label = 'GPT', markevery = 5, markersize =3)
# axarr[0, 0].plot(dataopal['z'], dataopal['xrms'], '--', label = 'OPAL')
# axarr[0, 0].set_title('Transverse Beam Size',fontsize=18)
x and y max, min trajectories
"""
import numpy as np
import matplotlib.pyplot as plt
import sys
import h5py
sys.path.append('/Users/nneveu/Documents/PythonScripts')
import myplots as mplt
run = 'zoomedin'
myfile = 'dipoleKicker20m.h5'
angledata = mplt.load('dipoleKicker20m.stat', 56)
hf = h5py.File(myfile, 'r')
steps = len(hf.keys()) - 1
#steps = 120
xmin = np.zeros((steps, 1))
xmax = np.zeros((steps, 1))
ymin = np.zeros((steps, 1))
ymax = np.zeros((steps, 1))
avez = np.zeros((steps, 1))
for i in np.arange(0, steps):
x = np.asarray(hf.get('/Step#' + str(i) + '/x')) * 10.0**3.0
#px = np.asarray(hf.get('/Step#'+str(steps-1)+'/px' ))*0.511
#py = np.asarray(hf.get('/Step#'+str(steps-1)+'/py' ))*0.511
times = np.loadtxt('timings.txt', skiprows=1)
tstep = times[:, 0]
seconds = times[:, 1]
plt.title('Timing results')
plt.xlabel('time step [s]')
plt.ylabel('simulation time [s]')
plt.plot(tstep, seconds, '*--')
plt.savefig('./time_vs_timestep.pdf',
format='pdf',
dpi=1000,
bbox_inches='tight')
#data1 = mplt.load('5e-10.stat')
#data2 = mplt.load('1e-10.stat')
data3 = mplt.load('5e-11.stat')
#data4 = mplt.load('1e-11.stat')
#data5 = mplt.load('5e-12.stat')
#data6 = mplt.load('1e-12.stat')
datah = mplt.load('1e5_np.stat')
datan = mplt.load('optLinac_40nC.stat')
#data = [data1, data2, data3, data4, data5, data6, datan]
#v = [str(5e-10), str(1e-10), str(5e-11), str(1e-11), str(5e-12), str(1e-12), 'multi-steps np=1e5']
data = [data3, datan, datah]
v = ['low fidelity', 'low fidelity adjusted dT', 'mid fidelity']
markers = ['b--', 'k-', 'y--', 'r-', 'k--', 'm-', '--']
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from glob import glob
from natsort import natsorted, ns
import sys
sys.path.append('/home/nicole/Documents/thesis_code')
import myplots as mplt
matplotlib.rc('xtick', labelsize=18)
matplotlib.rc('ytick', labelsize=18)
opal1 = mplt.load('optLinac_M185_GPhase-20_R8.5mm_FWHM1.5e-12_L1-L6_0_3D.stat') #_3D.stat')
opal2 = mplt.load('optLinac_M250_GPhase-20_R8.5mm_FWHM1.5e-12_L1-L6_0_3D.stat') #_3D.stat')
beamfiles = glob('./output/1nC/*beamsizes_1nC.npy')
n_points = len(beamfiles)
#https://stackoverflow.com/questions/4836710/does-python-have-a-built-in-function-for-string-natural-sort
natsorted(beamfiles, key=lambda y: y.lower())
#natsorted(beamfiles, alg=ns.IGNORECASE)
ave_sigx = {} #np.zeros((n_points))
ave_sigy = {} #np.zeros((n_points))
max_barx = {} #np.zeros((n_points))
max_bary = {} #np.zeros((n_points))
error_barsx = {} #np.zeros((n_points))
error_barsy = {} #np.zeros((n_points))
std_sigx = {}
@author: nneveu
"""
import numpy as np
import matplotlib.pyplot as plt
import sys
import myplots as mplt
run = 'dipole_test'
#opalfilebase = 'dipoleKickerBaselineK0-0pt012'
#file1 = mplt.load('optLinac_weight3.stat')
#file1 = mplt.load('optLinac_weight5_linacon.stat')
#file2 = mplt.load('optLinac_weight5_linacon.stat')
file1 = mplt.load('./data/optLinac3Dgun3DLinac.stat')
file2 = mplt.load('./data/optLinac3Dgun3DLinac.stat')
file1_label = 'weight 3'#'Linac on'#
file2_label = 'weight 5'#'weight 5'
for i in np.arange(6, 8, 1):
if i ==1:
#Energy Plot
plt.figure(1)
#plt.show(block=False)
#plt.axis((0, 20, 0, 70))
plt.title( r'Energy Vs. Z' , size=18)
plt.xlabel(r'z [m]', size=18)
