# Sandia National Laboratories, Livermore, CA, USA #===================================================================================== import os import sys import numpy as np from scipy import stats import matplotlib import matplotlib.pylab as plt import plot_utils as ut method = sys.argv[1] # Read data file into numpy array odeData = ut.ReadDataFile("solution_" + method + ".dat") # Define stride to reduce data stride = 10 # extract x coordinates xCoords = odeData[::stride, 0] # font and linewidth parameters # lw is line width # fs is font size lw, fs = ut.SetPlotParams() elw = lw / 2 # error bar line width # create figure and axis fig = plt.figure(figsize=(6, 4))
# # Questions? Contact the UQTk Developers at <*****@*****.**> # Sandia National Laboratories, Livermore, CA, USA #===================================================================================== import os import sys import numpy as np from scipy import stats import matplotlib import matplotlib.pylab as plt import plot_utils as ut # Read data file into numpy array odeData = ut.ReadDataFile("solution_NISP_modes.dat") # Define stride to reduce data stride = 1 # extract x coordinates xCoords = odeData[::stride,0] # font and linewidth parameters # lw is line width # fs is font size lw,fs = ut.SetPlotParams() # create figure and axis fig = plt.figure(figsize=(6,4))
#!/usr/bin/env python import os import sys import numpy as np from scipy import stats import matplotlib import matplotlib.pylab as plt import plot_utils as ut # Read data file into numpy array odeData = ut.ReadDataFile("solutionISP.dat") # Define stride to reduce data stride = 1000 # extract x coordinates xCoords = odeData[::stride, 0] # font and linewidth parameters # lw is line width # fs is font size lw, fs = ut.SetPlotParams() # create figure and axis fig = plt.figure(figsize=(6, 4)) ax = fig.add_axes([0.15, 0.15, 0.75, 0.75]) # set axis limits
# # Questions? Contact the UQTk Developers at <*****@*****.**> # Sandia National Laboratories, Livermore, CA, USA #===================================================================================== import os import sys import numpy as np from scipy import stats import matplotlib import matplotlib.pylab as plt import plot_utils as ut # Read data file into numpy array odeDataISP = ut.ReadDataFile("solution_ISP.dat") odeDataNISP = ut.ReadDataFile("solution_NISP.dat") # Define stride to reduce data stride = 10 # extract x coordinates xCoordsISP = odeDataISP[::stride, 0] xCoordsNISP = odeDataNISP[::stride, 0] # font and linewidth parameters # lw is line width # fs is font size lw, fs = ut.SetPlotParams()