def plotMeanSquaredDisplacement(particles,
t,
N,
eps,
chartName,
plotDiffusionConstant=False,
filename="meanSquaredDisplamcent"):
msd, diffusion_constant = MDFunctions.ComputeMeanSquaredDisplacement(
t, particles)
msd, yLabel = MDFunctions.SigmaToAngstrom(msd)
t, xLabel = MDFunctions.ArgonTimeToSeconds(t)
plt.title(chartName)
plt.plot(t, msd, label=f'Mean squared displacement')
plt.xlabel(xLabel)
plt.ylabel(f"Mean sq. disp {yLabel}")
plt.legend()
plt.savefig(f'./fig/{filename}.jpg')
plt.show()
if plotDiffusionConstant:
plt.title("Diffusion constant")
plt.plot(t, diffusion_constant, label=f'Diffusion constant')
plt.xlabel(xLabel)
plt.ylabel('D')
plt.legend()
plt.savefig(f'{filename}_diffusionConstant.jpg')
plt.show()
def plotVelocityAutoCorrelation(particles,
t,
N,
chartName,
includeDiffusionCoefficientSubPlot=False,
filename="velocityAutoCorrelation"):
vac, diffusion_coefficcient = MDFunctions.ComputeVelocityAutoCorrelation(
t, particles)
t, timeUnits = MDFunctions.ArgonTimeToSeconds(t)
plt.subplot(1, 1, 1)
plt.title(f"{chartName} Velocity correlation")
plt.plot(t, vac, label=f'Velocity auto correlation')
plt.xlabel(f"time ({timeUnits})")
plt.ylabel('Vel. Autocorrelation')
plt.legend()
plt.savefig(f'{filename}_velcorr.jpg')
plt.show()
if includeDiffusionCoefficientSubPlot:
plt.subplot(2, 1, 1)
plt.title(f"{chartName} Diffusion Coefficient")
plt.plot(t, diffusion_coefficcient, label=f'Diffusion coefficient')
plt.xlabel('time(s)')
plt.ylabel('Diffusion coefficient')
plt.legend()
plt.savefig(f'{filename}_diffcoeff.jpg')
plt.show()
def plotTemperature(particles, t, N, chartName, filename="plotTemperature"):
tPrime = MDFunctions.ComputeTemperatureReduced(N, particles)
tKelvin = MDFunctions.ArgonTPrimeToKelvin(tPrime)
tToSeconds, xLabel = MDFunctions.ArgonTimeToSeconds(t)
plt.title(chartName)
plt.plot(tToSeconds, tKelvin, label=f'Temperature (K)')
plt.xlabel(xLabel)
plt.ylabel('Kelvin (K)')
plt.legend()
plt.savefig(f'./fig/{filename}.jpg')
plt.show()
def Task4_di_read(t, filename):
num_bins = 10
bin_edges = np.linspace(0, 5, num_bins + 1)
bin_centres = 0.5 * (bin_edges[1:] + bin_edges[:-1])
V = constants.box**3
#Read the file prepared by the previous
particles, maxTindex = MDFileWriter.ReadEverything(filename, N)
#Convert x-axis units from sigma to Ångstrøm
bin_centres = MDFunctions.SigmaToAngstrom(bin_centres)
if t is None:
t = maxTindex
elif t > maxTindex:
raise Exception(
"Trying to read out rdf from frame {t} which only simulated {maxTindex} frames"
)
tInSeconds = MDFunctions.ArgonTimeToSeconds(t)
count = len(particles)
x = np.array([[0., 0., 0.] for i in range(count)]) # Velocity
j = 0
counter = 0
for j in range(0, count):
x[counter] = particles[j].x[t]
counter += 1
#x = np.where(x > 0)
#Bin the distance counts
data = MDFunctions.rdf(bin_edges, x, V)
chartName = f"Ar N={count} RDF after {tInSeconds[0]:11.6} {tInSeconds[1]}"
# def barchart(data, xlabels, chartName, filename = "barChart"):
MDPlot.barchart(data, bin_centres, "RDF", chartName, f"RDF_{filename}")
strLabels = []
for lb in bin_centres[0]:
strLabels.append(f"{lb:11.1f}")
