"stdu" : r"$\sigma_u/U_\infty$",

"meanv" : r"$V/U_\infty$",

"meanw" : r"$W/U_\infty$",

"""Loads wake data and returns y/R and statistics."""

folder = os.listdir("postProcessing/sets")[0]

flist = os.listdir("postProcessing/sets/"+folder)

flist.remove("streamwise_U.xy")

data = {}

for fname in flist:

fpath = "postProcessing/sets/"+folder+"/"+fname

z_H = float(fname.split("_")[1])

data_s = np.loadtxt(fpath, unpack=True)

data[z_H] = data_s

savetype=".pdf", print_analysis=True):

data = loadwake()

y_R = data[0][0]/R

z_H = np.asarray(sorted(data.keys()))

# Assemble 2-D arrays

u = np.zeros((len(z_H), len(y_R)))

v = np.zeros((len(z_H), len(y_R)))

w = np.zeros((len(z_H), len(y_R)))

xvorticity = np.zeros((len(z_H), len(y_R)))

for n in range(len(z_H)):

u[n,:] = data[z_H[n]][1]

v[n,:] = data[z_H[n]][2]

w[n,:] = data[z_H[n]][3]

try:

xvorticity[n,:] = data[z_H[n]][4]

except IndexError:

pass

def turb_lines():

plt.hlines(0.5, -1, 1, linestyles='solid', linewidth=2)

plt.vlines(-1, 0, 0.5, linestyles='solid', linewidth=2)

plt.vlines(1, 0, 0.5, linestyles='solid', linewidth=2)

if "meanu" in plotlist or "all" in plotlist:

plt.figure(figsize=(10,5))

cs = plt.contourf(y_R, z_H, u, 20, cmap=plt.cm.coolwarm)

plt.xlabel(r'$y/R$')

plt.ylabel(r'$z/H$')

cb = plt.colorbar(cs, shrink=1, extend='both',

orientation='horizontal', pad=0.2)

cb.set_label(r'$U/U_{\infty}$')

turb_lines()

ax = plt.axes()

ax.set_aspect(2)

plt.grid(True)

plt.yticks([0,0.13,0.25,0.38,0.5,0.63])

styleplot()

if "meanv" in plotlist or "all" in plotlist:

plt.figure(figsize=(10,5))

cs = plt.contourf(y/0.5, z, v, 20, cmap=plt.cm.coolwarm)

plt.xlabel(r'$y/R$')

plt.ylabel(r'$z/H$')

styleplot()

cb = plt.colorbar(cs, shrink=1, extend='both',

orientation='horizontal', pad=0.3)

cb.set_label(r'$V/U_{\infty}$')

#turb_lines()

ax = plt.axes()

ax.set_aspect(2)

plt.grid(True)

plt.yticks([0,0.13,0.25,0.38,0.5,0.63])

if "v-wquiver" in plotlist or "all" in plotlist:

# Make quiver plot of v and w velocities

plt.figure(figsize=(10,5))

Q = plt.quiver(y_R, z_H, v, w, angles='xy')

plt.xlabel(r'$y/R$')

plt.ylabel(r'$z/H$')

plt.ylim(-0.2, 0.78)

plt.xlim(-3.2, 3.2)

plt.quiverkey(Q, 0.75, 0.2, 0.1, r'$0.1$ m/s',

labelpos='E',

coordinates='figure',

fontproperties={'size': 'small'})

plt.tight_layout()

plt.hlines(0.5, -1, 1, linestyles='solid', colors='r',

linewidth=2)

plt.vlines(-1, -0.2, 0.5, linestyles='solid', colors='r',

linewidth=2)

plt.vlines(1, -0.2, 0.5, linestyles='solid', colors='r',

linewidth=2)

ax = plt.axes()

ax.set_aspect(2)

plt.yticks([0,0.13,0.25,0.38,0.5,0.63])

if save:

plt.savefig(savepath+'v-wquiver'+savetype)

if "xvorticity" in plotlist or "all" in plotlist:

plt.figure(figsize=(10,5))

cs = plt.contourf(y_R, z_H, xvorticity, 10, cmap=plt.cm.coolwarm)

plt.xlabel(r'$y/R$')

plt.ylabel(r'$z/H$')

cb = plt.colorbar(cs, shrink=1, extend='both',

orientation='horizontal', pad=0.26)

cb.set_label(r"$\Omega_x$")

turb_lines()

ax = plt.axes()

ax.set_aspect(2)

plt.yticks([0,0.13,0.25,0.38,0.5,0.63])

styleplot()

if save:

plt.savefig(savepath+'/xvorticity_AD'+savetype)

if "meancontquiv" in plotlist or "all" in plotlist:

plt.figure(figsize=(7.5, 4.8))

# Add contours of mean velocity

cs = plt.contourf(y_R, z_H, u, np.arange(0.15, 1.25, 0.05),

cmap=plt.cm.coolwarm)

cb = plt.colorbar(cs, shrink=1, extend="both",

orientation="vertical", pad=0.02)

cb.set_label(r'$U/U_{\infty}$')

plt.hold(True)

# Make quiver plot of v and w velocities

Q = plt.quiver(y_R, z_H, v, w, width=0.0022, edgecolor="none",

scale=3.0)

plt.xlabel(r'$y/R$')

plt.ylabel(r'$z/H$')

#plt.ylim(-0.2, 0.78)

#plt.xlim(-3.2, 3.2)

plt.xlim(-3.66, 3.66)

plt.ylim(-1.22, 1.22)

plt.quiverkey(Q, 0.65, 0.055, 0.1, r"$0.1 U_\infty$",

labelpos="E",

coordinates="figure",

fontproperties={"size": "small"})

plt.hlines(0.5, -1, 1, linestyles='solid', colors='gray',

linewidth=2)

plt.hlines(-0.5, -1, 1, linestyles='solid', colors='gray',

linewidth=2)

plt.vlines(-1, -0.5, 0.5, linestyles='solid', colors='gray',

linewidth=2)

plt.vlines(1, -0.5, 0.5, linestyles='solid', colors='gray',

linewidth=2)

ax = plt.axes()

ax.set_aspect(2.0)

plt.xlim((-3, 3))

plt.ylim((-1.125, 1.125))

plt.yticks(np.around(np.arange(-1.125, 1.126, 0.125), decimals=2))

styleplot()

if save:

plt.savefig(os.path.join(savepath, "meancontquiv" + savetype))

if print_analysis:

savetype=".pdf", newfig=True, marker="--ok",

fill="none", figsize=(10, 5)):

"""Plots the transverse wake profile of some quantity. These can be

* meanu

* meanv

* meanw

* stdu

"""

U = Re_D/1e6

label = "Exp."

folder = exp_path + "/Wake/U_" + str(U) + "/Processed/"

z_H_arr = np.load(folder + "z_H.npy")

i = np.where(z_H_arr==z_H)

q = np.load(folder + quantity + ".npy")[i]

y_R = np.load(folder + "y_R.npy")[i]

if newfig:

plt.figure(figsize=figsize)

plt.plot(y_R, q/U, marker, markerfacecolor=fill, label=label)

plt.xlabel(r"$y/R$")

plt.ylabel(ylabels[quantity])

plt.grid(True)

with open("log.funkyDoCalc") as f:

for line in f.readlines():

try:

line = line.replace("=", " ")

line = line.split()

if line[0] == "planeAverageAdvectionY":

y_adv = float(line[-1])

elif line[0] == "weightedAverage":

z_adv = float(line[-1])

elif line[0] == "planeAverageTurbTrans":

turb_trans = float(line[-1])

elif line[0] == "planeAverageViscTrans":

visc_trans = float(line[-1])

elif line[0] == "planeAveragePressureGradient":

pressure_trans = float(line[-1])

except IndexError:

pass

return {"y_adv" : y_adv, "z_adv" : z_adv, "turb_trans" : turb_trans,

xlist = [-1.99, -1.5, -1.0, -0.75, -0.5, -0.25, 0.0, 0.25, 0.5, 0.75,

1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 7.99]

df = pandas.DataFrame()

for x in xlist:

print("Setting measurement plane to x =", x)

set_funky_plane(x)

call(["./Allrun.post"])

dfi = pandas.DataFrame(read_funky_log(), index=[x])

df = df.append(dfi)

if not os.path.isdir("processed"):

os.mkdir("processed")

df.index.name = "x"

print(df)

data = read_funky_log()

y_adv = data["y_adv"]

z_adv = data["z_adv"]

turb_trans = data["turb_trans"]

visc_trans = data["visc_trans"]

pressure_trans = data["pressure_trans"]

plt.figure(figsize=(6,4))

ax = plt.gca()

ax.bar(range(5), [y_adv, z_adv, turb_trans, visc_trans, pressure_trans],

color="gray", edgecolor="black", hatch="//", width=0.5)

ax.set_xticks(np.arange(5)+0.25)

ax.set_xticklabels(["$y$-adv.", "$z$-adv.",

"Turb.", "Visc.", "Press."])

plt.ylabel(r"$\frac{U \, \mathrm{ transport}}{UU_\infty D^{-1}}$")

plt.tight_layout()

if print_analysis:

sum = y_adv + z_adv + turb_trans + visc_trans + pressure_trans

df = pandas.read_csv("processed/mom_transport.csv")

plt.plot(df.x, df.y_adv, "-o", label=r"$-V \partial U / \partial y$")

plt.plot(df.x, df.z_adv, "-s", label=r"$-W \partial U / \partial z$")

plt.plot(df.x, df.turb_trans, "-^", label=r"$\nu_t \nabla^2 U$")

plt.plot(df.x, df.visc_trans, "->", label=r"$\nu \nabla^2 U$")

plt.plot(df.x, df.pressure_trans/10, "-<", label=r"$-\partial P / \partial x$ ($\times 10^{-1}$)")

plt.legend(loc="lower right", ncol=1)

plt.xlabel("$x/D$")

plt.ylabel(r"$\frac{U \, \mathrm{ transport}}{UU_\infty D^{-1}}$")

plt.grid()

times = os.listdir("postProcessing/sets")

times.sort()

latest = times[-1]

filepath = os.path.join("postProcessing", "sets", latest,

"streamwise_U.xy")

x, u, v, w = np.loadtxt(filepath, unpack=True)

plt.plot(x, u, "k")

plt.xlabel("$x/D$")

plt.ylabel(r"$U/U_\infty$")

plt.grid()

plt.figure(figsize=(7.5, 4))

plt.subplot(121)

plot_U_streamwise()

plt.subplot(122)

plot_mom_transport()

plt.tight_layout()

if save:

if not os.path.isdir("figures"):

os.mkdir("figures")

set_sns()

#resample_wake(x=1.0)

plotwake(plotlist=["meancontquiv"], save=True)

#make_momentum_trans_bargraph()

if not os.path.isfile("processed/mom_transport.csv"):

run_funky_batch()

#plot_mom_transport()

plot_streamwise(save=True)