def separation_point(method, field_u, field_w, save=False):
radius = 75
theta = np.linspace(0, 120, 120)
theta = theta * 2 * np.pi / 360
x = 200 - radius * np.cos(theta)
y = 150 + radius * np.sin(theta)
j = np.floor(x / 10).astype(int)
i = np.floor(y / 10).astype(int)
dif_utab = []
u_tab = []
w_tab = []
print(i[0])
aux_u = field_u[i[0]][j[0]]
for k in range(0, 120):
ii = i[k]
jj = j[k]
val_u = field_u[ii][jj]
val_w = field_w[ii][jj]
dif_u = val_u - aux_u
dif_utab.append(dif_u)
u_tab.append(val_u)
w_tab.append(val_w)
max_idx_dif = max(range(len(dif_utab)), key=dif_utab.__getitem__)
theta_sep = theta[max_idx_dif]
# Plot
legendloc = (0.75, 0.55)
line_thickness = 1
real_theta_sep = theta_sep + 0.255
titlesize = 20
axis_lbsize = 25
tick_lbsize = 15
tickn = 8
fig = mplPlotter(light=True).setup2d(figsize=(8, 8))
ax1 = mplPlotter(light=True, fig=fig, shape_and_position=111,
usetex=False).plot2d(x=theta,
y=np.array(u_tab),
resize_axes=False,
color='red',
label=r'$\mathit{u}$',
more_subplots_left=True,
linewidth=line_thickness)
mplPlotter(
light=True, fig=fig, ax=ax1, shape_and_position=111, usetex=False
).plot2d(
x=theta,
y=np.array(w_tab),
plot_title=r'Velocity along sphere surface as a function of $\theta$,'
+ '\n plane y=0',
title_size=titlesize,
title_y=1.1,
aspect=0.1,
resize_axes=True,
grid=True,
gridlines='dotted',
x_bounds=[0, 140 / 180 * np.pi],
y_bounds=[-4, 13],
custom_x_ticklabels=[0, 140],
y_tick_number=tickn,
x_tick_number=tickn,
x_ticklabel_size=tick_lbsize,
y_ticklabel_size=tick_lbsize,
color='blue',
label=r'$\mathit{w}$',
more_subplots_left=True,
linewidth=line_thickness,
y_label=r'$\mathit{V}$' + ' $[m/s]$',
ylabel_rotation=90,
x_label=r'$\mathit{\theta}$' + ' $[deg]$',
yaxis_label_size=axis_lbsize,
xaxis_label_size=axis_lbsize)
ax1.axvline(
x=real_theta_sep,
ymin=-5,
ymax=15,
c='green',
linewidth=line_thickness,
label=r'$\mathit{\theta_{sep}}$' +
r'$ = {}^\circ$'.format(np.round(real_theta_sep / np.pi * 180, 2)))
ax1.legend(loc=legendloc, fontsize=21)
plt.tight_layout()
if save is True:
plt.savefig(os.path.join(img_path, 'sep_point_velocity.png'), dpi=150)
plt.show()
return theta_sep, u_tab, w_tab, theta
r'C:\Users\xXY4n\AE BSc\AE Year 2\Aerodynamics project\Data Analysis\data\velocity_ensemble_averaged\{}\{}_{}.txt'
.format(plane, 'w', version))
except:
interpolate_all(fill=fill,
plane=plane,
version=version,
quirk=quirk,
filenamestart=filenamestart,
var=re.findall(r'-?\d+', plane)[0],
f=f)
"""
Plot
"""
# Subplot setup
fig = mplPlotter(light=True).setup2d(figsize=(20, 5))
y_ticks = 8
x_ticks = 9 if plane == 'y=0' or plane == 'z=0' else 8
degree = 2
tsize = 20
axsize = 20
pad = 15
tit_y = 1.05
cbtit_size = 15
fillsphere = True
aspect = 1
save = False
if plane == 'z=0' or plane == 'y=0':
x_bounds = [0, 40]
y_bounds = [0, 30]
plane=plane,
version=version,
quirk=quirk,
filenamestart=filenamestart,
var=re.findall(
r'-?\d+', plane)[0],
f=f)
if clean is True:
clean_field()
"""
Plot
"""
# Subplot setup
fig = mplPlotter(light=True).setup2d(figsize=(20, 5))
y_ticks = 4
x_ticks = 5 if plane == 'y=0' or plane == 'z=0' else 4
degree = 2
tsize = 25
axsize = 25
pad = 15
tit_y = 1.05
cbtit_size = 15
fillsphere = True
aspect = 1
if plane == 'z=0' or plane == 'y=0':
x_bounds = [0, 40]
y_bounds = [0, 30]
diff_field = np.loadtxt(os.path.join(os.path.join(os.path.join(comp_field_path, comp_field), plane), '{}_{}.txt'.format(comp_field, comp)))
diff_field = w_mosaic
------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------------------------
"""
diff_field = np.loadtxt(
os.path.join(sub_field_path,
'{}_{}_vs_{}.txt'.format(comp, ensemble_method, comp_field)))
# Fields in plot
ens_field_title = 'RBF'
comp_field_title = 'Potential Flow'
# Figure setup
fig = mplPlotter(light=True).setup2d(figsize=(20, 6))
y_ticks = 4
x_ticks = 5 if plane == 'y=0' or plane == 'z=0' else 4
degree = 2
tsize = 25
axsize = 25
pad = 15
tit_y = 1.05
cbtit_size = 15
fillsphere = True
aspect = 1
if plane == 'z=0' or plane == 'y=0':
x_bounds = [0, 40]
y_bounds = [0, 30]
import pandas as pd
import numpy as np
import scipy.interpolate as int
from scipy.signal import lfilter
from scipy.signal import savgol_filter
import scipy.optimize as optimize
from mpl_plotter_mpl_plotting_methods import MatPlotLibPublicationPlotter as mplPlotter
# Plot setup
fig = mplPlotter(light=True).setup2d(figsize=(7, 15))
legendloc = (0.6, -0.65)
pointsize = 3
# File read
df = pd.read_csv(
r'C:\Users\xXY4n\AE BSc\AE Year 2\Aerodynamics project\Data Analysis\data\stagnation_line\stagnation_line_z=0.csv',
index_col=0)
df.columns = ['x', 'y', 'z', 'u', 'v', 'w']
xticks = 6
yticks = 6
# Experimental data
x = df['x']
u = df['u']
ax1 = mplPlotter(light=True, fig=fig, shape_and_position=411,
usetex=False).plot2d(
x=x,
if save is True:
dpi = 150
if epsilon2 == 500:
filename = r'C:\Users\xXY4n\AE BSc\AE Year 2\Aerodynamics project\Data Analysis\images\2DInterpolation_epsilon500_{}.png'.format(comp)
else:
filename = r'C:\Users\xXY4n\AE BSc\AE Year 2\Aerodynamics project\Data Analysis\images\2DInterpolation_{}_{}.png'.format(function, comp)
else:
dpi = None
filename = None
"""
Scatter
"""
widths = [1, 1, 1, 1]
heights = [1]
fig = mplPlotter(light=True).setup2d(figsize=(22, 7))
legendloc=(0.6, -0.5)
y_ticks = 6
x_ticks = 6
degree = 2
tsize=16
axsize = 15
pad = 15
tity = 1.05
shrink = 0.32
cb_vmin = arrcomp[0].min()
cb_vmax = arrcomp[0].max()
cmap = 'RdBu'
mplPlotter(light=True, fig=fig, shape_and_position=141).plot2d(scatter=True, x=y, y=z, c=arrcomp[0],