def make_movie(M, Range=None, field=['E', 'vorticity'], Dirbase=None, Dt=1):
if Dirbase == None:
Dirbase = '/Users/stephane/Documents/Experiences_local/Accelerated_grid/PIV_data' # local saving
nx, ny, nt = M.shape()
axes = panel(M)
if Range is not None:
start, stop, step = tuple(Range)
else:
start, stop, step = tuple([0, nt, 1])
frames = range(start, stop, step)
# field = ['Ux','Uy']
# field = ['E','vorticity']
figs = {}
Dirname = Dirbase + '/' + M.Id.get_id() + '/' + graphes.remove_special_chars(str(field)) + '/'
print(Dirname)
for i, f in enumerate(field):
if not hasattr(M, f):
M, field_n[i] = vgradient.compute(M, field[i], Dt=Dt)
field = field_n
# M,field[1] = vgradient.compute(M,field[1],Dt=Dt)
if Dt > 1:
print('Smoothed data')
Dirname = Dirname + 'Smooth_Dt_' + str(int(Dt)) + '/'
for i in frames:
graphes.set_fig(1)
for axe in axes:
plt.sca(axe)
plt.cla()
axes = panel(M, fignum=1)
plt.sca(axes[1])
print(i)
graphes.Mplot(M, field[0], i, fignum=1, log=True)
plt.text(-10, 80, field[0], fontsize=20)
plt.sca(axes[2])
graphes.Mplot(M, field[1], i, fignum=1, log=True)
plt.text(-10, 80, field[1], fontsize=20)
figs.update(graphes.legende('', '', 'Front view', cplot=True))
graphes.save_figs(figs, savedir=Dirname, suffix='_' + str(i), dpi=100, frmt='png', display=False)
return axes
def make_2dmovie(M, name, Range=None, fignum=1, local=True, log=False, vmin=0, vmax=1, filt=False):
"""
Movie of the colormap of the velocity modulus U over time
INPUT
-----
M : Mdata class instance, or any other object that contains the following fields :
methods : shape()
attributes : Ux, Uy
Sdata object
Ids object
...
name : name of the field to be plotted. example : Ux,Uy, vorticity, strain
Range : np array
fignum : int. default value is 1
Dirname : string
Directory to save the figures
log : bool. default value is True
OUTPUT
-----
None
"""
if Range is not None:
start, stop, step = tuple(Range)
else:
start, stop, step = tuple([0, M.shape()[-1], 5])
# U=np.sqrt(S.Ux**2+S.Uy**2)
# by default, pictures are save here :
if local:
Dirlocal = '/Users/stephane/Documents/Experiences_local/Accelerated_grid'
else:
Dirlocal = os.path.dirname(M.Sdata.fileCine)
Dirname = name
if filt:
Dirname = Dirname + '_filtered'
Dir = Dirlocal + '/PIV_data/' + M.Id.get_id() + '/' + Dirname + '/'
print(Dir)
fig = graphes.set_fig(fignum)
graphes.set_fig(0) # clear current figure
print('Compute ' + name)
M, field = vgradient.compute(M, name, filter=filt)
for i in range(start, stop, step):
# Z = energy(M,i)
graphes.Mplot(M, field, i, fignum=fignum, vmin=vmin, vmax=vmax, log=log, auto_axis=True)
# graphes.color_plot(Xp,Yp,-Z,fignum=fignum,vmax=700,vmin=0)
if i == start:
cbar = graphes.colorbar() # fignum=fignum,label=name+'(mm^2 s^{-2})')
else:
print('update')
# cbar.update_normal(fig)
filename = Dir + 'V' + str(i)
graphes.save_fig(fignum, filename, frmt='png')
def example(M, i=None):
figs = {}
if i == None:
nx, ny, nt = M.shape()
i = nt // 4
fields, names, vmin, vmax, labels, units = std_fields()
for j, field in enumerate(fields):
figs.update(graphes.Mplot(M, field, i, fignum=j + 1, colorbar=True, vmin=vmin[j], vmax=vmax[j]))
### add label on colorbar
return figs
def example(M, Range=None, field=['E', 'vorticity']):
nx, ny, nt = M.shape()
axes = panel(M)
if Range is not None:
start, stop, step = tuple(Range)
else:
start, stop, step = tuple([0, nt, 1])
frames = range(start, stop, step)
# field = ['Ux','Uy']
# field = ['E','vorticity']
figs = {}
Dirbase = '/Users/stephane/Documents/Experiences_local/Accelerated_grid/PIV_data' # local saving
Dirname = Dirbase + '/' + M.Id.get_id() + '/' + graphes.remove_special_chars(str(field)) + '/'
print(Dirname)
M, field[0] = vgradient.compute(M, field[0])
M, field[1] = vgradient.compute(M, field[1])
for i in frames:
graphes.set_fig(1)
for axe in axes:
plt.sca(axe)
plt.cla()
axes = panel(M, fignum=1)
plt.sca(axes[1])
graphes.Mplot(M, field[0], i, log=True)
plt.text(-10, 20, field[0], fontsize=20)
plt.sca(axes[2])
graphes.Mplot(M, field[1], i, fignum=1, log=True)
plt.text(-10, 20, field[1], fontsize=20)
figs.update(graphes.legende('', '', 'Front view', cplot=True))
graphes.save_figs(figs, savedir=Dirname, suffix='_' + str(i), dpi=100, frmt='png')
return axes
def make_plot(M, Range=None, color='k', field=['E', 'vorticity'], Dirbase=None, Dt=1, example=False, total=True,
fignum=1, save=True):
if Dirbase == None:
Dirbase = '/Users/stephane/Documents/Experiences_local/Accelerated_grid/PIV_data/Test6/' # local saving
Dirbase = './Stat_avg/Panel/' + M.Id.date
axes = flex_panel(M, fignum=fignum)
# for axe in axes:
# plt.sca(axe)
# plt.cla()
frames = select_range(M, Range)
# field = ['Ux','Uy']
# field = ['E','vorticity']
figs = {}
if hasattr(M, 'id'):
Dirname = Dirbase + '/' + M.Id.get_id() + '/' + graphes.remove_special_chars(str(field)) + '/'
else:
Dirname = Dirbase + '/JHTD_Data/' + graphes.remove_special_chars(str(field)) + '/'
print(Dirname)
if Dt > 1:
print('Smoothed data')
Dirname = Dirname + 'Smooth_Dt_' + str(int(Dt)) + '/'
# Dt = 50
t_moy, E_moy = access.avg_vs_t(M, 'E', frames, Dt=Dt)
t_moy, Omega_moy = access.avg_vs_t(M, 'omega', frames, Dt=Dt)
t_moy, Strain_moy = access.avg_vs_t(M, 'strain', frames, Dt=Dt)
t_moy, Y_pdf_moy = access.avg_vs_t(M, field[1], frames, Dt=Dt)
epsilon = scale.dissipation_rate(Omega_moy) # dissipation rate
eta = scale.K_scale(epsilon) # dissipative scale
micro_1 = np.sqrt(1. / 4 * E_moy / Strain_moy ** 2)
micro_2 = np.sqrt(E_moy / (Omega_moy) ** 2)
Re = scale.Re(micro_1, eta)
Re_lambda_1 = scale.Re_lambda(E_moy, micro_1)
Re_lambda_2 = scale.Re_lambda(E_moy, micro_2)
L = scale.I_scale(Re, E_moy)
# plt.sca(axes[2])
# graphes.graphloglog(t_moy,E_moy,fignum=1,label=color+'o-')
# Fourier.add_theory(t_moy,E_moy,[-2.],fignum=1)
# graphes.graphloglog(t_moy,Y_pdf_moy,fignum=1,label=color+'s-')
# graphes.graphloglog(t_moy,epsilon,fignum=1,label='gv-')
# Fourier.add_theory(t_moy,epsilon,[-3.],fignum=1)
# figs.update(graphes.legende('t (s)','E (mm^2/s^2), epsilon(mm^2/s^-3)',''))
plt.sca(axes[1])
graphes.graphloglog(t_moy, eta, fignum=fignum, label=color + 'o-')
graphes.graphloglog(t_moy, micro_1, fignum=fignum, label=color + 's-')
graphes.graphloglog(t_moy, micro_2, fignum=fignum, label='cp-')
graphes.graphloglog(t_moy, L, fignum=fignum, label='gv-')
figs.update(graphes.legende('t (s)', 'eta (mm), lambda (mm)', ''))
plt.sca(axes[2])
graphes.graphloglog(t_moy, Re, fignum=fignum, label=color + 'o-')
graphes.graphloglog(t_moy, Re_lambda_1, fignum=fignum, label=color + 's-')
graphes.graphloglog(t_moy, Re_lambda_2, fignum=fignum, label='cp-')
figs.update(graphes.legende('t (s)', 'Re , Re_lambda', ''))
# print(t_moy)
# print(Y_moy)
# print(t)
# print(Y_moy)
indices = [0, 1]
# indices = [1,4]
cla_axes = [axes[i] for i in indices]
if save:
graphes.save_figs(figs, savedir=Dirname, prefix='General', suffix='_vs_t', dpi=300, frmt='png', display=True)
individual = False
if example:
frames_disp = [1200]
else:
step = frames[1] - frames[0]
frames_disp = range(frames[0] + step * 10, frames[-1], step * 10)
if individual:
for frame in frames_disp:
# print(frame)
# print(frames)
i = frames.index(frame)
graphes.set_fig(1)
for axe in cla_axes:
plt.sca(axe)
plt.cla()
axes = flex_panel(M, fignum=1)
if total:
plt.sca(axes[0])
graphes.Mplot(M, field[0], frame, fignum=1, log=True)
plt.text(-10, 80, field[0], fontsize=20)
plt.sca(axes[1])
# graphes.graphloglog(t_moy,eta,fignum=1,label='ko-')
# graphes.graphloglog(t_moy,micro,fignum=1,label='ks-')
graphes.graph([t_moy[i]], [eta[i]], fignum=1, label='ro')
graphes.graph([t_moy[i]], [micro_1[i]], fignum=1, label='rs')
graphes.graph([t_moy[i]], [micro_2[i]], fignum=1, label='rp')
graphes.graphloglog([t_moy[i]], [L[i]], fignum=1, label='rv-')
plt.sca(axes[2])
graphes.graphloglog([t_moy[i]], [Re[i]], fignum=1, label='ro-')
graphes.graphloglog([t_moy[i]], [Re_lambda_1[i]], fignum=1, label='rs-')
graphes.graphloglog([t_moy[i]], [Re_lambda_2[i]], fignum=1, label='rp-')
plt.sca(axes[3])
figs.update(graphes.pdf(M, 'Ux', frame, Dt=Dt, fignum=1, label='m^'))
figs.update(graphes.pdf(M, 'Uy', frame, Dt=Dt, fignum=1, label='b>'))
figs.update(graphes.legende('t (s)', 'Re , Re_lambda', ''))
plt.sca(axes[4])
figs.update(graphes.pdf(M, field[1], frame, Dt=Dt, fignum=1, label=color + '-'))
# graphes.Mplot(M,field[1],i,fignum=1,log=True)
# plt.text(-10,80,'PDF '+field[1],fontsize=20)
# figs.update(graphes.legende('','','Front view',cplot=True))
graphes.save_figs(figs, savedir=Dirname, suffix='_' + str(frame), dpi=100, frmt='png', display=False)
return axes
print M.shape()
print M.Uy[10, :, 0]
print M.Id.date
print M.Id.index
for M in Mlist:
print(M.Sdata.fileCine[-20:-5])
print(M.Sdata.fileDir)
print(M.Sdata.filename) # name of the file(SData) that stores measures (M)
print(M.Sdata.param)
print M.shape()
# Plot the time averaged energy
frame = 10
# args are (M, variable, frame, vmin, vman)
graphes.Mplot(M, 'E', frame, vmin=0, vmax=100000)
graphes.colorbar()
# Plot the vorticity at a particular time
graphes.Mplot(M, 'omega', frame, vmin=-300, vmax=300)
graphes.colorbar()
# Plot the enstrophy at a particular time (frame#)
graphes.Mplot(M, 'enstrophy', frame, vmin=0, vmax=90000)
graphes.colorbar()
########################################################
figs = {}
fields, names, vmin, vmax, labels, units = comp.std_fields()
# print(M.param.v)
indices = range(50, M.Ux.shape[2])