def plot_slice(filename, start, count, output, loc, name):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
fields = ['b', 'u', 'v', 'w', 'ωz']
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: '{}_{:06}.png'.format(name, write)
# Layout
if loc[0] == 'x':
nrows, ncols = 5, 1
image = plot_tools.Box(6, 1)
image_axes = (2, 3)
data_slices = (0, slice(None), slice(None))
elif loc[0] == 'y':
nrows, ncols = 5, 1
image = plot_tools.Box(6, 1)
image_axes = (1, 3)
data_slices = (slice(None), 0, slice(None))
elif loc[0] == 'z':
nrows, ncols = 2, 3
image = plot_tools.Box(2, 2)
image_axes = (1, 2)
data_slices = (slice(None), slice(None), 0)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, field in enumerate(fields):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call plotting helper (dset axes: [t, x, y, z])
task = f"interp({field}, {loc})"
dset = file['tasks'][task]
plot_tools.plot_bot(dset,
image_axes, (index, ) + data_slices,
axes=axes,
title=task,
even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['b', 'p', 'u', 'w']
clims = [(-.5, .5), (-.15, .15), (-.5, .5), (-.5, .5)]
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 4, 1
image = plot_tools.Box(4, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
cmap = copy.copy(plt.cm.get_cmap("RdBu_r"))
# Plot writes
with h5py.File(filename, mode='r') as file:
# Get the temperature data
dset = file['tasks']['b']
for index in range(start, start + count):
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
plt.imsave(str(savepath),
np.flip(dset[index].T, axis=0),
cmap=cmap,
vmin=-0.5,
vmax=0.5,
dpi=dpi)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# To import the switchboard
import sys
switch_path = "../" + NAME
sys.path.insert(0, switch_path) # Adds higher directory to python modules path
import switchboard as sbp
# Get relevant parameters from switchboard used in loop
plot_all = sbp.plot_all_variables
#bp_task_name = sbp.bp_task_name
n_clrbar_ticks = sbp.n_clrbar_ticks
#T = sbp.T
# Display parameters
x_f = sbp.x_0 + sbp.L_x_dis
z_b = sbp.z_t - sbp.L_z_dis
# Calculate aspect ratio
AR = sbp.L_x_dis / sbp.L_z_dis
# Set tuples for display boundaries
x_lims = [sbp.x_0, x_f]
y_lims = [z_b, sbp.z_t]
# Change the size of the text overall
font = {'size' : sbp.font_size}
plt.rc('font', **font)
# Set parameters based on switches
tasks, nrows, ncols, title_str, time_factor = flip_the_switches(plot_all, sbp.plot_sponge, sbp.use_stop_sim_time, sbp.T)
# Plot settings
scale = sbp.scale
dpi = sbp.dpi
title_func = lambda sim_time: title_str.format(NAME, sim_time/time_factor)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
image = plot_tools.Box(AR, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.15, 0.15)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
if (plot_all == False):
# Plot stratification profile on the left
ax0 = plot_bp_on_left(sbp.bp_task_name, sbp.snapshots_dir, sbp.bp_snap_dir, mfig, sbp.buffer, sbp.extra_buffer, sbp.vp_dis_ratio, y_lims)
if sbp.plot_sponge:
ax1 = add_sponge_profile(sbp.sl_task_name, sbp.snapshots_dir, sbp.sl_snap_dir, mfig, sbp.buffer, sbp.extra_buffer, sbp.vp_dis_ratio, y_lims)
# shift n so that animation is on the right side
n = 1
plot_one_task(n, ncols, mfig, file, task, index, x_lims, y_lims, n_clrbar_ticks)
# Add title to frame
add_frame_title(fig, file, index, title_func)
# Save figure
save_fig_as_frame(fig, file, index, savename_func, output, dpi)
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
krel_list = [0.5, 1.0, 2.0, 3.0, 4.0, 5.0]
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 2, 3
image = plot_tools.Box(2, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Load projectors
def get_evals_proj(krel):
with np.load("data_modes_%s.npz" % krel, 'r') as file:
evals = file['evals']
proj = file['proj']
return evals, proj
evals_proj = {krel: get_evals_proj(krel) for krel in krel_list}
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, krel in enumerate(krel_list):
# Build subfigure axes
i, j = divmod(n, ncols)
ax = mfig.add_axes(i, j, [0, 0, 1, 1])
# Plot amplitudes
data = build_state_vector(file, index, krel)
evals, proj = evals_proj[krel]
amps = proj @ data
ax.loglog(evals.real, np.abs(amps), 'ob')
ax.loglog(-evals.real, np.abs(amps), '.r')
ax.set_title('krel = %s' % krel)
ax.grid()
ax.set_xlabel('ω')
ax.set_ylabel('amp')
ax.set_ylim(1e-26, 1e-2)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def integral(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['ZF']
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'ZF_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 1
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
with h5py.File(filename, mode='r') as file:
time = file['scales']['sim_time']
xaxis = file['scales']['x']['1.0']
dset = file['tasks']['ZF']
f = open('zf_set', 'w')
for j in range(0, len(time)):
for k in range(0, len(xaxis)):
f.write('%f %f %f\n' % (time[j], xaxis[k], dset[j][k][0]))
f.write('\n')
f.close()
return
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call plotting helper (dset axes: [t, x, y, z])
dset = file['tasks'][task]
logger.info('dset %s length %s' % (dset, len(dset.shape)))
image_axes = (1, 1)
data_slices = (index, slice(None), slice(None), 0)
plot_tools.plot_bot(dset, (1, 2), (slice(None), slice(None)))
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output, write_start):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['ux','uz']
scale = 2.5
dpi = 300
title_func = lambda sim_time: r'$t = {:.3f}$'.format(sim_time)
# savename_func = lambda write: 'yubo_{:06}.png'.format(write+write_start)
def savename_func(write):
# regex parse out filename number, 10 writes per file
num_per_file = 10
write_num = (write - 1) % num_per_file
filenum = int(re.match('.*s([\d]+)\.h5', filename)[1])
suffix_num = (filenum - 1) * num_per_file + write_num
if suffix_num > 201:
suffix_num -= 9 # hard coded, one of the restores is misnumbered
print(suffix_num)
return 'yubo_{:06}.png'.format(suffix_num)
# Layout
nrows, ncols = 1, 2
image = plot_tools.Box(1, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
if n==0: #ux
clim = [-0.25, 0.25]
title = r'$u_x$'
elif n==1: #uz
clim = [-0.1, 0.1]
title = r'$\Upsilon$'
plot_tools.plot_bot_3d(dset, 0, index, axes=axes, title=title, even_scale=True,clim=clim)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, y=title_height)
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['vorticity']
cmap = plt.cm.RdBu_r
savename_func = lambda write: 'write_{:06}.png'.format(write)
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
dpi = 200
func = lambda phi, r, data: (r * np.cos(phi), r * np.sin(phi), data)
# Layout
nrows, ncols = 1, 1
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0, 0, 0, 0)
margin = plot_tools.Frame(0.1, 0.1, 0.1, 0.1)
scale = 3
# Create figure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plotting loop
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
paxes, caxes = plot_tools.plot_bot_3d(dset,
0,
index,
axes=axes,
title=task,
even_scale=True,
visible_axes=False,
func=func,
cmap=cmap)
paxes.axis('off')
caxes.cla()
caxes.axis('off')
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.4, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def vertical(filename, start, count, output):
"""Slices in y-z at edge (x=0)."""
# Plot settings
tasks = [
'b vertical', 'q vertical', 'temp vertical', 'u vertical',
'v vertical', 'w vertical'
]
even_scale = [False, False, False, True, True, True]
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'vert_{:06}.png'.format(write)
# Layout
nrows, ncols = 2, 3
image = plot_tools.Box(2, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call plotting helper (dset axes: [t, x, y, z])
dset = file['tasks'][task]
image_axes = (2, 3)
data_slices = (index, 0, slice(None), slice(None))
plot_tools.plot_bot(dset,
image_axes,
data_slices,
axes=axes,
title=task,
even_scale=even_scale[n])
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['uphi', 'ur', 'vorticity', 'b']
scale = 2.5
dpi = 200
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 2, 2
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Function
def func(phimesh, rmesh, data):
xmesh = rmesh * np.cos(phimesh)
ymesh = rmesh * np.sin(phimesh)
return xmesh, ymesh, data
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_tools.plot_bot_3d(dset,
0,
index,
axes=axes,
title=task,
even_scale=True,
func=func)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def midplane(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
#tasks = ['phi','w','n','phi2','w2','n2']
tasks = ['phi', 'w', 'n', 'phi ZF', 'w ZF', 'n ZF']
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'mid_{:06}.png'.format(write)
# Layout
nrows, ncols = 2, 3
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call plotting helper (dset axes: [t, x, y, z])
dset = file['tasks'][task]
logger.info('dset %s length %s' % (dset, len(dset.shape)))
#if (n > 1):
#dset = np.log10(np.absolute(dset))
#dset = file.create_dataset('log_%d' %n, data=dset)
# image_axes = (2, 1)
# data_slices = (index, slice(None), slice(None), 0)
plot_tools.plot_bot_3d(dset,
0,
index,
axes=axes,
title=task,
even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['u', 'v', 'vorticity']
scale = 2.5
dpi = 400
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'ucvc_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 3
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
current_cmap = matplotlib.cm.viridis
current_cmap.set_bad(color='white')
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
image_axes = (1, 2)
data_slices = [index, slice(None), slice(None)]
plot_tools.plot_bot(dset,
image_axes,
data_slices,
axes=axes,
title=task,
cmap=current_cmap) #, clim=[-1,1])
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['phi', 'rho_g', 'w_g', 'w_m']
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 4
image = plot_tools.Box(1, 4)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
xlims = {
'phi': (0, 1),
'rho_g': (0, 0.1),
'w_g': (0, 4.0),
'w_m': (0, 4.0)
}
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
z = file['scales/z/1.0'][:]
axes.plot(dset[index], z, '.-')
axes.set_title(task)
axes.set_ylabel('z')
axes.set_xlim(xlims[task])
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def plot_spectra(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['b', 'u', 'v', 'w']
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'spec_{:06}.png'.format(write)
# Layout
nrows = 3
ncols = len(tasks)
image = plot_tools.Box(4, 4)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
scale = 2
dpi = 100
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for j, task in enumerate(tasks):
dset = file['tasks'][task]
# Load field in grid layout
field.set_scales(1)
field['g'] = dset[index]
for i in range(3):
data = np.log10(integrated_spectra(field, axis=i).T)
image_axes = [0, 1, 2]
image_axes.pop(i)
# Build subfigure axes
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
plot_tools.plot_bot(field,
image_axes,
data=data,
axes=axes,
title=task,
even_scale=False,
cmap='viridis')
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['p', 'b', 'u', 'w']
scale = 2
dpi = 80
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 4
image = plot_tools.Box(1, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
logmag = lambda xmesh, ymesh, data: (xmesh, ymesh, np.log10(np.abs(data)))
clim = [-20, 0]
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_tools.plot_bot_3d(dset,
0,
index,
axes=axes,
title=task,
func=logmag,
clim=clim)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
#with h5py.File(filename, mode='r') as file:
# tasks = sorted(file['tasks'].keys())
tasks = ['u', 'v', 'w']
scale = 4
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 3
image = plot_tools.Box(2, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
plt.style.use('prl')
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start + count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
#plot_axes = [3,1]
new_slices = [index] + run_slices
plot_tools.plot_bot(dset,
plot_axes,
new_slices,
axes=axes,
title=task,
even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(prefix, start, count, output, task):
"""Save plot of specified task at given time for six (6) runs."""
task = str(task)
scale = 4
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 3, 2
image = plot_tools.Box(2, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
plt.style.use('prl')
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
for folder in glob.glob(prefix):
filename = folder + "snapshots/snapshots_s1.h5"
with h5py.File(filename, mode='r') as file:
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset_title = 'tasks/' + task
dset = file[dset_title][10, ]
new_slices = [index] + run_slices
plot_tools.plot_bot(dset,
plot_axes,
new_slices,
axes=axes,
title=task,
even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
#tasks = ['invRi']
tasks = ['v']
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 1
image = plot_tools.Box(2,1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
# plot_tools.plot_bot_3d(dset, 0, index, axes=axes, clim=(0,0.01),title='Inverse Richardson', even_scale=True)
plot_tools.plot_bot_3d(dset, 0, index, axes=axes, clim=(-0.2,0.2),title='Meridional Velocity (kmhr^(-1))', even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def planes(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['ze bot','tf bot', 'ze mid', 'tf mid', 'ze top', 'tf top']
scale = 2.0
dpi = 200
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'mid_{:06}.png'.format(write)
# Layout
nrows, ncols = 3, 2
image = plot_tools.Box(2, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call plotting helper (dset axes: [t, x, y, z])
dset = file['tasks'][task]
image_axes = (2, 1)
data_slices = (index, slice(None), slice(None), 0)
plot_tools.plot_bot(dset, image_axes, data_slices, axes=axes, title=task, even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
def plot_power_spectra(ce2_filename,
start,
count,
output='write_',
field='zeta',
climits=None,
xlimits=None,
ylimits=None,
dns_tidx=-1,
ce2_tidx=-1,
label=None,
dns_filename=None):
with h5py.File(dns_filename,
'r') as dns_data, h5py.File(ce2_filename, 'r') as ce2_data:
nrows, ncols = 1, 3
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.1, 0.1, 0.1)
margin = plot_tools.Frame(0.1, 0.1, 0.1, 0.1)
scale = 4
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
dns_axes = mfig.add_axes(0, 0, [0, 0, 1, 1])
if field == 'zeta':
power_axis_label = r"$\log_{10} |\hat{\zeta}|^2$"
elif field == 'theta':
power_axis_label = r"$\log_{10} |\hat{\theta}|^2$"
else:
raise NotImplementedError(
"Field can only be theta or zeta, not {}".format(field))
# DNS
dns_image_axes = (2, 1)
dns_image_slices = (dns_tidx, slice(None), slice(None))
dns_kspace_data = dns_data['tasks/{}_kspace'.format(field)]
dns_time = dns_data['scales/sim_time'][dns_tidx]
pax, cax = plot_tools.plot_bot(dns_kspace_data,
dns_image_axes,
dns_image_slices,
func=calc_dns_power,
clim=climits,
cmap='viridis',
axes=dns_axes)
pax.xaxis.set_major_locator(MaxNLocator(integer=True))
#pax.yaxis.set_major_locator(MaxNLocator(integer=True))
pax.set_xlim(xlimits)
pax.set_ylim(ylimits)
cax.set_xlabel(power_axis_label)
pax.set_xlabel(r"$k_x$")
pax.set_ylabel(r"$k_{y}$")
pax.text(0.9,
0.85,
'a',
bbox={
'facecolor': 'grey',
'alpha': 0.5,
'boxstyle': 'round'
},
transform=pax.transAxes,
fontsize=18,
color='white')
pax.set_rasterized(True)
# CE2
ce2_axes = mfig.add_axes(0, 1, [0, 0, 1, 1])
ce2_image_axes = (1, 3)
ce2_image_slices = (ce2_tidx, slice(None), 0, slice(None))
ce2_kspace_data = ce2_data['tasks/{}_power'.format(field)]
ce2_time = ce2_data['scales/sim_time'][ce2_tidx]
ce2_write = ce2_data['scales/write_number'][ce2_tidx]
pax, cax = plot_tools.plot_bot(ce2_kspace_data,
ce2_image_axes,
ce2_image_slices,
func=calc_ce2_power,
clim=climits,
cmap='viridis',
axes=ce2_axes)
cax.set_xlabel(power_axis_label)
pax.xaxis.set_major_locator(MaxNLocator(integer=True))
pax.set_xlim(xlimits)
pax.set_ylim(ylimits)
pax.set_xlabel(r"$k_x$")
pax.set_ylabel(r"$k_{y}$")
pax.text(0.9,
0.85,
'b',
bbox={
'facecolor': 'grey',
'alpha': 0.5,
'boxstyle': 'round'
},
transform=pax.transAxes,
fontsize=18,
color='white')
pax.set_rasterized(True)
# plot only kx = 0 mode
kx0_axes = mfig.add_axes(0, 2, [0.03, 0, 0.94, 0.94])
kx, ky, data = plot_tools.get_plane(ce2_kspace_data, ce2_image_axes[0],
ce2_image_axes[1],
ce2_image_slices)
ce2_kx, ce2_ky, ce2_power = calc_ce2_power(kx, ky, data)
kx, ky, data = plot_tools.get_plane(dns_kspace_data, dns_image_axes[0],
dns_image_axes[1],
dns_image_slices)
dns_kx, dns_ky, dns_power = calc_dns_power(kx, ky, data)
kx0_axes.plot(dns_power[:, 0],
label='DNS t = {:5.2e}'.format(dns_time))
kx0_axes.plot(ce2_power[:, 0],
label='CE2 t = {:5.2e}'.format(ce2_time))
kx0_axes.set_xlabel(r"$k_{y}$")
kx0_axes.set_ylabel(power_axis_label)
#kx0_axes.set_xlim(1,15)
kx0_axes.text(0.9,
0.85,
'c',
bbox={
'facecolor': 'grey',
'alpha': 0.5,
'boxstyle': 'round'
},
transform=kx0_axes.transAxes,
fontsize=18,
color='black')
kx0_axes.xaxis.set_major_locator(MaxNLocator(integer=True))
kx0_axes.legend(loc='lower right')
outputdir = pathlib.Path(output)
for ext in ['png']: #,'pdf']:
outfilen = "power_spectra_dns_ce2_{}_field_{}_write_{:05d}.{}".format(
label, field, ce2_write, ext)
fig.savefig(str(outputdir / outfilen), dpi=400)
def main(filename, start, count, output="./img_snapshots", slice_type="side"):
"""Save plot of specified tasks for given range of analysis writes."""
filename = pathlib.Path(filename)
stem = filename.stem.split("_")[0]
if (slice_type == "top"):
nrows, ncols = 2,2
image_axes = [2, 3]
data_slices = [0, 0,slice(None), slice(None)]
tasks = ['Pressure(z=+1)', 'Ux(z=+1)', 'Uy(z=+1)']
elif (slice_type == "mid"):
nrows, ncols = 2,2
image_axes = [2, 3]
data_slices = [0, 0,slice(None), slice(None)]
tasks = ['W(z=+0.5)', 'T(z=+0.5)']
elif (slice_type == "side"):
nrows, ncols = 2,2
image_axes = [2, 1]
data_slices = [0, slice(None), slice(None),0]
tasks = ['Temperature(y=+1)', 'Pressure(y=+1)', 'Ox(y=+1)', 'Oz(y=+1)']
elif (slice_type == 'small'):
nrows, ncols = 2,2
image_axes = [2, 1]
data_slices = [0, slice(None), slice(None),0]
tasks = ['Temperature(y=+1)', 'Pressure(y=+1)', 'Oz(y=+1)']
else:
raise ValueError("must be side, mid or top slice. got {}".format(str(filename)))
# Plot settings
scale = 4
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: '{}_{:06}.png'.format(stem, write)
# Layout
image = plot_tools.Box(3, 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
data_slices[0] = index
plot_tools.plot_bot(dset, image_axes, data_slices, axes=axes, title=task, even_scale=True)
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
ce2_bias_data = h5py.File(ce2_bias_file, 'r')
ce2_image_axes = [0, 3]
if xy:
dns_image_axes = [0, 2]
dns_data_slices = (slice(None), 0, slice(None))
else:
dns_image_axes = [0, 1]
dns_data_slices = (slice(None), slice(None), 0)
ce2_data_slices = (slice(None), 0, 0, slice(None))
image_scales = ['sim_time', 0]
nrows, ncols = 1, 3
image = plot_tools.Box(2, 1)
pad = plot_tools.Frame(0.2, 0.1, 0.125, 0.125)
margin = plot_tools.Frame(0.1, 0.12, 0.1, 0.05)
y_ticks = (0.2, 0.4, 0.6, 0.8, 1.0)
scale = 2
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
axes = mfig.add_axes(0, 0, [0, 0, 1, 1])
# DNS
print("dns_data shape", dns_data['tasks/<u>_x'].shape)
print('ce2 data shape', ce2_data['tasks/cu'].shape)
pax, cax = plot_tools.plot_bot(dns_data['tasks/<u>_x'],
dns_image_axes,
def main(filename, start, count, output, write_start):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['ux', 'uz']
scale = 2.5
dpi = 300
# savename_func = lambda write: 'yubo_{:06}.png'.format(write+write_start)
def savename_func(suffix_num):
return 'yubo_{:06}'.format(suffix_num)
# Layout
nrows, ncols = 1, 2
image = plot_tools.Box(1, 2)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.15, 0.15, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as f:
for index in range(start, start + count):
paxes0 = None # use this to overplot text
for n, task in enumerate(tasks):
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = f['tasks'][task]
if n == 0: #ux
clim = [-1.3, 1.3]
title = r'$u_x / \overline{U}_c$'
func = lambda xmesh, ymesh, data: (xmesh, ymesh, data /
UX_C)
elif n == 1: #U
clim = [-0.1, 0.1]
title = r'$\Upsilon \equiv \ln (\rho / \overline{\rho})$'
func = None
paxes, _ = plot_tools.plot_bot_3d(dset,
0,
index,
axes=axes,
title=title,
even_scale=True,
clim=clim,
func=func)
if paxes0 is None:
paxes0 = paxes
# shade in forcing + damping zones
x = paxes.get_xlim()
plot_zbot, plot_ztop = paxes.get_ylim()
paxes.fill_between(x, [plot_zbot, plot_zbot], [Z_BOT, Z_BOT],
alpha=0.3,
color='grey')
paxes.fill_between(x, [Z_TOP, Z_TOP], [plot_ztop, plot_ztop],
alpha=0.3,
color='grey')
paxes.fill_between(x, [Z0 + 3 * SIGMA, Z0 + 3 * SIGMA],
[Z0 - 3 * SIGMA, Z0 - 3 * SIGMA],
alpha=0.5,
color='g')
# Add time annotation
sim_time = f['scales/sim_time'][index]
time_str = '$t=%.1f/N$' % sim_time
annotation = paxes0.text(0.1, 10.8, time_str, fontsize=14)
# regex parse out filename number, 10 writes per f
num_per_file = 10
write = f['scales/write_number'][index]
write_num = (write - 1) % num_per_file
filenum = int(re.match('.*s([\d]+)\.h5', filename)[1])
suffix_num = (filenum - 1) * num_per_file + write_num
if suffix_num > 201:
suffix_num -= 9 # hard coded, one of the restores is misnumbered
print(suffix_num)
# Save figure
savename = savename_func(suffix_num)
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
# if in PLOT_IDXS, change overplotted text and plot separately
try:
fig_idx = PLOT_IDXS.index(suffix_num)
annotation.remove()
print('Adding extra annotation', suffix_num)
overlay = '%s %s' % (PLOT_PREFIXES[fig_idx], time_str)
paxes0.text(0.1, 10.8, overlay, fontsize=14)
except ValueError:
# suffix_num not in PLOT_IDXS, continue
continue
fig.savefig(str(savepath) + '_labeled', dpi=dpi)
fig.clear()
plt.close(fig)
field = 'zeta'
climits = (-1, 7)
xlimits = (0, 63)
ylimits = (1, 63)
dns_tidx = -1
ce2_tidx = -1
label = None
dns_filename = "../scratch/busse_annulus_ra4.00e+07_beta3.16e+05_C3.16e-01_Pr1.00e+00_filter5.00e-01_nx512_ny128_CFL/snapshots/snapshots_s2.h5"
ce2_filename = "run_R_explicit_powerspec/data_snapshots/data_snapshots_s121.h5"
ce2_b_filename = "run_S_explicit_no_mean_subtr/data_snapshots/data_snapshots_s68.h5"
with h5py.File(dns_filename, 'r') as dns_data, h5py.File(
ce2_filename, 'r') as ce2_data, h5py.File(ce2_b_filename,
'r') as ce2_b_data:
nrows, ncols = 1, 3
image = plot_tools.Box(1, 1)
pad = plot_tools.Frame(0.2, 0.1, 0.1, 0.1)
margin = plot_tools.Frame(0.1, 0.1, 0.1, 0.1)
scale = 4
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
dns_axes = mfig.add_axes(0, 0, [0, 0, 1, 1])
if field == 'zeta':
power_axis_label = r"$\log_{10} |\hat{\zeta}|^2$"
elif field == 'theta':
power_axis_label = r"$\log_{10} |\hat{\theta}|^2$"
else:
raise NotImplementedError(
"Field can only be theta or zeta, not {}".format(field))
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['btot',
'btot_stat'] #for bouyancy in non-hydrostat and hydrostat cases
"""much of these settings are probably not needed, but I didn't want to break the code
by deleting them
"""
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 1, 1
image = plot_tools.Box(len(tasks), 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
'------------------------------------------------------'
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
time = np.zeros(0)
diff = np.zeros(0)
for index in range(start, start + count):
if index == 400: #for testing purposes
break
for n, task in enumerate(tasks):
if n == 0: #zoomed bouyancy on top, would like to plot contours aswell
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
ctour = plot_test.plot_bot_3d(
dset,
0,
index,
k=1,
axes=axes,
title='b in Pycnocline (Non-Hydrostat)',
even_scale=True,
clim=(3, 5)) #get contours for Fourier transform
# print(task)
if index != 0: #bypass first snapshot, since 1st is 0 for all variables
tour = ctour.collections[4].get_paths()[
0] #gets 4th contour
v = tour.vertices
if index == 1: #only need to do this once
Z = v[:, 1] #first set of z values in bouyancy
x = v[:, 0] #gets x values which are constant
if index > 1:
z = v[:, 1]
Z = np.vstack((Z, z)) #build array of z values
if index % 5 == 0: #just to know where it is at
print('n=', n, 'index=',
index) #nth variable, ith timestep
time = np.append(time, file['scales/sim_time'][index])
if len(time) >= 2:
difference = time[index - 1] - time[
index - 2] #time series interval
diff = np.append(diff, difference) #make an array
if n == 1: #zoomed bouyancy on top, would like to plot contours aswell
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
ctour = plot_test.plot_bot_3d(
dset,
0,
index,
k=1,
axes=axes,
title='b in Pycnocline (Non-Hydrostat)',
even_scale=True,
clim=(3, 5)) #get contours for Fourier transform
# print(task)
if index != 0: #bypass first snapshot, since 1st is 0 for all variables
tour = ctour.collections[4].get_paths()[
0] #now we are on 2nd etc snapshots
v = tour.vertices
if index == 1: #only need to do this once
Z_stat = v[:, 1]
if index > 1:
z_stat = v[:, 1]
Z_stat = np.vstack(
(Z_stat, z_stat)) #build array of z values
if index % 1 == 0: #just to know where it is at
print('n=', n, 'index=', index)
# plt.plot(x,z)
# plt.ylim(-0.15-1e-4, -0.15+1e-4)
# elif n == 2: #zoomed bouyancy on top
# # Build subfigure axes
# i, j = divmod(n, ncols)
# axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# # Call 3D plotting helper, slicing in time
# dset = file['tasks'][task]
# plot_test.plot_bot_3d(dset, 0, index, k=0, axes=axes, title='Change in b in Pycnocline ( Non-Hydrostat)',
# even_scale=True, clim=(-5e-5,5e-5))
# elif n == 3: #zoomed bouyancy on top
# # Build subfigure axes
# i, j = divmod(n, ncols)
# axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# # Call 3D plotting helper, slicing in time
# dset = file['tasks'][task]
# plot_test.plot_bot_3d(dset, 0, index, k=0, axes=axes, title='Change in b_stat in Pycnocline (Hydrostat)',
# even_scale=True, clim=(-5e-5,5e-5))
# Add time title
# title = title_func(file['scales/sim_time'][index])
# title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
# fig.suptitle(title, fontsize='large')#, x=0.48, y=title_height, ha='left')
# Save figure
# savename = savename_func(file['scales/write_number'][index])
# savepath = output.joinpath(savename)
# fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
##colour plot for x,t,z where z is the dependant variable, just used for testing
# X, T = np.meshgrid(x,time) #x,t mesh for z plot
# fig, (ax0, ax1) = plt.subplots(ncols=2, sharex=True, sharey=True) #2 plots
# im = ax0.pcolormesh(X, T, Z)
# ax0.set_title('Nonhydrostatic')
# ax0.set_ylabel('Time (s)')
#
# im = ax1.pcolormesh(X, T, Z_stat)
# ax1.set_title('Hydrostatic')
# ax0.set_xlabel('Horizontal Position (m)')
# colorbar(im) #to fit in colorbar
# plt.tight_layout(h_pad=1)
# plt.savefig('Colorbar_graph2')
# fig.clear()
# exit()
#Power Spectrum
#nonhydrostatic
Z = Z[30:, :] #delete first 30 rows, transients
Z_c = np.fft.fft(Z, axis=0) #coeff matrix
Z_p = np.abs(Z_c)**2 #power matrix
#hydrostatic
Z_stat = Z_stat[30:, :] #delete first n rows, transients
Z_c_stat = np.fft.fft(Z, axis=0) #coeff matrix
Z_p_stat = np.abs(Z_c)**2 #power matrix
n = Z.shape[0] #length of time axis
timestep = time[100] - time[99] #sampling interval, picked random interval
freq = np.fft.fftfreq(n, d=timestep) #frequency axis
X, w = np.meshgrid(x, freq)
fig, (ax0, ax1) = plt.subplots(ncols=2, sharex=True, sharey=True) #2 plots
im = ax0.pcolormesh(X, w, Z_p, vmin=1e-10, vmax=1e-8)
ax0.set_title('Nonhydrostatic')
ax0.set_ylabel('Freq (Hz)')
im = ax1.pcolormesh(X, w, Z_p_stat, vmin=0, vmax=1e-8)
ax1.set_title('Hydrostatic')
ax0.set_xlabel('Horizontal Position (m)')
colorbar(im) #to fit in colorbar
plt.tight_layout(h_pad=1)
plt.savefig('Powerspectrum_graph3')
print(np.std(diff[10:, ]) * 100 / diff[100]
) #looking at std dev time intervals as fraction of a later interval
print(len(time)) # look at number of time series
fig.clear()
def main(filename, start, count, output):
"""Save plot of specified tasks for given range of analysis writes."""
# Plot settings
tasks = ['u, 'v', 'b'] #for (change in) bouyancy in non-hydrostat and hydrostat cases
scale = 2.5
dpi = 100
title_func = lambda sim_time: 't = {:.3f}'.format(sim_time)
savename_func = lambda write: 'write_{:06}.png'.format(write)
# Layout
nrows, ncols = 2, 1 #no. of columns and rows corresponding to desired variables
image = plot_tools.Box(len(tasks), 1)
pad = plot_tools.Frame(0.2, 0.2, 0.1, 0.1)
margin = plot_tools.Frame(0.3, 0.2, 0.1, 0.1)
# Create multifigure
mfig = plot_tools.MultiFigure(nrows, ncols, image, pad, margin, scale)
fig = mfig.figure
# Plot writes
with h5py.File(filename, mode='r') as file:
for index in range(start, start+count):
for n, task in enumerate(tasks):
if n ==0: #zoomed bouyancy on top, would like to plot contours aswell
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_test.plot_bot_3d(dset, 0, index, k= 1, axes=axes, title='Horizontal Velocity u',
even_scale=True, clim=(-5e-4,5e-4))
if n == 1: #zoomed bouyancy on top, would like to plot contours aswell
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_test.plot_bot_3d(dset, 0, index, k=1, axes=axes, title='Vertical Velocity w',
even_scale=True, clim=(-5e-5,5e-5))
if n == 2: #zoomed bouyancy on top
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_test.plot_bot_3d(dset, 0, index, k=0, axes=axes, title='Change in Bouyancy b',
even_scale=True, clim=(-5e-4,5e-4))
if n == 3: #not currently in use
# Build subfigure axes
i, j = divmod(n, ncols)
axes = mfig.add_axes(i, j, [0, 0, 1, 1])
# Call 3D plotting helper, slicing in time
dset = file['tasks'][task]
plot_test.plot_bot_3d(dset, 0, index, k=0, axes=axes, title='Change in b_stat in Pycnocline (Hydrostat)',
even_scale=True, clim=(-5e2,5e2))
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, fontsize='large')#, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
