def run_test_iof(f, main__file__, show=False):
mpl.clf()
fac_tot = 1e9 * f["fac_tot"]
plot_args = dict(projection="polar",
lin=[-300, 300],
bounding_lat=35.0,
drawcoastlines=True, # for basemap only
title="Total FAC\n",
gridec='gray',
label_lat=True,
label_mlt=True,
colorbar=dict(pad=0.1) # pad the colorbar away from the plot
)
ax1 = mpl.subplot(121, projection='polar')
mpl.plot(fac_tot, ax=ax1, hemisphere='north', **plot_args)
ax1.annotate('(a)', xy=(0, 0), textcoords="axes fraction",
xytext=(-0.1, 1.0), fontsize=18)
ax2 = mpl.subplot(122, projection='polar')
plot_args['gridec'] = False
mpl.plot(fac_tot, ax=ax2, hemisphere="south", style="contourf",
levels=50, extend="both", **plot_args)
ax2.annotate('(b)', xy=(0, 0), textcoords="axes fraction",
xytext=(-0.1, 1.0), fontsize=18)
mpl.auto_adjust_subplots(subplot_params=dict())
mpl.plt.gcf().set_size_inches(8, 4)
mpl.plt.savefig(next_plot_fname(main__file__))
if show:
mpl.mplshow()
def run_test_2d(f, main__file__, show=False):
mpl.clf()
slc = "x=-20f:12f, y=0f"
plot_kwargs = dict(title=True, earth=True)
mpl.subplot(141)
mpl.plot(f['pp'], slc, logscale=True, **plot_kwargs)
mpl.plot(np.abs(f['psi']), style='contour', logscale=True, levels=30,
linewidths=0.8, colors='grey', linestyles='solid', cbar=None,
x=(-20, 12))
mpl.subplot(142)
mpl.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
mpl.plot2d_quiver(f['v'][slc], step=5, color='y', pivot='mid', width=0.03,
scale=600)
mpl.subplot(143)
mpl.plot(f['jy'], slc, clim=[-0.005, 0.005], **plot_kwargs)
mpl.streamplot(f['v'][slc], linewidth=0.3)
mpl.subplot(144)
mpl.plot(f['jy'], "x=7f:12f, y=0f, z=0f")
mpl.plt.suptitle("2D File")
mpl.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
mpl.plt.gcf().set_size_inches(10, 4)
mpl.savefig(next_plot_fname(main__file__))
if show:
mpl.show()
def main():
f = viscid.load_file("~/dev/work/tmedium/*.3d.[-1].xdmf")
grid = f.get_grid()
gslc = "x=-26f:12.5f, y=-15f:15f, z=-15f:15f"
# gslc = "x=-12.5f:26f, y=-15f:15f, z=-15f:15f"
b_cc = f['b_cc'][gslc]
b_cc.name = "b_cc"
b_fc = f['b_fc'][gslc]
b_fc.name = "b_fc"
e_cc = f['e_cc'][gslc]
e_cc.name = "e_cc"
e_ec = f['e_ec'][gslc]
e_ec.name = "e_ec"
pp = f['pp'][gslc]
pp.name = 'pp'
pargs = dict(logscale=True, earth=True)
# mpl.clf()
# ax1 = mpl.subplot(211)
# mpl.plot(f['pp']['y=0f'], **pargs)
# # mpl.plot(viscid.magnitude(f['b_cc']['y=0f']), **pargs)
# # mpl.show()
# mpl.subplot(212, sharex=ax1, sharey=ax1)
# mpl.plot(viscid.magnitude(viscid.fc2cc(f['b_fc'])['y=0f']), **pargs)
# mpl.show()
basename = './tmediumR.3d.{0:06d}'.format(int(grid.time))
viscid.save_fields(basename + '.h5', [b_cc, b_fc, e_cc, e_ec, pp])
f2 = viscid.load_file(basename + ".xdmf")
pargs = dict(logscale=True, earth=True)
mpl.clf()
ax1 = mpl.subplot(211)
mpl.plot(f2['pp']['y=0f'], style='contour', levels=5, colorbar=None,
colors='k', **pargs)
mpl.plot(viscid.magnitude(f2['b_cc']['y=0f']), **pargs)
mpl.subplot(212, sharex=ax1, sharey=ax1)
mpl.plot(viscid.magnitude(viscid.fc2cc(f2['b_fc'])['y=0f']), **pargs)
mpl.show()
os.remove(basename + '.h5')
os.remove(basename + '.xdmf')
return 0
def run_test_timeseries(f, main__file__, show=False):
mpl.clf()
ntimes = f.nr_times()
t = [None] * ntimes
pressure = np.zeros((ntimes,), dtype='f4')
for i, grid in enumerate(f.iter_times()):
t[i] = grid.time_as_datetime()
pressure[i] = grid['pp']['x=10.0f, y=0.0f, z=0.0f']
mpl.plt.plot(t, pressure)
mpl.plt.ylabel('Pressure')
dateFmt = mdates.DateFormatter('%H:%M:%S')
mpl.plt.gca().xaxis.set_major_formatter(dateFmt)
mpl.plt.gcf().autofmt_xdate()
mpl.plt.gca().grid(True)
mpl.plt.gcf().set_size_inches(8, 4)
mpl.plt.savefig(next_plot_fname(main__file__))
if show:
mpl.mplshow()
def run_test_3d(f, main__file__, show=False):
mpl.clf()
slc = "x=-20f:12f, y=0f"
plot_kwargs = dict(title=True, earth=True)
mpl.subplot(141)
mpl.plot(f['pp'], slc, logscale=True, **plot_kwargs)
mpl.subplot(142)
mpl.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
mpl.plot2d_quiver(f['v'][slc], step=5, color='y', pivot='mid', width=0.03,
scale=600)
mpl.subplot(143)
mpl.plot(f['jy'], slc, clim=(-0.005, 0.005), **plot_kwargs)
mpl.streamplot(f['v'][slc], linewidth=0.3)
mpl.subplot(144)
mpl.plot(f['jy'], "x=7f:12f, y=0f, z=0f")
mpl.plt.suptitle("3D File")
mpl.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
mpl.plt.gcf().set_size_inches(10, 4)
mpl.savefig(next_plot_fname(main__file__))
if show:
mpl.show()
def benchmark_streamline(precompile=True, profile=True, scale=True, plot=True):
which = "streamline"
print(which)
print('-' * len(which))
f0, seeds = make_vector_fld()
print("Timing", which)
sl_kwargs = dict(ibound=3.7, ds0=0.020)
lines, _ = viscid.streamlines(f0, seeds, **sl_kwargs)
nsegs_cython = np.sum([line.shape[1] for line in lines])
lines = None
ft_stats, cy_stats = dict(), dict()
bench_output_type = viscid.OUTPUT_TOPOLOGY
sl_kwargs.update(output=bench_output_type)
retFT = viscid.timeit(fort_topology,
f0,
seeds,
timeit_repeat=6,
timeit_stats=ft_stats)
_, retCY = viscid.timeit(viscid.streamlines,
f0,
seeds,
timeit_repeat=6,
timeit_stats=cy_stats,
**sl_kwargs)
fort_per_seg = ft_stats['min'] / retFT.get_info('nsegs')
cy_per_seg = cy_stats['min'] / nsegs_cython
print("Segs Fortran", retFT.get_info('nsegs'))
print("Segs Cython ", nsegs_cython)
print("Fortran took {0:.3g} sec/seg".format(fort_per_seg))
print("Cython took {0:.3g} sec/seg".format(cy_per_seg))
print_seedup("Cython", cy_per_seg, "Fortran", fort_per_seg, prefix="@ ")
if plot:
from viscid.plot import mpl
mpl.clf()
mpl.subplot(121, projection='polar')
mpl.plot(retCY, hemisphere='north')
mpl.subplot(122, projection='polar')
mpl.plot(retCY, hemisphere='south')
mpl.show()
if scale:
thetas = np.logspace(np.log10(3), np.log10(144), 8).astype('i')
cy_nsegs = [None] * len(thetas)
fort_nsegs = [None] * len(thetas)
cy_mintime = [None] * len(thetas)
fort_mintime = [None] * len(thetas)
for i, ntheta in enumerate(thetas):
seeds = viscid.Sphere(r=10.0, ntheta=ntheta, nphi=32)
_stats = dict()
topo = viscid.timeit(fort_topology,
f0,
seeds,
timeit_repeat=5,
timeit_stats=_stats,
timeit_quiet=True)
fort_nsegs[i] = topo.get_info('nsegs')
fort_mintime[i] = _stats['min']
_, topo = viscid.timeit(viscid.calc_streamlines,
f0,
seeds,
ibound=3.7,
ds0=0.020,
output=bench_output_type,
timeit_repeat=5,
timeit_stats=_stats,
timeit_quiet=True)
lines, _ = viscid.streamlines(f0, seeds, ibound=3.7, ds0=0.020)
cy_nsegs[i] = np.sum([line.shape[1] for line in lines])
cy_mintime[i] = _stats['min']
from viscid.plot import mpl
mpl.clf()
mpl.plt.plot(cy_nsegs, cy_mintime, label="Cython")
mpl.plt.plot(fort_nsegs, fort_mintime, label="Fortran")
mpl.plt.legend(loc=0)
mpl.plt.xlabel('Number of segments calculated')
mpl.plt.ylabel('time to calculate')
mpl.show()
mpl.clf()
cy_tperseg = np.array(cy_mintime) / np.array(cy_nsegs)
fort_tperseg = np.array(fort_mintime) / np.array(fort_nsegs)
mpl.plt.plot(thetas, cy_tperseg / fort_tperseg, label="over cython")
mpl.plt.xlabel('ntheta')
mpl.plt.ylabel('Fortran Speedup')
mpl.show()
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# plot2d = True
# plot3d = True
# args.show = True
img = np.load(sample_dir + "/logo.npy")
x = np.linspace(-1, 1, img.shape[0])
y = np.linspace(-1, 1, img.shape[1])
z = np.linspace(-1, 1, img.shape[2])
logo = viscid.arrays2field(img, [x, y, z])
if 1:
viscid.logger.info('Testing Line...')
seeds = viscid.Line([-1, -1, 0], [1, 1, 2], n=5)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Plane...')
seeds = viscid.Plane([0.0, 0.0, 0.0], [1, 1, 1], [1, 0, 0], 2, 2,
nl=160, nm=170, NL_are_vectors=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Volume...')
seeds = viscid.Volume([-0.8, -0.8, -0.8], [0.8, 0.8, 0.8],
n=[64, 64, 3])
# note: can't make a 2d plot of the volume w/o a slice
run_test(logo, seeds, plot2d=False, plot3d=plot3d, add_title="3d",
show=args.show)
if 1:
viscid.logger.info('Testing Volume (with ignorable dim)...')
seeds = viscid.Volume([-0.8, -0.8, 0.0], [0.8, 0.8, 0.0],
n=[64, 64, 1])
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="2d",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (phi, theta)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (theta, phi)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (phi, theta)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (theta, phi)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Patch...')
seeds = viscid.SphericalPatch(p0=[0, 0, 0], p1=[0, -0, -1],
max_alpha=30.0, max_beta=59.9,
nalpha=65, nbeta=80, r=0.5, roll=45.0)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing RectilinearMeshPoints...')
f = viscid.load_file(sample_dir + '/sample_xdmf.3d.[-1].xdmf')
slc = 'x=-40f:12f, y=-10f:10f, z=-10f:10f'
b = f['b'][slc]
z = b.get_crd('z')
sheet_iz = np.argmin(b['x']**2, axis=2)
sheet_pts = b['z=0:1'].get_points()
sheet_pts[2, :] = z[sheet_iz].reshape(-1)
isphere_mask = np.sum(sheet_pts[:2, :]**2, axis=0) < 5**2
day_mask = sheet_pts[0:1, :] > -1.0
sheet_pts[2, :] = np.choose(isphere_mask, [sheet_pts[2, :], 0])
sheet_pts[2, :] = np.choose(day_mask, [sheet_pts[2, :], 0])
nx, ny, _ = b.sshape
sheet_seed = viscid.RectilinearMeshPoints(sheet_pts.reshape(3, nx, ny))
vx_sheet = viscid.interp_nearest(f['vx'], sheet_seed)
try:
if not plot2d:
raise ImportError
from viscid.plot import mpl
mpl.clf()
mpl.plot(vx_sheet, symmetric=True)
mpl.plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
mpl.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import mvi
mvi.clf()
mesh = mvi.mesh_from_seeds(sheet_seed, scalars=vx_sheet,
clim=(-400, 400))
mvi.plot_earth_3d(crd_system=b)
mvi.view(azimuth=+90.0 + 45.0, elevation=90.0 - 25.0,
distance=30.0, focalpoint=(-10.0, +1.0, +1.0))
mvi.title("RectilinearMeshPoints")
mvi.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
mvi.show()
except ImportError:
pass
return 0
def _get_sep_pts_bisect(
fld,
seed,
trace_opts=None,
min_depth=3,
max_depth=7,
plot=False,
perimeter_check=perimeter_check_bitwise_or,
make_3d=True,
start_uneven=False,
_base_quadrent="",
_uneven_mask=0,
_first_recurse=True,
):
if len(_base_quadrent) == max_depth:
return [_base_quadrent] # causes pylint to complain
if trace_opts is None:
trace_opts = dict()
nx, ny = seed.uv_shape
(xlim, ylim) = seed.uv_extent
if _first_recurse and start_uneven:
_uneven_mask = UNEVEN_MASK
if _first_recurse and plot:
from viscid.plot import mvi
from viscid.plot import mpl
mpl.clf()
_, all_topo = viscid.calc_streamlines(fld, seed, **trace_opts)
mpl.plot(np.bitwise_and(all_topo, 15), show=False)
verts, arr = seed.wrap_mesh(all_topo.data)
mvi.mesh(verts[0], verts[1], verts[2], scalars=arr, opacity=0.75)
# quadrents and lines are indexed as follows...
# directions are counter clackwise around the quadrent with
# lower index (which matters for lines which are shared among
# more than one quadrent, aka, lines 1,2,6,7). Notice that even
# numbered lines are horizontal, like the interstate system :)
# -<--10-----<-8---
# | ^ ^
# 11 2 9 3 7
# \/ | |
# --<-2-----<-6----
# | ^ ^
# 3 0 1 1 5
# \/ | |
# ----0->-----4->--
# find low(left), mid(center), and high(right) crds in x and y
low_quad = "{0}{1:x}".format(_base_quadrent, 0 | _uneven_mask)
high_quad = "{0}{1:x}".format(_base_quadrent, 3 | _uneven_mask)
xl, xm, yl, ym = _quadrent_limits(low_quad, xlim, ylim)
_, xh, _, yh = _quadrent_limits(high_quad, xlim, ylim)
segsx, segsy = [None] * 12, [None] * 12
topo = [None] * 12
nxm, nym = nx // 2, ny // 2
# make all the line segments
segsx[0], segsy[0] = np.linspace(xl, xm, nxm), np.linspace(yl, yl, nxm)
segsx[1], segsy[1] = np.linspace(xm, xm, nym), np.linspace(yl, ym, nym)
segsx[2], segsy[2] = np.linspace(xm, xl, nxm), np.linspace(ym, ym, nxm)
segsx[3], segsy[3] = np.linspace(xl, xl, nym), np.linspace(ym, yl, nym)
segsx[4], segsy[4] = np.linspace(xm, xh, nxm), np.linspace(yl, yl, nxm)
segsx[5], segsy[5] = np.linspace(xh, xh, nym), np.linspace(yl, ym, nym)
segsx[6], segsy[6] = np.linspace(xh, xm, nxm), np.linspace(ym, ym, nxm)
segsx[7], segsy[7] = np.linspace(xh, xh, nym), np.linspace(ym, yh, nym)
segsx[8], segsy[8] = np.linspace(xh, xm, nxm), np.linspace(yh, yh, nxm)
segsx[9], segsy[9] = np.linspace(xm, xm, nym), np.linspace(ym, yh, nym)
segsx[10], segsy[10] = np.linspace(xm, xl, nxm), np.linspace(yh, yh, nxm)
segsx[11], segsy[11] = np.linspace(xl, xl, nym), np.linspace(yh, ym, nym)
allx = np.concatenate(segsx)
ally = np.concatenate(segsy)
# print("plot::", _base_quadrent, '|', _uneven_mask, '|', len(allx), len(ally))
pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
_, all_topo = viscid.calc_streamlines(fld, pts3d, **trace_opts)
topo[0] = all_topo[: len(segsx[0])]
cnt = len(topo[0])
for i, segx in zip(count(1), segsx[1:]):
topo[i] = all_topo[cnt : cnt + len(segx)]
# print("??", i, cnt, cnt + len(segx), np.bitwise_and.reduce(topo[i]))
cnt += len(topo[i])
# assemble the lines into the four quadrents
quad_topo = [None] * 4
# all arrays snip off the last element since those are
# duplicated by the next line... reversed arrays do the
# snipping with -1:0:-1
quad_topo[0] = np.concatenate([topo[0][:-1], topo[1][:-1], topo[2][:-1], topo[3][:-1]])
quad_topo[1] = np.concatenate([topo[4][:-1], topo[5][:-1], topo[6][:-1], topo[1][-1:0:-1]])
quad_topo[2] = np.concatenate([topo[2][-1:0:-1], topo[9][:-1], topo[10][:-1], topo[11][:-1]])
quad_topo[3] = np.concatenate([topo[6][-1:0:-1], topo[7][:-1], topo[8][:-1], topo[9][-1:0:-1]])
# now that the quad arrays are populated, decide which quadrents
# still contain the separator (could be > 1)
required_uneven_subquads = False
ret = []
for i in range(4):
if perimeter_check(quad_topo[i]):
next_quad = "{0}{1:x}".format(_base_quadrent, i | _uneven_mask)
subquads = _get_sep_pts_bisect(
fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=next_quad,
_uneven_mask=0,
_first_recurse=False,
)
ret += subquads
if len(ret) == 0:
perimeter = np.concatenate(
[
topo[0][::-1],
topo[4][::-1],
topo[5][::-1],
topo[7][::-1],
topo[8][::-1],
topo[10][::-1],
topo[11][::-1],
topo[3][::-1],
]
)
if _uneven_mask:
if len(_base_quadrent) > min_depth:
print("sep trace issue, but min depth reached: {0} > {1}" "".format(len(_base_quadrent), min_depth))
ret = [_base_quadrent]
else:
print("sep trace issue, the separator ended prematurely")
elif perimeter_check(perimeter):
ret = _get_sep_pts_bisect(
fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=_base_quadrent,
_uneven_mask=UNEVEN_MASK,
_first_recurse=False,
)
required_uneven_subquads = True
if plot and not required_uneven_subquads:
from viscid.plot import mvi
from viscid.plot import mpl
_pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
mvi.points3d(_pts3d[0], _pts3d[1], _pts3d[2], all_topo.data.reshape(-1), scale_mode="none", scale_factor=0.02)
mpl.plt.scatter(
allx, ally, color=np.bitwise_and(all_topo, 15), vmin=0, vmax=15, marker="o", edgecolor="y", s=40
)
if _first_recurse:
# turn quadrent strings into locations
xc = np.empty(len(ret))
yc = np.empty(len(ret))
for i, r in enumerate(ret):
xc[i], yc[i] = _quadrent_center(r, xlim, ylim)
pts_uv = np.array([xc, yc])
if plot:
from viscid.plot import mvi
from viscid.plot import mpl
mpl.plt.plot(pts_uv[0], pts_uv[1], "y*", ms=20, markeredgecolor="k", markeredgewidth=1.0)
mpl.show(block=False)
mvi.show(stop=True)
# return seed.to_3d(seed.uv_to_local(pts_uv))
# if pts_uv.size == 0:
# return None
if make_3d:
return seed.uv_to_3d(pts_uv)
else:
return pts_uv
else:
return ret
def topology_bitor_clusters(
fld,
min_depth=1,
max_depth=10,
multiple=True,
plot=False,
sep_val=streamline.TOPOLOGY_MS_SEPARATOR,
mask_limit=0b1111,
periodic="00",
pt_bnds=(),
):
"""Find separator as intersection of all global topologies
Neighbors are bitwise ORed until at least one value matches
`sep_val` which is presumably (Close | Open N | Open S | SW).
This happens between min_depth and max_depth times,
where the resolution of each iteration is reduced by a factor
of two, ie, worst case 2**(max_depth).
Args:
fld (Field): Topology (bitmask) as a field
min_depth (int): Iterate at least this many times
max_depth (int): Iterate at most this many times
multiple (bool): passed to :py:func:`viscid.cluster`
sep_val (int): Value of bitmask that indicates a separator
plot (bool): Make a 2D plot of Fld and the sep candidates
mask_limit (int): if > 0, then bitmask fld with mask_limit,
i.e., fld = fld & mask_limit (bitwise and)
periodic (sequence): indicate whether that direction is
periodic, and if so, whether the coordinate arrays are
overlapped or not. Values can be True, False, or '+'. '+'
indicates that x[0] and x[-1] are not colocated, so assume
they're dx apart where dx = x[-1] - x[-2].
pt_bnd (sequence): Boundaries that come to a point, i.e., all
values along that boundary are neighbors such as the poles
of a sphere. Specified like "0-" for lower boundary of
dimension 0 or "1+" for the upper boundary of dimension 1.
Returns:
ndarray: 2xN for N clusters of separator points in the same
coordinates as `fld`
"""
pd = [False if pi == "0" else bool(pi) for pi in periodic]
fld = fld.slice_reduce(":")
if mask_limit:
fld = np.bitwise_and(fld, mask_limit)
a = fld.data
x, y = fld.get_crds()
for i in range(max_depth):
if pd[0]:
a[(0, -1), :] |= a[(-1, 0), :]
if pd[1]:
a[:, (0, -1)] |= a[:, (-1, 0)]
a = (
a[:-1, :-1] | a[:-1, 1:] | a[1:, :-1] | a[1:, 1:] # pylint: disable=bad-whitespace
) # pylint: disable=bad-whitespace
x = 0.5 * (x[1:] + x[:-1])
y = 0.5 * (y[1:] + y[:-1])
# bitwise_or an entire bounary if all points are neighbors, like
# at the poles of a sphere
for bnd in pt_bnds:
slc = [slice(None), slice(None)]
slc[int(bnd[0])] = -1 if bnd[1] == "+" else 0
a[slc] = np.bitwise_or.reduce(a[slc])
indx, indy = np.where(a == sep_val)
if i + 1 >= min_depth and len(indx):
break
pts = viscid.cluster(indx, indy, x, y, multiple=multiple, periodic=periodic)
if plot:
from viscid.plot import mpl
mpl.clf()
ax0 = mpl.subplot(121)
mpl.plot(fld, title=True)
mpl.subplot(122, sharex=ax0, sharey=ax0)
or_fld = viscid.arrays2field(a, (x, y), name="OR")
mpl.plot(or_fld, title=True)
_x, _y = or_fld.get_crds()
mpl.plt.plot(_x[indx], _y[indy], "ko")
mpl.plt.plot(pts[0], pts[1], "y^")
mpl.plt.show()
return pts
def benchmark_streamline(precompile=True, profile=True, scale=True, plot=True):
which = "streamline"
print(which)
print('-' * len(which))
f0, seeds = make_vector_fld()
print("Timing", which)
sl_kwargs = dict(ibound=3.7, ds0=0.020)
lines, _ = viscid.streamlines(f0, seeds, **sl_kwargs)
nsegs_cython = np.sum([line.shape[1] for line in lines])
lines = None
ft_stats, cy_stats = dict(), dict()
bench_output_type = viscid.OUTPUT_TOPOLOGY
sl_kwargs.update(output=bench_output_type)
retFT = viscid.timeit(fort_topology, f0, seeds, timeit_repeat=6,
timeit_stats=ft_stats)
_, retCY = viscid.timeit(viscid.streamlines, f0, seeds, timeit_repeat=6,
timeit_stats=cy_stats, **sl_kwargs)
fort_per_seg = ft_stats['min'] / retFT.get_info('nsegs')
cy_per_seg = cy_stats['min'] / nsegs_cython
print("Segs Fortran", retFT.get_info('nsegs'))
print("Segs Cython ", nsegs_cython)
print("Fortran took {0:.3g} sec/seg".format(fort_per_seg))
print("Cython took {0:.3g} sec/seg".format(cy_per_seg))
print_seedup("Cython", cy_per_seg, "Fortran", fort_per_seg, prefix="@ ")
if plot:
from viscid.plot import mpl
mpl.clf()
mpl.subplot(121, projection='polar')
mpl.plot(retCY, hemisphere='north')
mpl.subplot(122, projection='polar')
mpl.plot(retCY, hemisphere='south')
mpl.show()
if scale:
thetas = np.logspace(np.log10(3), np.log10(144), 8).astype('i')
cy_nsegs = [None] * len(thetas)
fort_nsegs = [None] * len(thetas)
cy_mintime = [None] * len(thetas)
fort_mintime = [None] * len(thetas)
for i, ntheta in enumerate(thetas):
seeds = viscid.Sphere(r=10.0, ntheta=ntheta, nphi=32)
_stats = dict()
topo = viscid.timeit(fort_topology, f0, seeds, timeit_repeat=5,
timeit_stats=_stats, timeit_quiet=True)
fort_nsegs[i] = topo.get_info('nsegs')
fort_mintime[i] = _stats['min']
_, topo = viscid.timeit(viscid.calc_streamlines, f0, seeds,
ibound=3.7, ds0=0.020, output=bench_output_type,
timeit_repeat=5, timeit_stats=_stats,
timeit_quiet=True)
lines, _ = viscid.streamlines(f0, seeds, ibound=3.7, ds0=0.020)
cy_nsegs[i] = np.sum([line.shape[1] for line in lines])
cy_mintime[i] = _stats['min']
from viscid.plot import mpl
mpl.clf()
mpl.plt.plot(cy_nsegs, cy_mintime, label="Cython")
mpl.plt.plot(fort_nsegs, fort_mintime, label="Fortran")
mpl.plt.legend(loc=0)
mpl.plt.xlabel('Number of segments calculated')
mpl.plt.ylabel('time to calculate')
mpl.show()
mpl.clf()
cy_tperseg = np.array(cy_mintime) / np.array(cy_nsegs)
fort_tperseg = np.array(fort_mintime) / np.array(fort_nsegs)
mpl.plt.plot(thetas, cy_tperseg / fort_tperseg, label="over cython")
mpl.plt.xlabel('ntheta')
mpl.plt.ylabel('Fortran Speedup')
mpl.show()
