def run_reneg():
v = VPICReader(sys.argv[1])
n = v.get_num_ranks()
print("Ranks: ", n)
global TSIDX
TSIDX = int(sys.argv[2])
print("TS: ", v.get_ts(TSIDX))
global all_loads
all_loads = [0] * 32
read_into_global(v)
gen_anim_frames()
gen_hist(0.01)
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
ax1.clear()
#animate(v, ax1, len(anim_frames) - 1)
# ani = animation.FuncAnimation(fig, lambda x: animate_reneg(
# v, ax1, x), interval=10, frames=len(anim_frames))
animate_reneg(v, ax1, len(anim_frames) - 1)
plt.show()
def run():
v = VPICReader(sys.argv[1])
n = v.get_num_ranks()
print("Ranks: ", n)
global TSIDX
TSIDX = int(sys.argv[2])
read_into_global(v)
gen_anim_frames()
gen_hist(1.0)
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
ax1.clear()
#animate(v, ax1, len(anim_frames) - 1)
ani = animation.FuncAnimation(fig,
lambda x: animate(v, ax1, x),
interval=10,
frames=len(anim_frames))
#plt.show()
fname = 'vis/loadbalance.finbins.%s.512samples.gif' % (v.get_ts(TSIDX))
print(fname)
ani.save(fname, writer='imagemagick', fps=30, dpi=200)
def generate_distribution_violin(data_path: str, num_ranks: int,
timesteps: int, bw_value: float):
num_ranks = 2
vpic_reader = VPICReader(data_path, num_ranks=num_ranks)
fig = go.Figure()
for tsidx in range(0, timesteps):
data = vpic_reader.read_global(tsidx)
print(len(data))
# plotted_data = np.random.choice(data, 50000)
plotted_data = np.random.choice(data, 500)
head_cutoff = 0.5
head_cutoff_2 = 4
tail_cutoff = 10
head_data = len([i for i in plotted_data if i < head_cutoff])
head_data_2 = len([i for i in plotted_data if i < head_cutoff_2])
tail_data = len([i for i in plotted_data if i > tail_cutoff])
percent_head = head_data * 100.0 / len(plotted_data)
percent_head_2 = head_data_2 * 100.0 / len(plotted_data)
percent_tail = tail_data * 100.0 / len(plotted_data)
print('TS {0}, < {1}: {2:.2f}'.format(tsidx, head_cutoff,
percent_head))
print('TS {0}, < {1}: {2:.2f}'.format(tsidx, head_cutoff_2,
percent_head_2))
print('TS {0}, > {1}: {2:.2f}'.format(tsidx, tail_cutoff,
percent_tail))
plotted_data = list(map(lambda x: log_tailed(x, 10), plotted_data))
ts_name = 'Timestep {0}'.format(vpic_reader.get_ts(tsidx), )
violin_data = go.Violin(y=plotted_data,
box_visible=False,
meanline_visible=False,
name=ts_name,
side='positive',
points=False,
bandwidth=bw_value,
scalemode='width',
line=dict(width=1))
fig.add_trace(violin_data)
fig.update_traces(width=1.8)
fig.update_layout(
title_text='Energy distribution from 4 timesteps of a VPIC simulation'
' (tail is logarithmic)',
yaxis=dict(tickmode='array',
tickvals=list(range(0, 18, 2)),
ticktext=[
'{0:.0f}'.format(log_tailed_reverse(x, 10))
for x in range(0, 18, 2)
]),
)
fig.show()
def generate_distribution_box(data_path: str, num_ranks: int, timesteps: int):
# num_ranks = 4
vpic_reader = VPICReader(data_path, num_ranks=num_ranks)
fig = go.Figure()
for tsidx in range(0, timesteps):
data = vpic_reader.read_global(tsidx)
print(len(data))
plotted_data = np.random.choice(data, 50000)
head_cutoff = 2
tail_cutoff = 10
head_data = len([i for i in plotted_data if i < head_cutoff])
tail_data = len([i for i in plotted_data if i > tail_cutoff])
percent_head = head_data * 100.0 / len(plotted_data)
percent_tail = tail_data * 100.0 / len(plotted_data)
print('TS {0}, < {1}: {2:.2f}'.format(tsidx, head_cutoff,
percent_head))
print('TS {0}, > {1}: {2:.2f}'.format(tsidx, tail_cutoff,
percent_tail))
plotted_data = list(map(lambda x: log_tailed(x, 10), plotted_data))
ts_name = 'Timestep {0}'.format(vpic_reader.get_ts(tsidx), )
box_data = go.Box(y=plotted_data,
name=ts_name,
line_width=1,
marker=dict(size=4, line=dict(width=0)))
fig.add_trace(box_data)
fig.update_layout(
title_text='Energy distribution from 4 timesteps of a VPIC simulation'
' (tail is logarithmic)',
yaxis=dict(tickmode='array',
tickvals=list(range(0, 18, 2)),
ticktext=[
'{0:.0f}'.format(log_tailed_reverse(x, 10))
for x in range(0, 18, 2)
]),
)
# fig.show()
fig.write_image('../vis/poster/vpic32.distrib.box.pdf')
class TestVPICReader(unittest.TestCase):
def setUp(self):
self.vpicReader = VPICReader('.')
self.assertEqual(self.vpicReader.get_num_ranks(), 32)
return
def teardown(self):
return
def plot_hist_4():
v = VPICReader(sys.argv[1])
n = v.get_num_ranks()
print("Ranks: ", n)
fig, axes = plt.subplots(2, 2)
for row in range(2):
for col in range(2):
plot_simple_hist(v, axes[row][col], row * 2 + col)
# break
# break
plt.ylim([0, 0.5])
plt.tight_layout()
# plt.show()
plt.savefig("vis/ASCR/vpic_distrib.pdf")
return
def test_2_rank_pivots(self):
vpicReader = VPICReader('.')
rank = Rank(vpicReader, 2)
rank.insert(range(20))
pivots, pivot_width = rank.compute_pivots(5)
self.assertEqual(pivots, [0, 5, 10, 15, 19])
self.assertAlmostEqual(pivot_width, 5.0)
return
def test_1_insert_init(self):
self.vpicReader = VPICReader('.')
self.rank = Rank(self.vpicReader, 2)
self.rank.insert(range(20))
self.assertEqual(len(self.rank.oob_left), 20,
msg="init insertion not okay")
self.assertEqual(len(self.rank.oob_right), 0,
msg="init insertion not okay")
self.assertIsNone(self.rank.pivots)
self.assertIsNone(self.rank.pivot_counts)
def _test_num_pivots(self, num_pivots):
vpic_reader = VPICReader('../data')
reneg = Renegotiation(32, 0, vpic_reader)
reneg.set_NUM_PIVOTS(num_pivots)
reneg.read_all()
reneg.insert(0.05)
reneg.plot()
del vpic_reader
del reneg
vpic_reader = None
reneg = None
def setUp(self):
self.vpicReader = VPICReader('.')
self.assertEqual(self.vpicReader.get_num_ranks(), 32)
return
def run():
vpicReader = VPICReader(data_path)
rank0 = Rank(vpicReader, 0)
print(rank0.get_id())
rank0.read(0)
def generate_distribution_violin_alt(data_path: str,
fig_path: str,
num_ranks: int = None,
bw_value: float = 0.03):
# num_ranks = 4
vpic_reader = VPICReader(data_path, num_ranks=num_ranks)
ranks = vpic_reader.get_num_ranks()
timesteps = vpic_reader.get_num_ts()
print('[VPICReader] Ranks: {0}, ts: {1}'.format(ranks, timesteps))
fig = go.Figure()
all_shapes = []
all_annotations = []
timestamps = [
vpic_reader.get_ts(i) for i in range(vpic_reader.get_num_ts())
]
for tsidx in range(0, timesteps):
data = vpic_reader.sample_global(tsidx)
print('Read: ', len(data))
plotted_data = data
head_cutoff = 0.5
head_cutoff_2 = 4
tail_cutoff = 10
head_data = len([i for i in plotted_data if i < head_cutoff])
head_data_2 = len([i for i in plotted_data if i < head_cutoff_2])
tail_data = len([i for i in plotted_data if i > tail_cutoff])
percent_head = head_data * 100.0 / len(plotted_data)
percent_head_2 = head_data_2 * 100.0 / len(plotted_data)
percent_tail = tail_data * 100.0 / len(plotted_data)
print('TS {0}, < {1}: {2:.2f}'.format(tsidx, head_cutoff,
percent_head))
print('TS {0}, < {1}: {2:.2f}'.format(tsidx, head_cutoff_2,
percent_head_2))
print('TS {0}, > {1}: {2:.2f}'.format(tsidx, tail_cutoff,
percent_tail))
plotted_data = list(map(lambda x: log_tailed(x, 10), plotted_data))
ts_name = 'Timestep {0}'.format(vpic_reader.get_ts(tsidx), )
violin_data = go.Violin(y=plotted_data,
box_visible=False,
meanline_visible=False,
name=ts_name,
side='positive',
points=False,
bandwidth=bw_value,
scalemode='width',
line=dict(width=1))
fig.add_trace(violin_data)
label = 'Tail Mass: <br /> {0:.1f}%'.format(100 - percent_head_2)
print(label)
gen_annotation(all_shapes, all_annotations, label, tsidx + 0.1, 4,
max(plotted_data))
fig.update_traces(width=1.8)
fig.update_layout(xaxis=dict(
title=dict(text="Simulation Time (s)", ),
ticktext=timestamps,
tickvals=[x + 0.2 for x in range(timesteps)],
color='#000',
linecolor='#444',
),
yaxis=dict(title=dict(text='Particle Energy (eV)', ),
tickmode='array',
tickvals=list(range(0, 18, 2)),
ticktext=[
'{0:.0f}'.format(log_tailed_reverse(
x, 10)) for x in range(0, 18, 2)
],
linecolor='#444',
showgrid=True,
gridcolor='#ddd'),
plot_bgcolor='#fff',
shapes=all_shapes,
annotations=all_annotations,
showlegend=False,
legend=dict(x=0.87, y=1),
font=dict(size=18))
# fig.show()
# fig.write_image(
# '../vis/poster/vpic32.distrib.violin.alt.{0}.pdf'.format(bw_value))
fig.write_image(fig_path)