def _figure_data(self, plot, fmt, as_script=False, **kwargs):
if fmt == 'gif':
import plotly.io as pio
from PIL import Image
from plotly.io.orca import ensure_server, shutdown_server, status
running = status.state == 'running'
if not running:
ensure_server()
nframes = len(plot)
frames = []
for i in range(nframes):
plot.update(i)
img_bytes = BytesIO()
figure = go.Figure(self.get_plot_state(plot))
img = pio.to_image(figure, 'png', validate=False)
img_bytes.write(img)
frames.append(Image.open(img_bytes))
if not running:
shutdown_server()
bio = BytesIO()
duration = (1. / self.fps) * 1000
frames[0].save(bio,
format='GIF',
append_images=frames[1:],
save_all=True,
duration=duration,
loop=0)
bio.seek(0)
data = bio.read()
elif fmt in ('png', 'svg'):
import plotly.io as pio
# Wrapping plot.state in go.Figure here performs validation
# and applies any default theme.
figure = go.Figure(self.get_plot_state(plot))
data = pio.to_image(figure, fmt)
if fmt == 'svg':
data = data.decode('utf-8')
else:
raise ValueError("Unsupported format: {fmt}".format(fmt=fmt))
if as_script:
b64 = base64.b64encode(data).decode("utf-8")
(mime_type, tag) = MIME_TYPES[fmt], HTML_TAGS[fmt]
src = HTML_TAGS['base64'].format(mime_type=mime_type, b64=b64)
div = tag.format(src=src, mime_type=mime_type, css='')
return div
return data
def __run_exp(d,
cfgs,
prog_list,
pid,
cfgs_keys,
q,
WRITE_FREQ=10,
overwrite=True):
df = pd.DataFrame(index=range(WRITE_FREQ),
columns=list(cfgs_keys).extend(["acc", "elapsed_time"]))
def check_mem():
# gives an object with many fields
vm = psutil.virtual_memory()
return (vm.percent)
def pack_affmat_str(i):
#Extract info related to affmat
affmat_keys = []
affmat_vals = []
for k, v in cfgs[i].items():
if k.startswith("aff_") or k == "dataset":
affmat_keys.append(k)
affmat_vals.append(v)
affmat_keys, affmat_vals = (list(t) for t in zip(
*sorted(zip(affmat_keys, affmat_vals))))
affmat_str = ""
#Create string identiiiifying this affmat config
for i in range(len(affmat_keys)):
affmat_str = affmat_str + affmat_keys[i] + "=" + str(
affmat_vals[i]) + ";"
return (affmat_str)
print("Process Number:{}".format(pid))
count = 0
for i in range(len(cfgs)):
# disable output
nullwrite = open(os.devnull, 'w')
oldstdout = sys.stdout
if not DEBUG_MODE:
sys.stdout = nullwrite
#Get affmat string to index into affmat dict
affmat_str = pack_affmat_str(i)
#Update dataframe
for k, v in cfgs[i].items():
df.loc[i % WRITE_FREQ, k] = v
#Create GSSL object
gssl_obj = GraphSSL(cfgs[i])
#Get Affinity Matrix
if DISABLE_MATRIX_DICT:
W = gssl_obj.getAffMatrix()
else:
W = d.get(affmat_str, None)
if W is None:
W = gssl_obj.getAffMatrix()
d[affmat_str] = W
count += 1
#Run algorithm
res = gssl_obj.train(W)
if orca.status.state == "running":
orca.shutdown_server()
del gssl_obj
df.loc[i % WRITE_FREQ, "acc"] = res["acc"]
df.loc[i % WRITE_FREQ, "elapsed_time"] = res["elapsed_time"]
#Update results dict
if i % WRITE_FREQ == (WRITE_FREQ - 1) or i == (len(cfgs) - 1):
result_path = './results/' + OUTPUT_NAME + '_pid=' + str(
pid) + '.csv'
f_exists = os.path.isfile(result_path)
f_mode = "a"
if (f_exists and overwrite
and i == WRITE_FREQ - 1) or (not f_exists
and i == WRITE_FREQ - 1):
f_mode = "w"
with open(result_path, f_mode) as f:
is_header = (f_mode == "w")
df.iloc[0:((i % WRITE_FREQ) + 1), :].to_csv(f,
header=is_header)
df.iloc[0:((i % WRITE_FREQ) + 1), :] = np.nan
#Update progress list
prog_list[pid] = i / len(cfgs)
sys.stdout = oldstdout
#Enable output
q.put(1)