def _get_parallel_coordinate_plot(study: Study,
params: Optional[List[str]] = None
) -> "go.Figure":
layout = go.Layout(title="Parallel Coordinate Plot", )
trials = [
trial for trial in study.trials if trial.state == TrialState.COMPLETE
]
if len(trials) == 0:
logger.warning("Your study does not have any completed trials.")
return go.Figure(data=[], layout=layout)
all_params = {p_name for t in trials for p_name in t.params.keys()}
if params is not None:
for input_p_name in params:
if input_p_name not in all_params:
ValueError("Parameter {} does not exist in your study.".format(
input_p_name))
all_params = set(params)
sorted_params = sorted(list(all_params))
dims = [{
"label":
"Objective Value",
"values":
tuple([t.value for t in trials]),
"range":
(min([t.value for t in trials]), max([t.value for t in trials])),
}] # type: List[Dict[str, Any]]
for p_name in sorted_params:
values = []
for t in trials:
if p_name in t.params:
values.append(t.params[p_name])
is_categorical = False
try:
tuple(map(float, values))
except (TypeError, ValueError):
vocab = defaultdict(
lambda: len(vocab)) # type: DefaultDict[str, int]
values = [vocab[v] for v in values]
is_categorical = True
dim = {
"label":
p_name if len(p_name) < 20 else "{}...".format(p_name[:17]),
"values": tuple(values),
"range": (min(values), max(values)),
}
if is_categorical:
dim["tickvals"] = list(range(len(vocab)))
dim["ticktext"] = list(sorted(vocab.items(), key=lambda x: x[1]))
dims.append(dim)
traces = [
go.Parcoords(
dimensions=dims,
labelangle=30,
labelside="bottom",
line={
"color": dims[0]["values"],
"colorscale": "blues",
"colorbar": {
"title": "Objective Value"
},
"showscale": True,
"reversescale": study.direction == StudyDirection.MINIMIZE,
},
)
]
figure = go.Figure(data=traces, layout=layout)
return figure
def _get_parallel_coordinate_plot(study, params=None):
# type: (Study, Optional[List[str]]) -> go.Figure
layout = go.Layout(title='Parallel Coordinate Plot', )
trials = [
trial for trial in study.trials if trial.state == TrialState.COMPLETE
]
if len(trials) == 0:
logger.warning('Your study does not have any completed trials.')
return go.Figure(data=[], layout=layout)
all_params = {p_name for t in trials for p_name in t.params.keys()}
if params is not None:
for input_p_name in params:
if input_p_name not in all_params:
ValueError('Parameter {} does not exist in your study.'.format(
input_p_name))
all_params = set(params)
sorted_params = sorted(list(all_params))
dims = [{
'label':
'Objective Value',
'values':
tuple([t.value for t in trials]),
'range':
(min([t.value for t in trials]), max([t.value for t in trials]))
}] # type: List[Dict[str, Any]]
for p_name in sorted_params:
values = []
for t in trials:
if p_name in t.params:
values.append(t.params[p_name])
is_categorical = False
try:
tuple(map(float, values))
except (TypeError, ValueError):
vocab = defaultdict(
lambda: len(vocab)) # type: DefaultDict[str, int]
values = [vocab[v] for v in values]
is_categorical = True
dim = {
'label': p_name,
'values': tuple(values),
'range': (min(values), max(values))
}
if is_categorical:
dim['tickvals'] = list(range(len(vocab)))
dim['ticktext'] = list(sorted(vocab.items(), key=lambda x: x[1]))
dims.append(dim)
traces = [
go.Parcoords(dimensions=dims,
line={
'color':
dims[0]['values'],
'colorscale':
'blues',
'colorbar': {
'title': 'Objective Value'
},
'showscale':
True,
'reversescale':
study.direction == StudyDirection.MINIMIZE,
})
]
figure = go.Figure(data=traces, layout=layout)
return figure