)
# boxplot
X = np.random.rand(100, 2)
X[:, 1] += 2
viz.boxplot(
X=X,
opts=dict(legend=['Men', 'Women'])
)
# stemplot
Y = np.linspace(0, 2 * math.pi, 70)
X = np.column_stack((np.sin(Y), np.cos(Y)))
viz.stem(
X=X,
Y=Y,
opts=dict(legend=['Sine', 'Cosine'])
)
# pie chart
X = np.asarray([19, 26, 55])
viz.pie(
X=X,
opts=dict(legend=['Residential', 'Non-Residential', 'Utility'])
)
# mesh plot
x = [0, 0, 1, 1, 0, 0, 1, 1]
y = [0, 1, 1, 0, 0, 1, 1, 0]
z = [0, 0, 0, 0, 1, 1, 1, 1]
X = np.c_[x, y, z]
win=win,
opts=dict(
width=300,
height=300,
),
)
# boxplot
X = np.random.rand(100, 2)
X[:, 1] += 2
viz.boxplot(X=X, opts=dict(legend=['Men', 'Women']))
# stemplot
Y = np.linspace(0, 2 * math.pi, 70)
X = np.column_stack((np.sin(Y), np.cos(Y)))
viz.stem(X=X, Y=Y, opts=dict(legend=['Sine', 'Cosine']))
# quiver plot
X = np.arange(0, 2.1, .2)
Y = np.arange(0, 2.1, .2)
X = np.broadcast_to(np.expand_dims(X, axis=1), (len(X), len(X)))
Y = np.broadcast_to(np.expand_dims(Y, axis=0), (len(Y), len(Y)))
U = np.multiply(np.cos(X), Y)
V = np.multiply(np.sin(X), Y)
viz.quiver(
X=U,
Y=V,
opts=dict(normalize=0.9),
)
# pie chart
class VisdomPlotter(object):
"""Plots to Visdom"""
def __init__(self, server, env_name='main', port=8097):
self.viz = Visdom(server, port=port)
self.env = env_name
self.plots = {}
def plot(self, ylabel, xlabel, legend, title_name, x, y, markers=False):
if title_name not in self.plots.keys():
self.plots[title_name] = self.viz.line(X=np.array([x, x]),
Y=np.array([y, y]),
env=self.env,
opts=dict(
legend=[legend],
title=title_name,
xlabel=xlabel,
ylabel=ylabel,
markers=markers,
markersymbol='plus'))
else:
self.viz.line(X=np.array([x]),
Y=np.array([y]),
env=self.env,
win=self.plots[title_name],
name=legend,
update='append')
def plot_curve(self,
ylabel: str,
xlabel: str,
legend: list,
title_name: str,
x: np.array,
y: np.array,
markers=False):
if title_name in self.plots.keys():
# Reset plot
self.viz.close(self.plots[title_name], env=self.env)
self.plots[title_name] = self.viz.line(X=x,
Y=y,
env=self.env,
opts=dict(title=title_name,
xlabel=xlabel,
ylabel=ylabel,
markers=markers,
markersymbol='plus'))
def stem_plot(self, title_name: str, ylabel: str, xlabel: str,
legend: list, y: np.array, x: np.array):
if title_name in self.plots.keys():
# Reset plot
self.viz.close(self.plots[title_name], env=self.env)
self.plots[title_name] = self.viz.stem(X=x,
Y=y,
env=self.env,
opts=dict(legend=legend,
title_name=title_name,
xlabel=xlabel,
ylabel=ylabel))
def scatter_plot(self,
title_name: str,
x: np.array,
y: np.array,
legends=None):
if title_name in self.plots.keys():
# Reset plot
self.viz.close(self.plots[title_name], env=self.env)
y_plot = y.copy()
y_plot += 1
self.plots[title_name] = self.viz.scatter(X=x,
Y=y_plot,
env=self.env,
opts=dict(
title=title_name,
legends=[legends],
markersymbol='dot'))
def vis_1d_distribution(self, pts: np.array, name: str) -> None:
step = 0.05
max_distance = max(pts) + step
bins = np.arange(0.0, max_distance, step)
hist, _ = np.histogram(pts, bins=bins)
self.stem_plot(name, 'Samples number', name, ['dist'], bins[1:], hist)
def plot_exist(self, title_name):
return title_name in self.plots.keys()