def bqstreamplot(self):
Cxs = bq.DateScale()
Cys = bq.LinearScale()
Cx = self.CallIVtable.index.values
Cy = self.CallIVtable.as_matrix().transpose()
Ccol = self.CallIVtable.columns.tolist()
self.Cline = bq.Lines(x=Cx, y=Cy, scales={'x': Cxs, 'y': Cys},
colors=[i.hex for i in list(Color(rgb=(0.95,0,0)).range_to(Color(rgb=(0.45,0.1,0)), len(Ccol)))],
labels=Ccol,
enable_hover=True,
display_legend=True)
Cxax = bq.Axis(scale=Cxs, label='Datetime', grid_lines='solid')
Cyax = bq.Axis(scale=Cys, orientation='vertical', tick_format='0.1f', label='CallIV', grid_lines='solid')
figC = bq.Figure(marks=[self.Cline], axes=[Cxax, Cyax], animation_duration=1000)
Pxs = bq.DateScale()
Pys = bq.LinearScale()
Px = self.PutIVtable.index.values
Py = self.PutIVtable.as_matrix().transpose()
Pcol = self.PutIVtable.columns.tolist()
self.Pline = bq.Lines(x=Px, y=Py, scales={'x': Pxs, 'y': Pys},
colors=[i.hex for i in list(Color(rgb=(0,0.75,0)).range_to(Color(rgb=(0,0,0.45)), len(Pcol)))],
labels=Pcol,
enable_hover=True,
display_legend=True)
Pxax = bq.Axis(scale=Pxs, label='Datetime', grid_lines='solid')
Pyax = bq.Axis(scale=Pys, orientation='vertical', tick_format='0.1f', label='PutIV', grid_lines='solid')
figP = bq.Figure(marks=[self.Pline], axes=[Pxax, Pyax], animation_duration=1000)
display(HBox(([figC,figP])))
def lightcurve_widget(self):
'''Create light curve widget'''
xax = bq.Axis(label='Time (MJD)',
scale=self.sc_x,
grid_lines='solid',
label_location="middle")
xax.tick_style = {'stroke': 'black', 'font-size': 12}
yax = bq.Axis(label='Magnitude',
scale=self.sc_y,
orientation='vertical',
tick_format='0.1f',
grid_lines='solid',
label_location="middle")
yax.tick_style = {'stroke': 'black', 'font-size': 12}
panzoom = bq.PanZoom(scales={'x': [self.sc_x], 'y': [self.sc_y]})
return bq.Figure(
axes=[xax, yax],
marks=[],
layout=Layout(width='100%', height='auto'),
fig_margin={
'top': 0,
'bottom': 40,
'left': 50,
'right': 0
},
legend_location='top-right',
)
def live_plot(plot_string, topic_type, history=100, title=None):
topic = plot_string[:plot_string.find(':') - 1]
title = title if title else topic
fields = plot_string.split(':')[1:]
x_sc = bq.LinearScale()
y_sc = bq.LinearScale()
ax_x = bq.Axis(label='X', scale=x_sc, grid_lines='solid')
ax_y = bq.Axis(label='Y', scale=y_sc, orientation='vertical', grid_lines='solid')
lines = bq.Lines(x=np.array([]), y=np.array([]), scales={'x': x_sc, 'y': y_sc})
fig = bq.Figure(axes=[ax_x, ax_y], marks=[lines], labels=fields, display_legend=True, title=title)
data = []
def cb(msg, data=data):
data_el = []
for f in fields:
data_el.append(getattr(msg, f))
data.append(data_el)
data = data[-history:]
ndat = np.asarray(data).T
if lines:
lines.y = ndat
lines.x = np.arange(len(data))
rospy.Subscriber(topic, topic_type, cb)
return fig
def plot_timeseries(server, e, dataset_id):
"""This defines the initial bqplot time series plot"""
dt_x = bq.DateScale()
sc_y = bq.LinearScale()
constraints = {
"time>=": server.get("min_time"),
"time<=": server.get("max_time")
}
df, var = get_timeseries(
e=e,
dataset=dataset_id,
standard_name=server.get("standard_name"),
constraints=constraints,
)
def_tt = bq.Tooltip(fields=["y"], formats=[".2f"], labels=["value"])
time_series = bq.Lines(
x=df.index,
y=df[var],
scales={
"x": dt_x,
"y": sc_y
},
tooltip=def_tt,
)
ax_x = bq.Axis(scale=dt_x, label="Time")
ax_y = bq.Axis(scale=sc_y, orientation="vertical")
figure = bq.Figure(marks=[time_series], axes=[ax_x, ax_y])
figure.title = f"{dataset_id[:18]} - {var}"
figure.layout.height = "300px"
figure.layout.width = "800px"
return figure
def init_bq_fig(self):
self.bq_xscale = bq.LinearScale()
self.bq_yscale = bq.LinearScale()
self.bq_colorscale = bq.ColorScale(min=-1, max=1)
self.bq_xax = bq.Axis(scale=self.bq_xscale)
self.bq_yax = bq.Axis(scale=self.bq_yscale, orientation='vertical')
self.bq_colorax = bq.ColorAxis(scale=self.bq_colorscale)
self.bq_heat = bq.HeatMap(
x=self.x,
y=self.z,
color=zeros_like(self.cY),
scales={
'x': self.bq_xscale,
'y': self.bq_yscale,
'color': self.bq_colorscale
}
)
self.bq_fig = bq.Figure(
marks=[self.bq_heat],
axes=[
self.bq_xax,
self.bq_yax,
self.bq_colorax
]
)
def create(self, data):
size = data.shape[0]
assert len(data.shape) == 1
xmin, xmax = self.limits[0]
dx = (xmax - xmin) / size
x = np.linspace(xmin, xmax - dx, size) + dx / 2
# print xmin, xmax, x
self.scale_x = bq.LinearScale(min=xmin + dx / 2, max=xmax - dx / 2)
self.scale_y = bq.LinearScale()
self.axis_x = bq.Axis(label='X', scale=self.scale_x)
self.axis_y = bq.Axis(label='Y',
scale=self.scale_y,
orientation='vertical')
self.bars = bq.Bars(x=x,
y=data,
scales={
'x': self.scale_x,
'y': self.scale_y
},
colors=[self.color])
self.fig = bq.Figure(axes=[self.axis_x, self.axis_y],
marks=[self.bars],
padding_x=0)
def draw_graph(graph, pos=None):
from numpy import array
import networkx as nx
import bqplot as bq
if pos is None:
pos = nx.spring_layout(graph)
nodes = graph.nodes()
x = [pos[n][0] for n in nodes]
y = [pos[n][1] for n in nodes]
lines_x = []
lines_y = []
for k, v in graph.edges():
i1 = graph.nodes().index(k)
i2 = graph.nodes().index(v)
lines_x.append([x[i1], x[i2]])
lines_y.append([y[i1], y[i2]])
lines_x = array(lines_x)
lines_y = array(lines_y)
x_sc = bq.LinearScale()
y_sc = bq.LinearScale()
points = bq.Scatter(x=x, y=y, scales={'x': x_sc, 'y': y_sc})
lines = bq.Lines(x=lines_x,
y=lines_y,
scales={
'x': x_sc,
'y': y_sc
},
colors=['red'])
ax_x = bq.Axis(scale=x_sc)
ax_y = bq.Axis(scale=y_sc, orientation='vertical')
fig = bq.Figure(marks=[lines, points], axes=[ax_x, ax_y])
return fig
def make_pixel_intensities_pane(self):
FULL_HEIGHT = 800
scales = {
'x': bq.LinearScale(min=0),
'y': bq.LinearScale(min=0, max=255)
}
self.pixel_intensities_mark = bq.Lines(scales=scales,
colors=['blue', 'green', 'red'],
display_legend=True,
opacities=[0.7] * 3)
axes = [bq.Axis(scale=scales['y'], orientation='vertical')]
self.pixel_intensities_fig = bq.Figure(
marks=[self.pixel_intensities_mark], axes=axes)
self.pixel_intensities_fig.layout.width = '100%'
self.pixel_intensities_fig.layout.height = str(
self.display_pane.size * FULL_HEIGHT) + 'px'
self.pixel_intensities_fig.layout.margin = '0'
self.pixel_intensities_fig.title = 'Pixel Intensities Along Segment'
self.update_pixel_intensities_mark()
return ipy.VBox([
self.pixel_intensities_fig,
bq.toolbar.Toolbar(figure=self.pixel_intensities_fig)
])
def __init__(self, scheme, count=None, **options):
colors = self.palettes[scheme]
super().__init__(scheme, count or len(colors))
self.colors = self.mkpal(colors, self.count)
self.opt = opt = getopt(options,
fig_title=self.scheme,
fig_width=960,
fig_height=150)
data = np.arange(0, len(self.colors))
cs = bq.ColorScale(colors=self.colors)
hm = bq.HeatMap(color=np.array([data, data]), scales={"color": cs})
self.figure = bq.Figure(marks=[hm],
layout=ipw.Layout(
width="%spx" % opt.fig["width"],
height="%spx" % opt.fig["height"]),
padding_x=0.0,
padding_y=0.0,
fig_margin={
"top": 60,
"bottom": 0,
"left": 0,
"right": 0
},
title=opt.fig["title"])
self.vbox = ipw.VBox([self.figure, bq.Toolbar(figure=self.figure)])
def __init__(self, model=None, *args, **kwargs):
super(GeneratorCostView, self).__init__(*args, **kwargs)
if model is not None:
self.model = model
else:
self.model = Generator()
self._scale_x = bq.LinearScale(min=self.model.minimum_real_power,
max=self.model.maximum_real_power)
self._scale_y = bq.LinearScale(
min=0, max=(max(self.model.cost_curve_values) * 1.5 + 50))
self._scales = {
'x': self._scale_x,
'y': self._scale_y,
}
self._scatter = bq.Scatter(x=self.model.cost_curve_points,
y=self.model.cost_curve_values,
scales=self._scales)
self._lines = bq.Lines(x=self.model.cost_curve_points,
y=self.model.cost_curve_values,
scales=self._scales)
self._axes_x = bq.Axis(scale=self._scale_x)
self._axes_y = bq.Axis(scale=self._scale_y,
orientation='vertical',
padding_x=0.025)
f = bq.Figure(marks=[
self._lines,
self._scatter,
],
axes=[
self._axes_x,
self._axes_y,
])
children = [f]
self.children = children
t.link((self.model, 'maximum_real_power'), (self._scale_x, 'max'))
t.link((self.model, 'cost_curve_points'), (self._scatter, 'x'))
t.link((self.model, 'cost_curve_values'), (self._scatter, 'y'))
t.link((self._lines, 'x'), (self._scatter, 'x'))
t.link((self._lines, 'y'), (self._scatter, 'y'))
# self._scatter.observe(self._callback_ydata, names=['y'])
with self._scatter.hold_sync():
self._scatter.enable_move = True
self._scatter.update_on_move = True
self._scatter.interactions = {'click': None}
def representation_complexe():
real = widgets.BoundedFloatText(value=1,
min=-2.0,
max=2.0,
step=0.1,
disabled=True)
imag = widgets.BoundedFloatText(value=1,
min=-2.0,
max=2.0,
step=0.1,
disabled=True)
sc_x = bqplot.LinearScale(min=-2, max=2)
sc_y = bqplot.LinearScale(min=-2, max=2)
ax_x = bqplot.Axis(scale=sc_x, offset=dict(value=0.5), grid_lines='none')
ax_y = bqplot.Axis(scale=sc_y,
orientation='vertical',
offset=dict(value=0.5),
grid_lines='none')
z_point = bqplot.Scatter(x=[real.value],
y=[imag.value],
scales={
'x': sc_x,
'y': sc_y
},
colors=['green'],
enable_move=True)
z_point.update_on_move = True
fig = bqplot.Figure(marks=[z_point],
axes=[ax_x, ax_y],
min_aspect_ratio=1,
max_aspect_ratio=1)
complex_z = widgets.HBox([
widgets.Label('$z = $'), real,
widgets.Label('$ + $'), imag,
widgets.Label('$i$')
])
def update_z(change=None):
real.value = z_point.x[0]
imag.value = z_point.y[0]
z_point.observe(update_z, names=['x', 'y'])
#def update_point(change=None):
# z_point.x = [real.value]
# z_point.y = [imag.value]
#real.observe(update_point, names='value')
#imag.observe(update_point, names='value')
return widgets.VBox([fig, complex_z],
layout=widgets.Layout(align_items="center"))
def get_input_form(self, figure_title, no_users=100):
if self.fig:
return self.fig
self.figure_title = figure_title
max_hours = 24 + 1
max_users = no_users
# Define scales
x_scale = bqplot.LinearScale(min=0, max=max_hours)
y_scale = bqplot.LinearScale(min=0, max=max_users)
# Initialize data for our line
line = bqplot.Lines(
x=np.arange(0, max_hours),
y=np.zeros(max_hours),
scales={"x": x_scale, "y": y_scale},
fill="bottom",
fill_opacities=[0.5],
)
# Layout only - axes (plural of axis)
x_axis = bqplot.Axis(scale=x_scale, label="Hour", grid_lines="none")
y_axis = bqplot.Axis(
scale=y_scale,
label="Number of Users",
grid_lines="none",
orientation="vertical",
)
def _fix_input_callback(change):
# ensures we draw integer values 0 or greater and that
# 00:00 [0] and 24:00 [24] represent the same value.
with line.hold_sync():
if change["old"][-1] != change["new"][-1]:
line.y[0] = line.y[-1]
elif change["old"][0] != change["new"][0]:
line.y[-1] = line.y[0]
line.y = np.fmax(0, np.rint(line.y))
line.observe(_fix_input_callback, names=["y"])
handdraw_interaction = bqplot.interacts.HandDraw(lines=line)
self.fig = bqplot.Figure(
marks=[line],
axes=[x_axis, y_axis],
interaction=handdraw_interaction,
animation_duration=150,
title=self.figure_title,
)
return self.fig
def __init__(self):
'''Initialization of a Gomoku game with an empty board and a random starting party'''
self.A = np.zeros(
(15, 15),
dtype=int) # this holds the information of the current game status
# 0 means empty place
# 1 is red
# 2 is blue
# the visualization of the table is generated by bqplot
sc_x = bq.LinearScale(max=15.5, min=-1.5)
sc_y = bq.LinearScale(max=15.5, min=-1.5)
scatt1 = bq.Scatter(x=[],
y=[],
scales={
'x': sc_x,
'y': sc_y
},
colors=['red'],
default_size=500)
scatt2 = bq.Scatter(x=[],
y=[],
scales={
'x': sc_x,
'y': sc_y
},
colors=['blue'],
default_size=500)
winline = bq.Lines(x=[],
y=[],
scales={
'x': sc_x,
'y': sc_y
},
colors=['lightgreen'],
stroke_width=5)
props = dict(tick_values=np.arange(16) - 0.5,
grid_color='black',
tick_style={'font-size': 0})
ax_x = bq.Axis(scale=sc_x, **props)
ax_y = bq.Axis(scale=sc_y, orientation='vertical', **props)
fig = bq.Figure(marks=[scatt1, scatt2, winline], axes=[ax_x, ax_y])
fig.max_aspect_ratio = 1.0
fig.min_aspect_ratio = 1.0
fig.layout.height = '600px'
self.fig = fig
# the starting player is randomly selected
self.who_is_next = np.random.randint(1, 3)
self.fig.title = 'Next player is ' + ['red ', 'blue '
][self.who_is_next - 1]
# initially noone is winning
self.win_string = False
def plot_orbit(z0=0.5+0.5*1j, c=0+0*1j):
sc_x = bqplot.LinearScale(min=-1.2, max=1.2)
sc_y = bqplot.LinearScale(min=-1.2, max=1.2)
c_point = bqplot.Scatter(x=[c.real], y=[c.imag], scales={'x': sc_x, 'y': sc_y}, colors=['red'],
enable_move=True, default_size=200)
c_point.update_on_move = True
z_point = bqplot.Scatter(x=[z0.real], y=[z0.imag], scales={'x': sc_x, 'y': sc_y}, colors=['green'],
enable_move=True, default_size=200)
z_point.update_on_move = True
c_label = bqplot.Label(x=[c.real+.05], y=[c.imag+.05], scales={'x': sc_x, 'y': sc_y}, colors=['red'],
text=['c'],
default_size=26, font_weight='bolder')
z_label = bqplot.Label(x=[z0.real+.05], y=[z0.imag+.05], scales={'x': sc_x, 'y': sc_y}, colors=['green'],
text=['z0'],
default_size=26, font_weight='bolder')
scatt = bqplot.Scatter(x=[], y=[], scales={'x': sc_x, 'y': sc_y}, colors=['black'], default_size=20)
theta = np.linspace(0, 2.*np.pi, 1000)
x = np.cos(theta)
y = np.sin(theta)
circle = bqplot.Lines(x=x, y=y, scales={'x': sc_x, 'y': sc_y}, colors=['black'])
lin = bqplot.Lines(x=[], y=[], scales={'x': sc_x, 'y': sc_y}, colors=['black'], stroke_width=1)
def update_line(change=None):
out = orbit(z_point.x + 1j*z_point.y, c_point.x + 1j*c_point.y)
c_label.x = c_point.x + 0.05
c_label.y = c_point.y + 0.05
z_label.x = z_point.x + 0.05
z_label.y = z_point.y + 0.05
lin.x = out.real
lin.y = out.imag
scatt.x = out.real.flatten()
scatt.y = out.imag.flatten()
update_line()
# update line on change of x or y of scatter
c_point.observe(update_line, names=['x'])
c_point.observe(update_line, names=['y'])
z_point.observe(update_line, names=['x'])
z_point.observe(update_line, names=['y'])
ax_x = bqplot.Axis(scale=sc_x, offset=dict(value=0.5), grid_lines='none')
ax_y = bqplot.Axis(scale=sc_y, orientation='vertical', offset=dict(value=0.5), grid_lines='none')
fig = bqplot.Figure(marks=[scatt, lin, circle, c_point, z_point, c_label, z_label], axes=[ax_x, ax_y],
min_aspect_ratio=1, max_aspect_ratio=1)
fig.layout.height = '800px'
return fig
def display(self):
pos = networkx.nx_pydot.graphviz_layout(self._graph, prog='dot')
x, y = zip(*(pos[node] for node in self._graph.nodes()))
fw_id_to_node_index = {
self._fw_workflow.fws[i].fw_id: i
for i in range(len(self._fw_workflow.fws))
}
node_data = [{
'label': str(node.fw_id),
'name': node.name,
'state': node.state,
'tasks': [str(t) for t in node.tasks],
'shape': 'rect',
} for node in self._fw_workflow.fws]
link_data = [{
'source': fw_id_to_node_index[source],
'target': fw_id_to_node_index[target]
} for source, target in self._graph.edges()]
xs = bqplot.LinearScale(min=min(x), max=max(x))
ys = bqplot.LinearScale(min=min(y), max=max(y))
scales = {'x': xs, 'y': ys}
graph = bqplot.Graph(node_data=node_data,
link_data=link_data,
scales=scales,
colors=['white'],
link_type='line',
highlight_links=False,
x=x,
y=y,
selected_style={
'stroke': 'yellow',
'stroke-width': '4',
'opacity': '0.5'
})
tooltip = bqplot.Tooltip(fields=['name', 'state', 'tasks'],
format=['', '', ''])
graph.tooltip = tooltip
layout = ipywidgets.Layout(min_width='50%',
width='auto',
min_height='200px',
height='auto')
fig = bqplot.Figure(marks=[graph], layout=layout)
#toolbar = bqplot.Toolbar(figure=fig)
#return ipywidgets.VBox([fig, toolbar])
return ipywidgets.VBox([fig])
def add_del(scale, img):
"""Add function for ipywidget buttons to add and delete points"""
scat = bq.Scatter(x=[],
y=[],
scales=scale,
colors=['orange'],
enable_move=True)
image = bq.Image(x=np.array([scale['x'].min, scale['x'].max]),
y=np.array([scale['y'].min, scale['y'].max]),
image=img,
scales=scale,
enable_hover=False)
interact_control = widgets.ToggleButtons(options=['Add', 'Delete'],
style={'button_width': '130px'})
def change_interact(shape):
"""Give a meaning to the buttons."""
interact_params = {
'Add': {
'interactions': {
'click': 'add'
},
'enable_move': True
},
'Delete': {
'interactions': {
'click': 'delete'
},
'enable_move': False
}
}
for param, value in interact_params[interact_control.value].items():
setattr(scat, param, value)
interact_control.observe(change_interact)
fig = bq.Figure(title='Cross-section',
marks=[image, scat],
padding_x=0,
padding_y=0)
fig.axes = [
bq.Axis(scale=scale['x']),
bq.Axis(scale=scale['y'], orientation='vertical')
]
return widgets.VBox([fig, interact_control])
def create_fig(self):
t1_values = self.get_values(self.t1)
t2_values = self.get_values(self.t2)
self.df = t1_values.merge(t2_values, how='inner', on='patient.id')
sc_x = plt.LinearScale()
sc_y = plt.LinearScale()
self.mark = plt.Scatter(scales={'x': sc_x, 'y': sc_y}, default_size=16)
ax_x = plt.Axis(scale=sc_x, label=self.t1.title)
ax_y = plt.Axis(scale=sc_y,
label=self.t2.title,
orientation='vertical')
self.fig = plt.Figure(marks=[self.mark], axes=[ax_x, ax_y])
def __init__(self, lineFig):
"""
"""
self.lineFig = lineFig
self.marks = self.lineFig.marks
y_ord = bq.OrdinalScale()
x_sc = bq.LinearScale()
legendLabels = []
self.colours = []
for mark in self.marks:
legendLabels += mark.labels
self.colours += mark.colors[:len(mark.labels)]
self.bars = bq.Bars(
y=[1] *
len(legendLabels), # all bars have a amplitude of 1 ## ?
x=legendLabels,
scales={
'y': x_sc,
'x': y_ord
},
colors=self.colours,
padding=0.6,
orientation='horizontal',
stroke='white') ## remove the black border around the bar
self.bars.opacities = [ScatLegend.OPAC_BRIGHT] * len(self.bars.x)
ax_y = bq.Axis(scale=y_ord, orientation="vertical")
ax_x = bq.Axis(scale=x_sc)
ax_x.visible = False
margin = dict(top=40, bottom=0, left=110, right=5)
self.fig = bq.Figure(marks=[self.bars],
axes=[ax_y, ax_x],
fig_margin=margin)
# Variable height depending on number of bars in legend
self.fig.layout.height = str(45 + 20 * len(legendLabels)) + 'px'
self.fig.layout.width = '170px'
self.fig.min_aspect_ratio = 0.000000000001 # effectively remove aspect ratio constraint
self.fig.max_aspect_ratio = 999999999999999 # effectively remove aspect ratio constraint
self.fig.background_style = {'fill': 'White'}
self.bars.on_element_click(self.changeOpacity)
def create_plot():
index = pd.date_range(start='2000-06-01', end='2001-06-01',
freq='30min') + timedelta(minutes=15)
s = pd.Series(np.full(len(index), np.nan), index=index)
x = index.values
y = s
x_sc = bq.DateScale()
y_sc = bq.LinearScale(min=0)
line = bq.Lines(
x=x,
y=y,
scales={
'x': x_sc,
'y': y_sc
},
#display_legend=True, labels=["line 1"],
#fill='bottom', # opacity does work with this option
#fill_opacities = [0.5] *len(x)
)
panzoom = bq.PanZoom(scales={'x': [x_sc], 'y': [y_sc]})
#p = bq.Scatter(x=x, y=y, scales= {'x': x_sc, 'y': y_sc})
ax_x = bq.Axis(scale=x_sc)
ax_y = bq.Axis(scale=y_sc, orientation='vertical', tick_format='0.2f')
#fig = bq.Figure(marks=[line, p], axes=[ax_x, ax_y])
fig = bq.Figure(marks=[line], axes=[ax_x, ax_y], interaction=panzoom)
fig.layout.width = '95%'
#p.interactions = {'click': 'select', 'hover': 'tooltip'}
#p.selected_style = {'opacity': 1.0, 'fill': 'DarkOrange', 'stroke': 'Red'}
#p.unselected_style = {'opacity': 0.5}
#p.tooltip = bq.Tooltip(fields=['x', 'y'], formats=['', '.2f'])
#sel = bq.interacts.IndexSelector(scale=p.scales['x'])
#
#def update_range(*args):
# if sel.selected:
# print(sel.selected[0])
#
#sel.observe(update_range, 'selected')
#fig.interaction = sel
return fig, line
def make_image_plot(self):
marks = [self.bq_img]
for interactor in self.interactors:
marks += interactor.image_plot_marks
image_plot = bq.Figure(marks=marks, padding_y=0)
height, width, _ = self.raw_frame.get().shape
# make sure the image is displayed with the correct aspect ratio
image_plot.layout.width = '100%'
image_plot.layout.margin = '0'
image_plot.layout.height = str(self.size * self.FULL_INTERNAL_WIDTH *
height / width +
self.size * self.FULL_OFFSET) + 'px'
return image_plot
def __init__(self, precisions, recalls, thres):
assert (len(recalls) == len(precisions) == len(thres))
# Callback
def index_change_callback(change):
selected_recall = int(np.round(change.new[0]))
index = np.abs(recalls - selected_recall).argmin()
w_precision.value = "{:2.2f}".format(precisions[index])
w_recall.value = "{:2.2f}".format(recalls[index])
w_threshold.value = "{:2.2f}".format(thres[index])
# Set up bqplot UI
ls_x = bqplot.LinearScale(min=0, max=100) # reverse=True)
ls_y = bqplot.LinearScale(min=0, max=100)
axis_y = bqplot.Axis(label='Recall', scale=ls_x)
axis_x = bqplot.Axis(label='Precision',
scale=ls_y,
orientation='vertical')
lines = bqplot.Lines(x=recalls,
y=precisions,
scales={
'x': ls_x,
'y': ls_y
},
colors=['orange'])
index_sel = bqplot.interacts.IndexSelector(scale=ls_x,
marks=[lines],
color="blue",
colors=["green"])
index_sel.observe(index_change_callback, names=['selected'])
fig = bqplot.Figure(marks=[lines],
axes=[axis_x, axis_y],
title='Precision-recall curve',
interaction=index_sel)
# Set up p/r/threshold text fields UI
w_precision = widgets.Text(value="CLICK ON PLOT",
description="Precision:")
w_recall = widgets.Text(value="CLICK ON PLOT", description="Recall:")
w_threshold = widgets.Text(value="CLICK ON PLOT",
description="Threshold:")
w_texts = widgets.HBox(children=[w_precision, w_recall, w_threshold])
# Create final UI
self.ui = widgets.VBox([fig, w_texts])
def __init__(self, session, state=None):
# if we allow padding, we sometimes get odd behaviour with the interacts
self.scale_x = bqplot.LinearScale(min=0, max=1, allow_padding=False)
self.scale_y = bqplot.LinearScale(min=0, max=1)
super(BqplotBaseView, self).__init__(session, state=state)
# session.hub.subscribe(self, SubsetCreateMessage,
# handler=self.receive_message)
self.scales = {'x': self.scale_x, 'y': self.scale_y}
self.axis_x = bqplot.Axis(
scale=self.scale_x, grid_lines='solid', label='x')
self.axis_y = bqplot.Axis(scale=self.scale_y, orientation='vertical', tick_format='0.2f',
grid_lines='solid', label='y')
def update_axes(*ignore):
self.axis_x.label = str(self.state.x_att)
if self.is2d:
self.axis_y.label = str(self.state.y_att)
self.state.add_callback('x_att', update_axes)
if self.is2d:
self.state.add_callback('y_att', update_axes)
self.figure = bqplot.Figure(scales=self.scales, animation_duration=0, axes=[
self.axis_x, self.axis_y])
self.figure.padding_y = 0
self._fig_margin_default = self.figure.fig_margin
self._fig_margin_zero = dict(self.figure.fig_margin)
self._fig_margin_zero['left'] = 0
self._fig_margin_zero['bottom'] = 0
link((self.state, 'x_min'), (self.scale_x, 'min'), float_or_none)
link((self.state, 'x_max'), (self.scale_x, 'max'), float_or_none)
link((self.state, 'y_min'), (self.scale_y, 'min'), float_or_none)
link((self.state, 'y_max'), (self.scale_y, 'max'), float_or_none)
on_change([(self.state, 'show_axes')])(self._sync_show_axes)
self.create_tab()
self.output_widget = widgets.Output()
self.main_widget = widgets.VBox([
self.widget_toolbar,
widgets.HBox([self.figure, self.tab]),
self.output_widget
])
def _getFig(self):
for v in self.model.label:
x_sc = bq.LinearScale()
y_sc = bq.LinearScale()
x_ax = bq.Axis(label='Time',
scale=x_sc,
tick_format='0.0f',
color='black',
grid_lines='solid',
grid_color='#ddd')
y_ax = bq.Axis(label=v,
scale=y_sc,
tick_format='0.2f',
color='black',
grid_lines='solid',
grid_color='#ddd',
orientation='vertical')
# Generate a line (but does not plot it)
l = bq.Lines(x=self.model.T,
y=self.sol[v],
colors=[self.colors[v]],
scales={
'x': x_sc,
'y': y_sc
})
self.lines.update({v: l})
fig = bq.Figure(axes=[x_ax, y_ax],
marks=self.lines.values(),
fig_margin={
'top': 10,
'bottom': 0,
'left': 60,
'right': 10
},
max_aspect_ratio=3,
min_aspect_ratio=2.5)
fig.layout.width = '100%'
return fig
def _get_hist_figure(self, x, y, color, bidx):
'''
get a bqplot histogram figure with data and interactive sliders
'''
x_scale = bq.LinearScale()
y_scale = bq.LinearScale()
x_axis = bq.Axis(scale=x_scale, tick_values=None, num_ticks=3)
y_axis = bq.Axis(scale=y_scale,
tick_values=None,
num_ticks=0,
orientation='vertical',
visible=False)
line = bq.Lines(x=x,
y=y,
scales={
'x': x_scale,
'y': y_scale
},
colors=[color],
selected_style={'opacity': '1'},
unselected_style={'opacity': '0.2'})
fast_sel = bq.interacts.FastIntervalSelector(marks=[line],
scale=x_scale,
color='orange')
fig = bq.Figure(title=color,
marks=[line],
axes=[x_axis, y_axis],
fig_margin={
'top': 40,
'bottom': 40,
'left': 40,
'right': 40
},
interaction=fast_sel)
fig.layout.width = '225px'
fig.layout.height = '225px'
return fig
def make_pred_bqplot():
x_sc = bq.LinearScale()
y_sc = bq.LinearScale()
ax_x = bq.Axis(label="Feature", scale=x_sc) # , tick_format="0.0f"
ax_y = bq.Axis(
label="Target",
scale=y_sc,
orientation="vertical" # , tick_format="0.0e"
)
line = bq.Lines(
x=[0],
y=[0],
scales={
"x": x_sc,
"y": y_sc
},
colors=["darkblue"],
opacities=[1],
)
scatter = bq.Scatter(
x=[0],
y=[0],
scales={
"x": x_sc,
"y": y_sc
},
colors=["red"],
opacities=[1],
)
out_plot = bq.Figure(
axes=[ax_x, ax_y],
marks=[line, scatter],
# interaction=interval_selector,
# animation_duration=100,
)
out_plot.legend_style = {"stroke-width": 0}
out_plot.layout.width = "flex"
return {k: v for k, v in locals().items()}
def display(self):
pos = networkx.nx_pydot.graphviz_layout(self._graph, prog='dot')
x, y = zip(*(pos[node] for node in self._graph.nodes()))
node_data = [{
'label': str(node._id),
'shape': 'rect',
'tasks': [str(t) for t in node._tasks]
} for node in self._graph.nodes()]
link_data = [{
'source': source.index[self],
'target': target.index[self]
} for source, target in self._graph.edges()]
xs = bqplot.LinearScale()
ys = bqplot.LinearScale()
scales = {'x': xs, 'y': ys}
graph = bqplot.Graph(node_data=node_data,
link_data=link_data,
scales=scales,
colors=['white'],
link_type='line',
highlight_links=False,
x=x,
y=y,
selected_style={
'stroke': 'yellow',
'stroke-width': '4',
'opacity': '0.5'
})
tooltip = bqplot.Tooltip(fields=['tasks'])
graph.tooltip = tooltip
layout = ipywidgets.Layout(min_width='50%',
width='auto',
min_height='200px',
height='auto')
fig = bqplot.Figure(marks=[graph], layout=layout)
return ipywidgets.VBox([fig])
def create_fig(self, *args):
logger.info('Creating figure.')
tooltip_widget = plt.Tooltip(fields=['size', 'label'])
pie = plt.Pie(tooltip=tooltip_widget,
interactions={
'click': 'select',
'hover': 'tooltip'
})
pie.radius = 110
pie.inner_radius = 65
pie.font_weight = 'bold'
pie.selected_style = {
"opacity": "1",
"stroke": "white",
"stroke-width": "4"
}
pie.unselected_style = {"opacity": "0.5"}
logger.info('Returning figure.')
return plt.Figure(marks=[pie])
def __init__(self, session, state=None):
# if we allow padding, we sometimes get odd behaviour with the interacts
self.scale_x = bqplot.LinearScale(min=0, max=1, allow_padding=False)
self.scale_y = bqplot.LinearScale(min=0, max=1)
super(BqplotBaseView, self).__init__(session, state=state)
self.scales = {'x': self.scale_x, 'y': self.scale_y}
self.axis_x = bqplot.Axis(
scale=self.scale_x, grid_lines='none', label='x')
self.axis_y = bqplot.Axis(scale=self.scale_y, orientation='vertical', tick_format='0.2f',
grid_lines='none', label='y')
def update_axes(*ignore):
self.axis_x.label = str(self.state.x_att)
if self.is2d:
self.axis_y.label = str(self.state.y_att)
self.state.add_callback('x_att', update_axes)
if self.is2d:
self.state.add_callback('y_att', update_axes)
self.figure = bqplot.Figure(scales=self.scales, animation_duration=0,
axes=[self.axis_x, self.axis_y],
fig_margin={'left': 60, 'bottom': 60, 'top': 10, 'right': 10})
self.figure.padding_y = 0
self._fig_margin_default = self.figure.fig_margin
self._fig_margin_zero = dict(self.figure.fig_margin)
self._fig_margin_zero['left'] = 0
self._fig_margin_zero['bottom'] = 0
link((self.state, 'x_min'), (self.scale_x, 'min'), float_or_none)
link((self.state, 'x_max'), (self.scale_x, 'max'), float_or_none)
link((self.state, 'y_min'), (self.scale_y, 'min'), float_or_none)
link((self.state, 'y_max'), (self.scale_y, 'max'), float_or_none)
on_change([(self.state, 'show_axes')])(self._sync_show_axes)
self.create_layout()
def plot():
co2_conc = in_dd1.value
key_x = in_dd2.value
key_y = in_dd3.value
dir_name = Path(co2_dict[co2_conc])
df = get_df(dir_name)
sc_x = bq.LinearScale(min=5, max=25)
sc_y = bq.LinearScale()
da_x = df[key_x]
da_y = df[key_y]
ax_x = bq.Axis(scale=sc_x, grid_lines='solid', label=key_x)
ax_y = bq.Axis(scale=sc_y, orientation='vertical', label=key_y)
lines = bq.Lines(x=da_x,
y=da_y,
scales={
'x': sc_x,
'y': sc_y
},
stroke_width=3,
colors=['blue'])
#ax.plot('wavlen_um','total_trans',data=df)
#ax.set_title(key)
#ax.set_xlim([5,25])
grid[:, 1:2] = bq.Figure(marks=[lines],
axes=[ax_x, ax_y],
layout=Layout(width='auto', height='auto'),
fig_margin=dict(top=60,
bottom=40,
left=40,
right=0),
title=key_x + ' vs ' + key_y +
' with CO2 conc. = ' + co2_conc)
def gui_figure (self) :
self._x_scale = bq.LinearScale(min=0, max=self.opt.fig.width)
self._y_scale = bq.LinearScale(min=0, max=self.opt.fig.height)
if self.opt.fig.title is None :
title, top = " ", 0
else :
title = str(self.opt.fig.title).strip() or " "
top = 60 if title != " " else 0
title = str(self.opt.fig.title) or " " if self.opt.fig.title else " "
figure = bq.Figure(marks=([self.gui_graph]
+ list(self.gui_marks.values())
+ list(self.gui_tips.values())),
layout=ipw.Layout(width="%spx" % self.opt.fig.width,
height="%spx" % self.opt.fig.height),
padding_x=self.opt.fig.padding,
padding_y=self.opt.fig.padding,
fig_margin={"top" : top,
"bottom" : 0,
"left" : 0,
"right" : 0},
background_style={"fill" : self.opt.fig.background},
title=title)
return figure
