class Node(pynetsym.Node):
state = Enum('S', 'I', 'R')
recovery_rate = Float(1.0)
infection_rate = Float(1.0)
infected_fraction = Float
def initialize(self, state):
self.state = state
if state == 'I':
self.send(Activator.name, 'infected', node=self.id)
def infect(self):
if self.state == 'S':
self.state = 'I'
self.send(Activator.name, 'infected', node=self.id)
def activate(self):
if self.state == 'I':
for node in self.neighbors():
if random.random() < self.infection_rate:
self.send(node, 'infect')
if random.random() < self.recovery_rate:
self.state = 'R'
self.send(Activator.name, 'not_infected', node=self.id)
elif self.state in ('R', 'S'):
pass
else:
self.send_log('I should not get here.')
class Node(pynetsym.Node):
state = Enum('S', 'I', 'R')
recovery_rate = Float(1.0)
infection_rate = Float(1.0)
spread_out = False
def initialize(self, state):
self.state = state
if state == 'I':
self.send(Activator.name, 'infected', node=self.id)
def infect(self):
if self.state == 'S':
self.state = 'I'
self.send(Activator.name, 'infected', node=self.id)
def activate(self):
if self.state == 'I':
if not self.spread_out or self.infection_rate < 1.0:
for node in self.neighbors():
if random.random() < self.infection_rate:
self.send(node, 'infect')
self.spread_out = True
if random.random() < self.recovery_rate:
self.state = 'R'
self.send(Activator.name, 'not_infected', node=self.id)
def test_traits_shared_transient(self):
# Regression test for a bug in traits where the same _metadata
# dictionary was shared between different trait types.
class LazyProperty(TraitType):
def get(self, obj, name):
return 1729
self.assertFalse(Float().transient)
LazyProperty().as_ctrait()
self.assertFalse(Float().transient)
class PAFTest(HasTraits):
context = Instance(ParametricModelingContext)
parameters = Instance(Parameters)
update = Button
r = Float(1.)
a = Float(100.)
view = View(
Item("parameters", editor=PAFContextEditorFactory(context='context')),
Item("update"), Item("a"), Item("r"))
def _update_changed(self):
self.parameters.a = self.a
self.parameters.r = self.r
class NewModelBDialog(NewModelDialog):
"""Create a dialog requesting the parameters to create Model B."""
model_name = Str(MODEL_B_NAME)
nclasses = Int(5)
nannotators = Int(8)
# prior strength multiplies the dirichlet parameters alpha
prior_strength = Float(1.0)
parameters_group = VGroup(
Item(name='nclasses',
editor=RangeEditor(mode='spinner', low=2, high=1000),
label='Number of annotation classes:',
width=100),
Item(name='nannotators',
editor=RangeEditor(mode='spinner', low=2, high=1000),
label='Number of annotators:',
width=100),
Item(name='prior_strength',
editor=RangeEditor(mode='slider',
low=0.0, low_label='null ',
high=3.0, high_label=' high',
label_width=50),
label='Informativeness of prior:')
)
class FloatWithRangeEditor(HasTraits):
"""Dialog containing a RangeEditor in 'spinner' mode for an Int.
"""
number = Float(5.0)
traits_view = View(Item('number', editor=RangeEditor(low=0.0, high=12.0)),
buttons=['OK'])
def wrapper(self, *arg):
t1 = time.time()
self.valid = func(self, *arg)
t2 = time.time()
dt = t2 - t1
if 'duration' not in self.traits():
self.add_trait('duration', Float())
self.duration = dt
class CalibrationObject(HasTraits):
tweak_dict = Dict
cx = Float
cy = Float
rx = Float
ry = Float
rotation = Property(depends_on='rx,ry,_rotation')
_rotation = Float
center = Property(depends_on='cx,cy')
scale = Float(1)
def _set_rotation(self, rot):
self._rotation = rot
def _get_rotation(self):
# if not (self.rx and self.rx):
# return self._rotation
rot = self._rotation
if not rot:
rot = self.calculate_rotation(self.rx, self.ry)
return rot
def _get_center(self):
return self.cx, self.cy
def set_right(self, x, y):
self.rx = x
self.ry = y
self._rotation = 0
def set_center(self, x, y):
self.cx = x
self.cy = y
def calculate_rotation(self, x, y, sense='east'):
def rotation(a, b):
return calc_rotation(self.cx, self.cy, a, b)
if sense == 'west':
print('x={}, y={}, cx={}, cy={}'.format(x, y, self.cx, self.cy))
if y > self.cy:
rot = calc_rotation(self.cx, self.cy, x, y) - 180
else:
rot = calc_rotation(self.cx, self.cy, x, y) + 180
elif sense == 'north':
if x > self.cx:
rot = rotation(x, -y)
else:
rot = rotation(y, -x)
elif sense == 'south':
rot = rotation(-y, x)
else:
rot = rotation(x, y)
return rot
class MandelbrotParameters(HasTraits):
""" Stores the parameters needed to visualize the Mandelbrot set.
"""
# The number of points on each dimension of the grid.
grid_size = Int(500)
# Left limit for the x coordinates.
xmin = Float(-2.0)
# Right limit for the x coordinates.
xmax = Float(1.0, auto_set=False)
# Bottom limit for the y coordinates.
ymin = Float(-1.5, auto_set=False)
# Upper limit for the y coordinates.
ymax = Float(1.5, auto_set=False)
# Convenience property that returns a tuple with the bounds on the x axis.
x_bounds = Property
def _get_x_bounds(self):
return (self.xmin, self.xmax)
# 1D array with the x coordinates of the boundaries of the grid element.
x_coords = Property
def _get_x_coords(self):
# The coordinates have 1 more element than the number of points in
# the grid, because they represent the locations of pixel boundaries.
return numpy.linspace(self.xmin, self.xmax, self.grid_size+1)
# Convenience property that returns a tuple with the bounds on the y axis.
y_bounds = Property(depends_on='ymin,ymax')
def _get_y_bounds(self):
return (self.ymin, self.ymax)
# 1D array with the y coordinates of the boundaries of the grid element.
y_coords = Property(depends_on='ymin,ymax')
def _get_y_coords(self):
# The coordinates have 1 more element than the number of points in
# the grid, because they represent the locations of pixel boundaries.
return numpy.linspace(self.ymin, self.ymax, self.grid_size+1)
class DummyParent(HasTraits):
number = Int()
number2 = Int()
instance = Instance(Dummy, allow_none=True)
instance2 = Instance(Dummy)
income = Float()
dummies = List(Dummy)
def test_complex_baseclass(self):
# Given
class Base(HasTraits):
x = Int
class_name = "MyClass"
bases = (Base, )
class_dict = {"attr": "something", "my_trait": Float()}
# When
update_traits_class_dict(class_name, bases, class_dict)
# Then
self.assertEqual(class_dict[InstanceTraits], {})
self.assertEqual(class_dict[ListenerTraits], {})
self.assertIs(class_dict[BaseTraits]["x"],
class_dict[ClassTraits]["x"])
self.assertIs(
class_dict[BaseTraits]["my_trait"],
class_dict[ClassTraits]["my_trait"],
)
def test_trait_added_match_func_correct(self):
# Test the match function supplied to TraitAddedObserver is consistent
# with the filter.
instance = DummyParent()
integer_observer = create_observer(
filter=lambda name, trait: type(trait.trait_type) is Int,
notify=True,
)
handler = mock.Mock()
call_add_or_remove_notifiers(
object=instance,
graph=create_graph(integer_observer),
handler=handler,
)
# when
# This trait does not satisfy the filter
instance.add_trait("another_number", Float())
instance.another_number += 1
# then
self.assertEqual(handler.call_count, 0)
class BoardWrapper(HasTraits):
pins = List(PinWrapper)
digital_pins = List(PinWrapper)
analog_pins = List(PinWrapper)
defines = List(GuiDefine)
port_type = Enum('serial',
[
'none',
'serial',
]
)
serial_device = Enum(_auto_detect_serial_unix())
baudrate = Int(115200)
sleep_after_connect = Int(2)
timeout = Int(1)
uptime = Float()
tree = None
vcc = Float()
avr_name = Str()
arduino_version = Str()
firmware_build_time = Str()
gcc_version = Str()
libc_version = Str()
libc_date = Str()
connected = Bool(False)
connect = Button()
disconnect = Button()
def _connect_fired(self):
try:
connection = SerialManager(device=self.serial_device,
baudrate=self.baudrate,
sleep_after_connect=self.sleep_after_connect,
timeout=self.timeout)
connection.open()
print ArduinoApi(connection=connection).millis()
except Exception as e:
traceback.print_exc()
message(traceback.format_exc(), buttons=['OK'])
return
a = self.tree = ArduinoTree(connection=connection)
d = a.define.as_dict
s = [GuiDefine(name=k, value=str(v)) for k, v in d.items()]
s.sort(key=lambda x: x.name)
self.defines = s
self.digital_pins = [PinWrapper(pin=a.pin.get(x))
for x in a.pin.names_digital]
self.analog_pins = [PinWrapper(pin=a.pin.get(x))
for x in a.pin.names_analog]
self.pins = self.digital_pins + self.analog_pins
fw = a.firmware_info
self.arduino_version = fw.get('arduino_version')
self.firmware_build_time = str(fw.get('compile_datetime'))
self.avr_name = fw.get('avr_name')
self.gcc_version = fw.get('gcc_version')
self.libc_version = fw.get('libc_version')
self.libc_date = str(fw.get('libc_date'))
self.connected = True
def _disconnect_fired(self):
self.digital_pins = []
self.analog_pins = []
self.pins = []
self.defines = []
self.avr_name = ''
self.arduino_version = ''
self.firmware_build_time = ''
self.gcc_version = ''
self.libc_version = ''
self.libc_date = ''
self.tree.connection.close()
del self.tree
self.tree = None
self.connected = False
update_interval = Int(1000, desc='interval in msec')
update_enable = Bool(True)
def update(self):
if self.update_enable and self.connected and self.tree:
for x in self.pins:
x.update()
self.uptime = self.tree.api.millis() / 1000.0
self.vcc = self.tree.vcc.read() if self.tree.vcc else -1
time.sleep(self.update_interval / 1000.0)
traits_view = View(
Tabbed(
Group(
HGroup(
Group(
button('connect', enabled_when='not connected'),
button('disconnect', enabled_when='connected'),
Item(
'port_type', enabled_when='not connected', width=300,
),
Group(
'serial_device',
'baudrate',
'sleep_after_connect',
'timeout',
visible_when='port_type=="serial"',
enabled_when='not connected',
),
),
Group(
'avr_name',
'arduino_version',
'firmware_build_time',
'gcc_version',
'libc_version',
'libc_date',
# 'baudrate',
# 'sleep_after_connect',
# visible_when='port_type=="serial"',
springy=True,
),
),
label='connection',
),
Group(
'uptime',
'vcc',
label='misc',
),
Item(name='digital_pins',
editor=ListEditor(
style='custom',
),
style='readonly',
show_label=False,
),
Item(name='analog_pins',
editor=ListEditor(
style='custom',
),
style='readonly',
show_label=False,
),
Group(
'update_enable',
Item(name='update_interval',
editor=RangeEditor(
mode='slider',
low=1,
high=1000,
),
style='custom',
),
label='settings',
),
Item('defines',
show_label=False,
editor=ListEditor(
# auto_size=False,
# editable=False,
# configurable=False,
style='custom',
),
style='readonly',
)
),
width=800,
height=600,
buttons=['Undo', 'Revert', 'OK', 'Cancel'],
kind='live',
resizable=True,
handler=Handler(),
)
class CreateAcqpFileInputSpec(BaseInterfaceInputSpec):
total_readout = Float(0.0)
class PosteriorPlot(PyannoPlotContainer):
# data to be displayed
posterior = Array
### plot-related traits
plot_width = Float
def _plot_width_default(self):
return 450 if is_display_small() else 500
plot_height = Float
def _plot_height_default(self):
return 600 if is_display_small() else 750
colormap_low = Float(0.0)
colormap_high = Float(1.0)
origin = Str('top left')
plot_container = Instance(HPlotContainer)
plot_posterior = Instance(Plot)
def _create_colormap(self):
if self.colormap_low is None:
self.colormap_low = self.posterior.min()
if self.colormap_high is None:
self.colormap_high = self.posterior.max()
colormap = Reds(
DataRange1D(low=self.colormap_low, high=self.colormap_high))
return colormap
def _plot_container_default(self):
data = self.posterior
nannotations, nclasses = data.shape
# create a plot data object
plot_data = ArrayPlotData()
plot_data.set_data("values", data)
# create the plot
plot = Plot(plot_data, origin=self.origin)
img_plot = plot.img_plot("values",
interpolation='nearest',
xbounds=(0, nclasses),
ybounds=(0, nannotations),
colormap=self._create_colormap())[0]
ndisp = 55
img_plot.y_mapper.range.high = ndisp
img_plot.y_mapper.domain_limits = ((0, nannotations))
self._set_title(plot)
plot.padding_top = 80
# create x axis for labels
label_axis = self._create_increment_one_axis(plot, 0.5, nclasses,
'top')
label_axis.title = 'classes'
self._add_index_axis(plot, label_axis)
plot.y_axis.title = 'items'
# tweak plot aspect
goal_aspect_ratio = 2.0
plot_width = (goal_aspect_ratio * self.plot_height * nclasses / ndisp)
self.plot_width = min(max(plot_width, 200), 400)
plot.aspect_ratio = self.plot_width / self.plot_height
# add colorbar
colormap = img_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=img_plot,
orientation='v',
resizable='',
width=15,
height=250)
colorbar.padding_top = plot.padding_top
colorbar.padding_bottom = int(self.plot_height - colorbar.height -
plot.padding_top)
colorbar.padding_left = 0
colorbar.padding_right = 30
# create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
container.bgcolor = 0xFFFFFF # light gray: 0xEEEEEE
# add pan tools
img_plot.tools.append(
PanTool(img_plot,
constrain=True,
constrain_direction="y",
speed=7.))
self.decorate_plot(container, self.posterior)
self.plot_posterior = plot
return container
def add_markings(self,
mark_classes,
mark_name,
marker_shape,
delta_x,
delta_y,
marker_size=5,
line_width=1.,
marker_color='white'):
plot = self.plot_posterior
nannotations = plot.data.arrays['values'].shape[0]
y_name = mark_name + '_y'
x_name = mark_name + '_x'
valid = is_valid(mark_classes)
y_values = np.arange(nannotations)[valid] + delta_y + 0.5
x_values = mark_classes[valid].astype(float) + delta_x + 0.5
plot.data.set_data(y_name, y_values)
plot.data.set_data(x_name, x_values)
plot.plot((x_name, y_name),
type='scatter',
name=mark_name,
marker=marker_shape,
marker_size=marker_size,
color='transparent',
outline_color=marker_color,
line_width=line_width)
def remove_markings(self, mark_name):
self.plot_posterior.delplot(mark_name)
def _create_resizable_view(self):
# resizable_view factory, as I need to compute the height of the plot
# from the number of annotations, and I couldn't find any other way to
# do that
# "touch" posterior_plot to have it initialize
self.plot_container
if is_display_small():
height = 760
else:
height = 800
resizable_plot_item = (Item(
'plot_container',
editor=ComponentEditor(),
resizable=True,
show_label=False,
width=self.plot_width,
height=self.plot_height,
))
resizable_view = View(VGroup(
Include('instructions_group'),
resizable_plot_item,
),
width=450,
height=height,
resizable=True)
return resizable_view
def traits_view(self):
return self._create_resizable_view()
pan_instructions = Str
def _pan_instructions_default(self):
return 'Left-click and drag to navigate items'
instructions_group = VGroup(
HGroup(Spring(),
Item('instructions', style='readonly', show_label=False),
Spring()),
HGroup(Spring(),
Item('pan_instructions', style='readonly', show_label=False),
Spring()))
class MatrixPlot(PyannoPlotContainer):
# data to be displayed
matrix = Array
#### plot-related traits
colormap_low = Float(None)
colormap_high = Float(None)
origin = Str('top left')
matrix_plot_container = Instance(HPlotContainer)
def _create_colormap(self):
if self.colormap_low is None:
self.colormap_low = self.matrix.min()
if self.colormap_high is None:
self.colormap_high = self.matrix.max()
if self.colormap_low >= 0.0:
colormap_factory = Reds
else:
colormap_factory = reverse(RdBu)
colormap = colormap_factory(
DataRange1D(low=self.colormap_low, high=self.colormap_high))
return colormap
def _matrix_plot_container_default(self):
matrix = np.nan_to_num(self.matrix)
width = matrix.shape[0]
# create a plot data object and give it this data
plot_data = ArrayPlotData()
plot_data.set_data("values", matrix)
# create the plot
plot = Plot(plot_data, origin=self.origin)
img_plot = plot.img_plot("values",
interpolation='nearest',
xbounds=(0, width),
ybounds=(0, width),
colormap=self._create_colormap())[0]
#### fix axes
self._remove_grid_and_axes(plot)
axis = self._create_increment_one_axis(plot, 0.5, width, 'bottom')
self._add_value_axis(plot, axis)
axis = self._create_increment_one_axis(
plot,
0.5,
width,
'left',
ticks=[str(i) for i in range(width - 1, -1, -1)])
self._add_index_axis(plot, axis)
#### tweak plot attributes
self._set_title(plot)
plot.aspect_ratio = 1.
# padding [left, right, up, down]
plot.padding = [0, 0, 25, 25]
# create the colorbar, handing in the appropriate range and colormap
colormap = img_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=img_plot,
orientation='v',
resizable='v',
width=20,
padding=[0, 20, 0, 0])
colorbar.padding_top = plot.padding_top
colorbar.padding_bottom = plot.padding_bottom
# create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
container.bgcolor = 0xFFFFFF
self.decorate_plot(container, self.matrix)
return container
resizable_plot_item = Item('matrix_plot_container',
editor=ComponentEditor(),
resizable=True,
show_label=False,
width=600,
height=400)
traits_plot_item = Instance(Item)
def _traits_plot_item_default(self):
return Item('matrix_plot_container',
editor=ComponentEditor(),
resizable=False,
show_label=False,
height=-200,
width=-200)
class PinInfo(HasTraits):
pin_nr = PinTrait()
R = Float()
node = Any()
group = Str()
