def _plot_default(self):
# Create a GridContainer to hold all of our plots: 2 rows, 4 columns:
container = GridContainer(fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(2, 4))
arrangements = [('top left', 'h'),
('top right', 'h'),
('top left', 'v'),
('top right', 'v'),
('bottom left', 'h'),
('bottom right', 'h'),
('bottom left', 'v'),
('bottom right', 'v')]
orientation_name = {'h': 'horizontal', 'v': 'vertical'}
pd = ArrayPlotData(image=lena())
# Plot some bessel functions and add the plots to our container
for origin, orientation in arrangements:
plot = Plot(pd, default_origin=origin, orientation=orientation)
plot.img_plot('image')
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
title = '{0}, {1}'
plot.title = title.format(orientation_name[orientation],
origin.replace(' ', '-'))
# Add to the grid container
container.add(plot)
return container
def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=20, fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(3,3), spacing=(12,12))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index = x)
# Plot some bessel functions and add the plots to our container
for i in range(9):
pd.set_data("y" + str(i), jn(i,x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]), line_width=2.0,
bgcolor = "white", border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 10
# Set each plot's aspect ratio based on its position in the
# 3x3 grid of plots.
n,m = divmod(i, 3)
plot.aspect_ratio = float(n+1) / (m+1)
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
return container
def _create_plot_component():
# Create a GridContainer to hold all of our plots: 2 rows, 3 columns:
container = GridContainer(padding=40,
fill_padding=True,
bgcolor="lightgray",
use_backbuffer=True,
shape=(2, 3),
spacing=(20, 20))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index=x)
# Plot some bessel functions and add the plots to our container
for i in range(6):
pd.set_data("y" + str(i), jn(i, x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]),
line_width=2.0,
bgcolor="white",
border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 0
plot.padding_top = 30
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container (
container.add(plot)
# Set the upper-left plot to only be resizable vertically, and to have a
# fixed horizontal width. This also constrains the width of the first column.
ul_plot = container.components[0]
ul_plot.set(resizable="v", width=200)
ul_plot.overlays.append(
PlotLabel("Not horizontally resizable", component=ul_plot))
# Set the bottom center plot to have a fixed width and height.
# This also constrains the height of the bottom row and the width of
# the middle column.
cplot = container.components[4]
cplot.set(resizable="", bounds=[400, 400])
cplot.overlays.append(PlotLabel("Not resizable", component=cplot))
container.padding_top = 50
container.overlays.append(
PlotLabel(
'Resize the window - some plots resize, others cannot '
'(see source code)',
component=container,
font="swiss 16",
overlay_position="top"))
return container
def test_nonresizable_container(self):
cont = GridContainer(shape=(1, 1), resizable="")
comp1 = StaticPlotComponent([200, 300])
cont.add(comp1)
cont.do_layout()
self.assert_tuple(comp1.position, (0, 0))
self.assert_tuple(comp1.bounds, (200, 300))
return
def test_nonresizable_container(self):
cont = GridContainer(shape=(1,1), resizable="")
comp1 = StaticPlotComponent([200,300])
cont.add(comp1)
cont.do_layout()
self.assert_tuple(comp1.position, (0,0))
self.assert_tuple(comp1.bounds, (200,300))
return
def test_single_cell(self):
cont = GridContainer(shape=(1,1))
comp1 = StaticPlotComponent([200,300])
cont.add(comp1)
cont.do_layout()
# it would be nice to make all boolean tests here trigger
# assert failures, maybe using Pypy?
self.assert_tuple(comp1.position, (0,0))
self.assert_tuple(comp1.bounds, (200,300))
return
def test_single_cell(self):
cont = GridContainer(shape=(1, 1))
comp1 = StaticPlotComponent([200, 300])
cont.add(comp1)
cont.do_layout()
# it would be nice to make all boolean tests here trigger
# assert failures, maybe using Pypy?
self.assert_tuple(comp1.position, (0, 0))
self.assert_tuple(comp1.bounds, (200, 300))
return
def _create_plot_component():
# Create a GridContainer to hold all of our plots: 2 rows, 3 columns:
container = GridContainer(padding=40, fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(2,3), spacing=(20,20))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index = x)
# Plot some bessel functions and add the plots to our container
for i in range(6):
pd.set_data("y" + str(i), jn(i,x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]), line_width=2.0,
bgcolor = "white", border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 0
plot.padding_top = 30
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container (
container.add(plot)
# Set the upper-left plot to only be resizable vertically, and to have a
# fixed horizontal width. This also constrains the width of the first column.
ul_plot = container.components[0]
ul_plot.set(resizable="v", width=200)
ul_plot.overlays.append(PlotLabel("Not horizontally resizable",
component=ul_plot))
# Set the bottom center plot to have a fixed width and height.
# This also constrains the height of the bottom row and the width of
# the middle column.
cplot = container.components[4]
cplot.set(resizable="", bounds=[400,400])
cplot.overlays.append(PlotLabel("Not resizable", component=cplot))
container.padding_top = 50
container.overlays.append(
PlotLabel('Resize the window - some plots resize, others cannot '
'(see source code)',
component=container,
font = "swiss 16",
overlay_position = "top"))
return container
def updateImageContainer(self):
container = GridContainer(bgcolor="transparent", shape=(1,1),
use_backbuffer=True)
self.imagecontainer = container
cont = getattr(self.pyxda, 'imageplot')
if cont in container._components:
container.remove(cont)
container.add(cont)
container.get_preferred_size()
container.invalidate_draw()
return
def get_plots(self): #return [p.plothandle for p in self.plots] gc = GridContainer(padding=20, fill_padding=True, bgcolor='lightgray', use_backbuffer=True, shape=(3,3), spacing=(10,10)) [gc.add(p.plothandle) for p in self.plots] return gc
def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=40, fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(2,3), spacing=(20,20))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index = x)
# Plot some bessel functions and add the plots to our container
for i in range(6):
pd.set_data("y" + str(i), jn(i,x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]), line_width=2.0,
bgcolor = "white", border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 0
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
# Set the upper-left plot to only be resizable vertically, and to have
# a fixed horizontal width
ul_plot = container.components[0]
ul_plot.set(resizable="v", padding_top=30, width=200)
ul_plot.overlays.append(PlotLabel("Vertically resizable",
component=ul_plot))
# Set the bottom center plot to have a fixed width and height
cplot = container.components[4]
cplot.set(resizable="", padding_top = 30, bounds=[400,400])
cplot.overlays.append(PlotLabel("Not resizable", component=cplot))
return container
def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=20,
fill_padding=True,
bgcolor="lightgray",
use_backbuffer=True,
shape=(3, 3),
spacing=(12, 12))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index=x)
# Plot some bessel functions and add the plots to our container
for i in range(9):
pd.set_data("y" + str(i), jn(i, x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]),
line_width=2.0,
bgcolor="white",
border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 10
# Set each plot's aspect ratio based on its position in the
# 3x3 grid of plots.
n, m = divmod(i, 3)
plot.aspect_ratio = float(n + 1) / (m + 1)
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
return container
def test_row(self):
cont = GridContainer(shape=(1,3), halign="center", valign="center")
c1 = StaticPlotComponent([50,50])
c2 = StaticPlotComponent([30,30])
c3 = StaticPlotComponent([0,0], resizable="hv")
cont.add(c1, c2, c3)
cont.bounds = list(cont.get_preferred_size())
cont.do_layout()
self.assert_tuple(c1.position, (0,0))
self.assert_tuple(c1.bounds, (50,50))
self.assert_tuple(c2.position, (50,10))
self.assert_tuple(c2.bounds, (30,30))
self.assert_tuple(c3.position, (80,0))
self.assert_tuple(c3.bounds, (0,50))
cont.bounds = [100, 50]
cont.do_layout()
self.assert_tuple(c1.position, (0,0))
self.assert_tuple(c1.bounds, (50,50))
self.assert_tuple(c2.position, (50,10))
self.assert_tuple(c2.bounds, (30,30))
self.assert_tuple(c3.position, (80,0))
self.assert_tuple(c3.bounds, (20,50))
return
def test_row(self):
cont = GridContainer(shape=(1, 3), halign="center", valign="center")
c1 = StaticPlotComponent([50, 50])
c2 = StaticPlotComponent([30, 30])
c3 = StaticPlotComponent([0, 0], resizable="hv")
cont.add(c1, c2, c3)
cont.bounds = list(cont.get_preferred_size())
cont.do_layout()
self.assert_tuple(c1.position, (0, 0))
self.assert_tuple(c1.bounds, (50, 50))
self.assert_tuple(c2.position, (50, 10))
self.assert_tuple(c2.bounds, (30, 30))
self.assert_tuple(c3.position, (80, 0))
self.assert_tuple(c3.bounds, (0, 50))
cont.bounds = [100, 50]
cont.do_layout()
self.assert_tuple(c1.position, (0, 0))
self.assert_tuple(c1.bounds, (50, 50))
self.assert_tuple(c2.position, (50, 10))
self.assert_tuple(c2.bounds, (30, 30))
self.assert_tuple(c3.position, (80, 0))
self.assert_tuple(c3.bounds, (20, 50))
return
def build_plot(self):
global plotdata # FIXME: Don't use global!
onearray = Array
onearray = sp.ones(self.indata.shape[0])
minuses = onearray * (-1.)
# Define index array for fit function:
self.mod_x = sp.arange(self.line_center - 50.,
self.line_center + 50., .01)
self.Model = sp.zeros(self.mod_x.shape[0])
# Establish continuum array in a way that opens for other, more
# elaborate continua.
self.contarray = sp.ones(self.mod_x.shape[0]) * \
self.Components['Contin']
self.y = {}
for comp in self.CompoList:
self.y[comp] = stats.norm.pdf(
self.mod_x,
self.Components[comp][0] + self.line_center,
self.Components[comp][1]
) * self.Components[comp][1] * sp.sqrt(2. * sp.pi) * \
self.Components[comp][2]
self.Model = self.contarray + self.y[self.select]
broca = BroadcasterTool()
# Define the part of the data to show in initial view:
plotrange = sp.where((self.x > self.line_center - 20) &
(self.x < self.line_center + 20))
# Define the y axis max value in initial view (can be panned/zoomed):
maxval = float(self.indata[plotrange].max() * 1.1)
minval = maxval / 15.
maxerr = self.errs[plotrange].max() * 1.3
resmin = max(self.Resids[plotrange].max(), 5.) * 1.2
cenx = sp.array([self.line_center, self.line_center])
ceny = sp.array([-minval, maxval])
cenz = sp.array([-maxval, maxval])
# Build plot of data and model
plotdata = ArrayPlotData(
wl=self.x,
data=self.indata,
xs=self.mod_x,
cont=self.contarray,
ones=onearray,
minus=minuses,
model=self.Model,
errors=self.errs,
ceny=ceny,
cenz=cenz,
cenx=cenx,
Residuals=self.Resids,
)
for comp in self.CompoList:
plotdata.set_data(comp, self.y[comp])
olplot = GridContainer(shape=(2, 1), padding=10,
fill_padding=True,
bgcolor='transparent',
spacing=(5, 10))
plot = Plot(plotdata)
plot.y_axis.title = 'Flux density'
resplot = Plot(plotdata, tick_visible=True, y_auto=True)
resplot.x_axis.title = u'Wavelength [Å]'
resplot.y_axis.title = u'Residuals/std. err.'
# Create initial plot: Spectrum data, default first component,
# default total line profile.
self.comprenders = []
self.datarender = plot.plot(('wl', 'data'), color='black',
name='Data',
render_style='connectedhold')
self.contrender = plot.plot(('xs', 'cont'), color='darkgray',
name='Cont')
self.modlrender = plot.plot(('xs', 'model'), color='blue',
line_width=1.6, name='Model')
self.centrender = plot.plot(('cenx', 'ceny'),
color='black',
type='line',
line_style='dot',
name='Line center',
line_width=1.)
# There may be an arbitrary number of gaussian components, so:
for comp in self.CompoList:
self.comprenders.append(
plot.plot(('xs', comp),
type='line',
#color='auto',
color=tuple(COLOR_PALETTE[self.CompNum]),
line_style='dash',
name=comp)
)
# Create panel with residuals:
resplot.plot(('wl', 'Residuals'), color='black', name='Resids')
resplot.plot(('wl', 'ones'), color='green')
resplot.plot(('wl', 'minus'), color='green')
resplot.plot(('cenx', 'cenz'), color='red',
type='line',
line_style='dot',
line_width=.5)
plot.x_axis.visible = False
# Set ranges to change automatically when plot values change.
plot.value_range.low_setting,\
plot.value_range.high_setting = (-minval, maxval)
plot.index_range.low_setting,\
plot.index_range.high_setting = (self.line_center - 20.,
self.line_center + 20.)
resplot.value_range.low_setting,\
resplot.value_range.high_setting = (-resmin, resmin)
resplot.index_range.low_setting,\
resplot.index_range.high_setting = (plot.index_range.low_setting,
plot.index_range.high_setting)
#resplot.index_range = plot.index_range # Yes or no? FIXME
plot.overlays.append(ZoomTool(plot, tool_mode='box',
drag_button='left',
always_on=False))
resplot.overlays.append(ZoomTool(resplot, tool_mode='range',
drag_button='left',
always_on=False))
# List of renderers to tell the legend what to write
self.plots['Contin'] = self.contrender
self.plots['Center'] = self.centrender
self.plots['Model'] = self.modlrender
for i in sp.arange(len(self.comprenders)):
self.plots[self.CompoList[i]] = self.comprenders[i]
# Build Legend:
legend = Legend(component=plot, padding=10, align="ur")
legend.tools.append(LegendTool(legend, drag_button="right"))
legend.plots = self.plots
plot.overlays.append(legend)
olplot.tools.append(broca)
pan = PanTool(plot)
respan = PanTool(resplot, constrain=True, constrain_direction='x')
broca.tools.append(pan)
broca.tools.append(respan)
plot.overlays.append(ZoomTool(plot, tool_mode='box',
always_on=False))
olplot.add(plot)
olplot.add(resplot)
olplot.components[0].set(resizable='hv', bounds=[500, 400])
olplot.components[1].set(resizable='h', bounds=[500, 100])
self.plot = plot
self.resplot = resplot
self.plwin = olplot
self.legend = legend
self.plotrange = plotrange
def _create_plot_component(): container = GridContainer(padding=40, fill_padding=True, bgcolor="lightgray", use_backbuffer=True, shape=(3,3), spacing=(10,10)) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-5,90)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Roll (degrees)", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-5,90)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Pitch (degrees)", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-5,365)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Yaw (degrees)", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-100,100)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Gyro X", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-100,100)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Gyro Y", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-100,100)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Gyro Z", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) x = arange(100) y = arange(100) plot = create_line_plot((x,y), color="red", width=2.0, index_bounds=(-5,100), value_bounds=(-1,35)) plot.padding = 50 plot.fill_padding = True plot.bgcolor = "white" left, bottom = add_default_axes(plot, vtitle="Battery Voltage (V)", htitle="Time (s)") hgrid, vgrid = add_default_grids(plot) bottom.tick_interval = 20.0 vgrid.grid_interval = 10.0 container.add(plot) return container
def build_plot(self):
print 'Building plot...'
fitrange = self.fitrange # Just for convenience
onearray = Array
onearray = sp.ones(self.indata.shape[0])
minuses = onearray * (-1.)
# Define index array for fit function:
self.mod_x = sp.arange(self.line_center - 50., self.line_center + 50.,
.01)
self.Model = sp.zeros(self.mod_x.shape[0])
# Establish continuum array in a way that opens for other, more
# elaborate continua.
self.contarray = sp.ones(self.mod_x.shape[0]) * \
self.Components['Contin'][0]
self.y = {}
for comp in self.CompoList:
self.y[comp] = gauss( # x, mu, sigma, amplitude
self.mod_x, self.Components[comp][0] + self.line_center,
self.Components[comp][1], self.Components[comp][2])
self.Model = self.contarray + self.y[self.select]
broca = BroadcasterTool()
# Define the part of the data to show in initial view:
plotrange = sp.where((self.x > self.line_center - 30)
& (self.x < self.line_center + 30))
# Define the y axis max value in initial view (can be panned/zoomed):
maxval = float(self.indata[fitrange].max() * 1.2)
minval = maxval / 15.
minval = abs(np.median(self.indata[fitrange])) * 1.5
maxerr = self.errs[fitrange].max() * 1.3
resmin = max(sp.absolute(self.Resids[self.fitrange]).max(), 5.) * 1.2
cenx = sp.array([self.line_center, self.line_center])
ceny = sp.array([-minval, maxval])
cenz = sp.array([-maxval, maxval])
# Gray shading of ignored ranges
rangelist = np.array(self.rangelist)
grayx = np.array(rangelist.flatten().repeat(2))
grayx = np.hstack((self.x.min(), grayx, self.x.max()))
grayy = np.ones_like(grayx) * self.indata.max() * 2.
grayy[1::4] = -grayy[1::4]
grayy[2::4] = -grayy[2::4]
grayy = np.hstack((grayy[-1], grayy[:-1]))
# Build plot of data and model
self.plotdata = ArrayPlotData(
wl=self.x,
data=self.indata,
xs=self.mod_x,
cont=self.contarray,
ones=onearray,
minus=minuses,
model=self.Model,
errors=self.errs,
ceny=ceny,
cenz=cenz,
cenx=cenx,
Residuals=self.Resids,
grayx=grayx,
grayy=grayy,
)
# Add dynamically created components to plotdata
for comp in self.CompoList:
self.plotdata.set_data(comp, self.y[comp])
olplot = GridContainer(shape=(2, 1),
padding=10,
fill_padding=True,
bgcolor='transparent',
spacing=(5, 10))
plot = Plot(self.plotdata)
plot.y_axis.title = 'Flux density'
resplot = Plot(self.plotdata, tick_visible=True, y_auto=True)
resplot.x_axis.title = u'Wavelength [Å]'
resplot.y_axis.title = u'Residuals/std. err.'
# Create initial plot: Spectrum data, default first component,
# default total line profile.
self.comprenders = []
self.datarender = plot.plot(('wl', 'data'),
color='black',
name='Data',
render_style='connectedhold')
self.contrender = plot.plot(('xs', 'cont'),
color='darkgray',
name='Cont')
self.modlrender = plot.plot(('xs', 'model'),
color='blue',
line_width=1.6,
name='Model')
self.centrender = plot.plot(('cenx', 'ceny'),
color='black',
type='line',
line_style='dot',
name='Line center',
line_width=1.)
self.rangrender = plot.plot(
('grayx', 'grayy'),
type='polygon',
face_color='lightgray',
edge_color='gray',
face_alpha=0.3,
alpha=0.3,
)
# There may be an arbitrary number of gaussian components, so:
print 'Updating model'
for comp in self.CompoList:
self.comprenders.append(
plot.plot(
('xs', comp),
type='line',
color=Paired[self.Components[comp]
[3]], # tuple(COLOR_PALETTE[self.CompNum]),
line_color=Paired[self.Components[comp][
3]], # tuple(COLOR_PALETTE[self.CompNum]),
line_style='dash',
name=comp))
# Create panel with residuals:
resplot.plot(('wl', 'Residuals'), color='black', name='Resids')
resplot.plot(('wl', 'ones'), color='green')
resplot.plot(('wl', 'minus'), color='green')
resplot.plot(('cenx', 'cenz'),
color='red',
type='line',
line_style='dot',
line_width=.5)
resplot.plot(
('grayx', 'grayy'), # Yes, that one again
type='polygon',
face_color='lightgray',
edge_color='gray',
face_alpha=0.3,
alpha=0.3,
)
plot.x_axis.visible = False
# Set ranges to change automatically when plot values change.
plot.value_range.low_setting,\
plot.value_range.high_setting = (-minval, maxval)
plot.index_range.low_setting,\
plot.index_range.high_setting = (self.line_center - 30.,
self.line_center + 30.)
resplot.value_range.low_setting,\
resplot.value_range.high_setting = (-resmin, resmin)
resplot.index_range.low_setting,\
resplot.index_range.high_setting = (plot.index_range.low_setting,
plot.index_range.high_setting)
#resplot.index_range = plot.index_range # Yes or no? FIXME
plot.overlays.append(
ZoomTool(plot,
tool_mode='box',
drag_button='left',
always_on=False))
resplot.overlays.append(
ZoomTool(resplot,
tool_mode='range',
drag_button='left',
always_on=False))
# List of renderers to tell the legend what to write
self.plots['Contin'] = self.contrender
self.plots['Center'] = self.centrender
self.plots['Model'] = self.modlrender
for i in sp.arange(len(self.comprenders)):
self.plots[self.CompoList[i]] = self.comprenders[i]
# Build Legend:
legend = Legend(component=plot, padding=10, align="ur")
legend.tools.append(LegendTool(legend, drag_button="right"))
legend.plots = self.plots
plot.overlays.append(legend)
olplot.tools.append(broca)
pan = PanTool(plot)
respan = PanTool(resplot, constrain=True, constrain_direction='x')
broca.tools.append(pan)
broca.tools.append(respan)
plot.overlays.append(ZoomTool(plot, tool_mode='box', always_on=False))
olplot.add(plot)
olplot.add(resplot)
olplot.components[0].set(resizable='hv', bounds=[500, 400])
olplot.components[1].set(resizable='h', bounds=[500, 100])
self.plot = plot
self.resplot = resplot
self.plwin = olplot
self.legend = legend
self.plotrange = plotrange