我们从Python开源项目中，提取了以下6个代码示例，用于说明如何使用ipywidgets.interactive()。
def widgetify(fun, layout=None, manual=False, **kwargs): f = fun if manual: app = ipywidgets.interact_manual(f, **kwargs) app = app.widget else: app = ipywidgets.interactive(f, **kwargs) # if layout is None: # TODO: add support for changing layouts w = MyApp(app.children, kwargs) f.widget = w # defaults = #dict([(key, val.value) for key, val in kwargs.iteritems() if isinstance(val, Widget)]) app.update() #app.on_displayed(f(**(w.kwargs))) return w
def ImageUXOWidget(): Out = interactive(fcnImageUXOWidget,psi=FloatSlider(min=-180., max=180., value=-0., step=10., continuous_update=False, description = "$\psi$"),\ theta=FloatSlider(min=0, max=180., value=-0., step=10., continuous_update=False, description = "$\\theta$"),\ phi=FloatSlider(min=-180., max=180., value=-0., step=10., continuous_update=False, description = "$\phi$"),\ k1=FloatSlider(min=1., max=3., value=1., step=0.1, continuous_update=False, description = "$k_{x'}$"),\ alpha1=FloatSlider(min=-4., max=-2., value=-3.7, step=0.1, continuous_update=False, description = "log($\\alpha_{x'}$)"),\ beta1=FloatSlider(min=1., max=2., value=1., step=0.1, continuous_update=False, description = "$\\beta_{x'}$"),\ gamma1=FloatSlider(min=-4., max=-2., value=-2.7, step=0.1, continuous_update=False, description = "log($\gamma_{x'}$)"),\ k2=FloatSlider(min=1., max=3., value=1.5, step=0.1, continuous_update=False, description = "$k_{y'}$"),\ alpha2=FloatSlider(min=-4., max=-2., value=-3.7, step=0.1, continuous_update=False, description = "log($\\alpha_{y'}$)"),\ beta2=FloatSlider(min=1., max=2., value=-1., step=0.1, continuous_update=False, description = "$\\beta_{y'}$"),\ gamma2=FloatSlider(min=-4., max=-2., value=-2.5, step=0.1, continuous_update=False, description = "log($\gamma_{y'}$)"),\ k3=FloatSlider(min=1., max=3., value=2., step=0.1, continuous_update=False, description = "$k_{z'}$"),\ alpha3=FloatSlider(min=-4., max=-2., value=-3.2, step=0.1, continuous_update=False, description = "log($\\alpha_{z'}$)"),\ beta3=FloatSlider(min=1., max=2., value=1., step=0.1, continuous_update=False, description = "$\\beta_{z'}$"),\ gamma3=FloatSlider(min=-4., max=-2., value=-2.2, step=0.1, continuous_update=False, description = "log($\gamma_{z'}$)"),\ tn=IntSlider(min=1, max=11, value=1., step=1, continuous_update=False, description = "Time channel")) return Out
def run_spiralInteractive(inData, period, pParams = [], inIndex = None, mainTitle = 'Spiral plot', barLabel = 'Amplitude', plotTS = False): ''' Wrapper for plot_spiral that is interactive when used in Jupyter notebooks @param inData: Input data to use in plot @param period: Period value with which to wrap data around the plot @param pParams: List of plot's period parameters [min, max, step] necessary for interactive @param inIndex: Input index (series time coordinates) @param plotTS: Optional flag to plot the time series of the data in a separate window ''' from ipywidgets import fixed, interact, interactive from IPython.display import clear_output, display, HTML plotData, plotIndex = mod_data(inData, inIndex) if len(pParams) != 3: pParams = [period - .1, period + .1, .01] inter = interactive(plot_spiral, plotData = fixed(plotData), plotIndex = fixed(plotIndex), mainTitle = fixed(mainTitle), barLabel = fixed(barLabel), plotTS = fixed(plotTS), T = (pParams[0], pParams[1], pParams[2])) display(inter)
def __call__(self): init = 'x' self.position_options = {'x': self.solver.xmesh, 'z': self.solver.zmesh} self.position_formatter = widgets.Dropdown(options=self.position_options[init], description='Lineout Intercept') z_axis_options = OrderedDict() z_axis_options['E_x'] = 0 z_axis_options['E_z'] = 1 z_axis_options['Potential'] = 2 z_axis_formatter = widgets.Dropdown(options=z_axis_options, description='Field Data') x_axis_options = OrderedDict() x_axis_options['x'] = 0 x_axis_options['z'] = 1 x_axis_formatter = widgets.Dropdown(options=x_axis_options, description='Lineout Axis') p1 = interactive(self._plot_lineout, x=x_axis_formatter, position=self.position_formatter, y=z_axis_formatter) display(p1)
def interactive(img, cmap='gray', window=(2, 98)): import ipywidgets as ipy # Get some information about the image bbox = Box.fromMask(img) window_vals = np.nanpercentile(img.get_data(), window) # Setup figure fig, axes = plt.subplots(1, 3, figsize=(8, 4)) implots = [None, None, None] for i in range(3): sl = Slice(bbox, bbox.center, i, 256, orient='clin') sl_img = sl.sample(img, order=0) sl_color = colorize(sl_img, cmap, window_vals) implots[i] = axes[i].imshow(sl_color, origin='lower', extent=sl.extent, cmap=cmap, vmin = 0.1) axes[i].axis('off') def wrap_sections(x, y, z): for i in range(3): sl = Slice(bbox, np.array((x, y, z)), i, 256, orient='clin') sl_img = sl.sample(img, order=0) sl_color = colorize(sl_img, cmap, window_vals) implots[i].set_data(sl_color) plt.show() # Setup widgets slider_x = ipy.FloatSlider(min=bbox.start[0], max=bbox.end[0], value=bbox.center[0]) slider_y = ipy.FloatSlider(min=bbox.start[1], max=bbox.end[1], value=bbox.center[1]) slider_z = ipy.FloatSlider(min=bbox.start[2], max=bbox.end[2], value=bbox.center[2]) widgets = ipy.interactive(wrap_sections, x=slider_x, y=slider_y, z=slider_z) # Now do some manual layout hbox = ipy.HBox(widgets.children[0:3]) # Set the sliders to horizontal layout vbox = ipy.VBox((hbox, widgets.children[3])) # iplot.widget.children[-1].layout.height = '350px' return vbox
def __init__(self, solver, field_data, potential_data): """ Initialize instance of the interactive plotter Args: solver: Instance of a Warp FieldSolver object field_data: Array of 3D field data (vector component, nx, nz). potential_data: Array of field data (nx, nz). """ self.solver = solver self.field_data = field_data self.potential_data = potential_data
