Beispiel #1
0
def _create_plot_component():

    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    pd = ArrayPlotData(index = x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i,x))

    # Create some line plots of some of the data
    plot1 = Plot(pd, padding=50)
    plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")
    plot1.plot(("index", "y3"), name="j_3", color="blue")

    # Attach some tools to the plot
    plot1.tools.append(PanTool(plot1))
    zoom = ZoomTool(component=plot1, tool_mode="box", always_on=False)
    plot1.overlays.append(zoom)

    # Add the scrollbar
    hscrollbar = PlotScrollBar(component=plot1, axis="index", resizable="h",
                               height=15)
    plot1.padding_top = 0
    hscrollbar.force_data_update()

    # Create a container and add our plots
    container = VPlotContainer()
    container.add(plot1)
    container.add(hscrollbar)

    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 __init__(self):

        super(HHCurrentTraits, self).__init__()

        # gates
        self.vm = linspace(-120,65,1000)
        (M, N, H) = self.__gates()
        nA = self.__iv()
        self.gatedata = ArrayPlotData(x=self.vm, M=M, N=N, H=H)
        self.ivdata = ArrayPlotData(x=self.vm, nA=nA)
        
        gateplot = Plot(self.gatedata)
        gateplot.plot(("x", "M"), type = "line", color = "blue")
        gateplot.plot(("x", "N"), type = "line", color = "green")
        gateplot.plot(("x", "H"), type = "line", color = "red")

        ivplot = Plot(self.ivdata)
        ivplot.plot(("x", "nA"), type = "line", color = "black")

        container = VPlotContainer(ivplot, gateplot)
        container.spacing = 0
        gateplot.x_axis.orientation = "top"
        gateplot.padding_bottom = 0
        ivplot.padding_top = 0
        
        self.plots = container
Beispiel #4
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def _create_plot_component():

    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    pd = ArrayPlotData(index=x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i, x))

    # Create some line plots of some of the data
    plot1 = Plot(pd, padding=50)
    plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")
    plot1.plot(("index", "y3"), name="j_3", color="blue")

    # Attach some tools to the plot
    plot1.tools.append(PanTool(plot1))
    zoom = ZoomTool(component=plot1, tool_mode="box", always_on=False)
    plot1.overlays.append(zoom)

    # Add the scrollbar
    hscrollbar = PlotScrollBar(component=plot1,
                               axis="index",
                               resizable="h",
                               height=15)
    plot1.padding_top = 0
    hscrollbar.force_data_update()

    # Create a container and add our plots
    container = VPlotContainer()
    container.add(plot1)
    container.add(hscrollbar)

    return container
Beispiel #5
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    def _signals_plot_default(self):
        print('_signals_plot_default')
        """Create the Plot instance."""

        plot = Plot()

        plot.add(self.signals_renderer)

        x_axis = PlotAxis(component=plot,
                          mapper=self.signals_renderer.index_mapper,
                          orientation='bottom')
        # y_axis = PlotAxis(component=plot,
        #                     mapper=self.signals_renderer.value_mapper,
        #                     orientation='left')
        plot.overlays.extend([x_axis])

        plot.origin_axis_visible = False
        plot.padding_top = 0
        plot.padding_left = 0
        plot.padding_right = 0
        plot.padding_bottom = 50
        plot.border_visible = False
        plot.bgcolor = "white"
        plot.use_downsampling = True
        return plot
Beispiel #6
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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 __init__(self, ExprmntVm=None, ExprmntnA=None):

        super(HHCurrentTraits, self).__init__()
        # gates
        self.vm = linspace(-120,65,1000)
        ((MCur1,NCur1,HCur1),(MCur2,NCur2,HCur2)) = self.__gates()
        self.Cur1gatedata = ArrayPlotData(x=self.vm, M=MCur1, N=NCur1, H=HCur1)
        self.Cur2gatedata = ArrayPlotData(x=self.vm, M=MCur2, N=NCur2, H=HCur2)

        Cur1gatesplot = Plot(self.Cur1gatedata)
        Cur1gatesplot.plot(("x", "M"), type = "line", color = "blue")
        Cur1gatesplot.plot(("x", "N"), type = "line", color = "green")
        Cur1gatesplot.plot(("x", "H"), type = "line", color = "red")

        Cur2gatesplot = Plot(self.Cur2gatedata)
        Cur2gatesplot.plot(("x", "M"), type = "line", color = "blue")
        Cur2gatesplot.plot(("x", "N"), type = "line", color = "green")
        Cur2gatesplot.plot(("x", "H"), type = "line", color = "red")

        (Cur1,Cur2) = self.__iv()
        self.ivdata = ArrayPlotData(x=self.vm, nA1=Cur1, nA2=Cur2, combin=Cur1+Cur2)
        ivplot = Plot(self.ivdata)
        ivplot.plot(("x", "nA1"), type = "line", color = "blue")
        ivplot.plot(("x", "nA2"), type = "line", color = "green")
        ivplot.plot(("x", "combin"), type = "line", color = "black")
        
        if ExprmntVm is not None:
            self.ivdata.set_data('ExptVm',ExprmntVm)
            self.ivdata.set_data('ExptnA',ExprmntnA)
            ivplot.plot(("ExptVm", "ExptnA"),
                        type = "scatter", color = "red", marker_size = 5)


        self.plots = VPlotContainer(ivplot, Cur2gatesplot, Cur1gatesplot)
        self.plots.spacing = 0
        ivplot.padding_top = 0
        Cur1gatesplot.padding_bottom = 0
        Cur2gatesplot.padding_top = 0

        self.write_button = Button(label="Print_Pars")
Beispiel #8
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    def intensity_histogram_plot_component(self):

        data = ArrayPlotData(x=self.bin_edges, y=self.hist)

        plot = Plot(data)
        plot.plot(
            ('x', "y"),
            type='bar',
            color='auto',
            bar_width=1,
        )
        # without padding plot just doesn't seem to show up?
        plot.border_width = 0
        plot.padding = 0
        plot.padding_top = 0
        return plot
def _create_plot_component():

    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    pd = ArrayPlotData(index=x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i, x))

    # Create some line plots of some of the data
    plot1 = Plot(pd)
    plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")

    # Tweak some of the plot properties
    plot1.title = "My First Line Plot"
    plot1.padding = 50
    plot1.padding_top = 75
    plot1.legend.visible = True

    x = linspace(-5, 15.0, 100)
    y = jn(5, x)
    foreign_plot = create_line_plot((x, y),
                                    color=tuple(COLOR_PALETTE[0]),
                                    width=2.0)
    left, bottom = add_default_axes(foreign_plot)
    left.orientation = "right"
    bottom.orientation = "top"
    plot1.add(foreign_plot)

    # Attach some tools to the plot
    broadcaster = BroadcasterTool()
    broadcaster.tools.append(PanTool(plot1))
    broadcaster.tools.append(PanTool(foreign_plot))

    for c in (plot1, foreign_plot):
        zoom = ZoomTool(component=c, tool_mode="box", always_on=False)
        broadcaster.tools.append(zoom)

    plot1.tools.append(broadcaster)

    return plot1
Beispiel #10
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def _create_plot_component():

    # Create some x-y data series to plot
    x = linspace(-2.0, 10.0, 100)
    pd = ArrayPlotData(index = x)
    for i in range(5):
        pd.set_data("y" + str(i), jn(i,x))

    # Create some line plots of some of the data
    plot1 = Plot(pd)
    plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")

    # Tweak some of the plot properties
    plot1.title = "My First Line Plot"
    plot1.padding = 50
    plot1.padding_top = 75
    plot1.legend.visible = True

    x = linspace(-5, 15.0, 100)
    y = jn(5, x)
    foreign_plot = create_line_plot((x,y), color=tuple(COLOR_PALETTE[0]), width=2.0)
    left, bottom = add_default_axes(foreign_plot)
    left.orientation = "right"
    bottom.orientation = "top"
    plot1.add(foreign_plot)

    # Attach some tools to the plot
    broadcaster = BroadcasterTool()
    broadcaster.tools.append(PanTool(plot1))
    broadcaster.tools.append(PanTool(foreign_plot))

    for c in (plot1, foreign_plot):
        zoom = ZoomTool(component=c, tool_mode="box", always_on=False)
        broadcaster.tools.append(zoom)

    plot1.tools.append(broadcaster)

    return plot1
Beispiel #11
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def _create_plot_component():
    army_lat = np.column_stack([army['start_lat'],
                                army['end_lat']]).reshape(-1)
    army_lon = np.column_stack([army['start_lon'],
                                army['end_lon']]).reshape(-1)

    plot_data = ArrayPlotData(
        army_lon=army_lon,
        army_lat=army_lat,
        army_size=army['size'],
        army_color=army['direction'] * army["group"],
        towns_lat=towns['lat'],
        towns_lon=towns['lon'],
        towns=towns['town'],
        temp_lon=temperatures['lon'],
        temp=temperatures['temp'],
        temp_date=temperatures['date'],
    )

    map_plot = Plot(plot_data)
    map_plot.x_grid = None
    map_plot.y_grid = None
    map_plot.x_axis.orientation = 'top'
    map_plot.x_axis.title = 'Longitude'
    map_plot.y_axis.title = 'Latitude'
    map_plot.title = "Minard's Map of Napoleon's Russian Campaign"
    map_plot._title.overlay_position = "inside top"
    map_plot._title.hjustify = "left"
    map_plot._title.vjustify = "bottom"
    map_plot.plot(
        ("army_lon", "army_lat", "army_color", "army_size"),
        type="cmap_segment",
        name="my_plot",
        color_mapper=viridis,
        border_visible=True,
        bgcolor="white",
        size_min=1.0,
        size_max=128.0,
    )
    map_plot.plot(
        ("towns_lon", "towns_lat"),
        type="scatter",
    )
    map_plot.plot(
        ("towns_lon", "towns_lat", "towns"),
        type="text",
        text_margin=4,
        h_position='right',
        text_offset=(4, 0),
    )
    map_plot.plot_1d(
        ('temp_lon'),
        type='line_scatter_1d',
        alpha=0.5,
        line_style='dot',
    )
    map_plot.index_range.high_setting = 38
    map_plot.index_range.low_setting = 23
    map_plot.value_range.high_setting = 56.0
    map_plot.value_range.low_setting = 53.5
    map_plot.tools.extend([
        PanTool(map_plot),
        ZoomTool(map_plot),
    ])

    temp_plot = Plot(plot_data, height=100)
    temp_plot.index_range = map_plot.index_range
    temp_plot.x_grid = None
    temp_plot.x_axis = None
    temp_plot.y_axis.orientation = 'right'
    temp_plot.y_axis.title = u'Temp (°Re)'
    temp_plot.plot(
        ('temp_lon', 'temp'),
        type='line',
    )
    temp_plot.plot_1d(
        ('temp_lon'),
        type='line_scatter_1d',
        alpha=0.5,
        line_style='dot',
    )
    temp_plot.plot_1d(
        ('temp_lon', 'temp_date'),
        type='textplot_1d',
        alpha=0.5,
        line_style='dot',
        alignment='bottom',
    )
    temp_plot.value_range.high_setting = 5
    temp_plot.value_range.low_setting = -35

    container = VPlotContainer(temp_plot, map_plot)
    container.spacing = 0
    map_plot.padding_bottom = 0
    map_plot.padding_left = 70
    map_plot.padding_right = 70
    map_plot.padding_top = 50
    temp_plot.padding_top = 0
    temp_plot.padding_bottom = 15
    temp_plot.padding_right = 70
    temp_plot.padding_left = 70
    temp_plot.height = 100
    temp_plot.resizable = 'h'

    return container