Esempio n. 1
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    def interactive_figure(self):
        """Add interactivity, ie. the option to show/hide lines to the figure."""

        lines = self.plot_figure()  # Generates a list of lines
        labels = [line for line in lines.keys()]  # Prepare a list of labels for the tickboxes
        lineNames = ['l'+str(x) for x in range(len(lines))]  # Prepare a list of names for the lines
        lines = {k: v for k, v in zip(lineNames, lines.values())}  # Create a dictionary {name: line}
        activeL = list(range(len(lines)))  # List of all line index to mark them as active in CheckboxGroup

        JScode = [self._visible_line_JS(k) for k in lines]  # Generate JavaScript for each line
        JScode = '\n'.join(JScode)  # From a list to a single string

        with open(osjoin(getcwd(), 'mLearning', 'JScodeAllLines.js'), 'r') as fileJS:
            buttonJS = fileJS.read()  # Read JavaScript code from a file to toggle the visibility of all lines
        # with open(osjoin(getcwd(), 'mLearning', 'JScode.js'), 'w+') as codeFile:
        #     codeFile.write(JScode)  # Write whole CustomJS to a file for debugging purposes

        callback = CustomJS(code=JScode, args={})  # Args will be added once checkbox and button are added to lines
        checkbox = CheckboxGroup(labels=labels,
                                 active=activeL,  # Labels to be ticked from the beginning
                                 callback=callback,
                                 name='checkbox')  # JavaScript var name

        buttonCallback = CustomJS(code=buttonJS, args={})  # Same as for callback
        button = Button(label="Select/Unselect All",  # Button HTML text
                        button_type="default",
                        callback=buttonCallback,
                        name='button')  # JavaScript var name

        lines['checkbox'], lines['button'] = checkbox, button  # Adding widget to lines
        callback.args, buttonCallback.args = lines, lines  # And then lines to callback
        layout = row(self.fig, widgetbox(children=[button, checkbox], width=200))  # One row, two columns

        logging.debug('Interaction implemented')
        return layout
Esempio n. 2
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def liability_plot(df_base, df_reform, span, mtr_opt):
    df_base = ColumnDataSource(df_base)
    df_reform = ColumnDataSource(df_reform)
    tools = "pan, zoom_in, zoom_out, reset"
    fig = figure(plot_width=600,
                 plot_height=500,
                 x_range=(-10000, 300000),
                 y_range=(-20000, 100000),
                 tools=tools,
                 active_drag="pan")
    fig.yaxis.axis_label = "Tax Liabilities"
    fig.yaxis.formatter = NumeralTickFormatter(format="$0,000")

    filer_income = Span(location=span,
                        dimension='height',
                        line_color='black',
                        line_dash='dotted',
                        line_width=1.5)
    fig.add_layout(filer_income)
    label_format = f'{span:,}'
    filer_income_label = Label(x=span,
                               y=25,
                               y_units='screen',
                               x_offset=10,
                               text="{}: $".format(mtr_opt) + label_format,
                               text_color='#303030',
                               text_font="arial",
                               text_font_style="italic",
                               text_font_size="10pt")
    fig.add_layout(filer_income_label)
    axis = Span(location=0,
                dimension='width',
                line_color='#bfbfbf',
                line_width=1.5)
    fig.add_layout(axis)

    iitax_base = fig.line(x="Axis",
                          y="Individual Income Tax",
                          line_color='#2b83ba',
                          muted_color='#2b83ba',
                          line_width=2,
                          legend="Individual Income Tax Liability",
                          muted_alpha=0.1,
                          source=df_base)
    payroll_base = fig.line(x="Axis",
                            y="Payroll Tax",
                            line_color='#abdda4',
                            muted_color='#abdda4',
                            line_width=2,
                            legend='Payroll Tax Liability',
                            muted_alpha=0.1,
                            source=df_base)

    iitax_reform = fig.line(x="Axis",
                            y="Individual Income Tax",
                            line_color='#2b83ba',
                            muted_color='#2b83ba',
                            line_width=2,
                            line_dash='dashed',
                            legend="Individual Income Tax Liability",
                            muted_alpha=0.1,
                            source=df_reform)
    payroll_reform = fig.line(x="Axis",
                              y="Payroll Tax",
                              line_color='#abdda4',
                              muted_color='#abdda4',
                              line_width=2,
                              line_dash='dashed',
                              legend='Payroll Tax Liability',
                              muted_alpha=0.1,
                              source=df_reform)

    iitax_base.muted = False
    payroll_base.muted = False
    iitax_reform.muted = False
    payroll_reform.muted = False

    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base (Solid)",
                         button_type="default",
                         callback=base_callback,
                         active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": iitax_base,
        "object2": payroll_base
    }

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform (Dashed)",
                           button_type="default",
                           callback=reform_callback,
                           active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": iitax_reform,
        "object2": payroll_reform
    }

    fig.xaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.xaxis.axis_label = mtr_opt
    fig.xaxis.minor_tick_line_color = None

    fig.legend.click_policy = "mute"

    layout = column(fig, row(base_toggle, reform_toggle))

    js_liability, div_liability = components(layout)

    outputs = {
        "media_type":
        "bokeh",
        "title":
        "Tax Liabilities by {} (Holding Other Inputs Constant)".format(
            mtr_opt),
        "data": {
            "javascript": js_liability,
            "html": div_liability
        }
    }

    return outputs
Esempio n. 3
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def credit_plot(df_base, df_reform, span, mtr_opt):
    df_base = ColumnDataSource(df_base)
    df_reform = ColumnDataSource(df_reform)
    tools = "pan, zoom_in, zoom_out, reset"
    fig = figure(plot_width=600,
                 plot_height=500,
                 x_range=(-2500, 70000),
                 tools=tools,
                 active_drag="pan")

    filer_income = Span(location=span,
                        dimension='height',
                        line_color='black',
                        line_dash='dotted',
                        line_width=1.5)
    fig.add_layout(filer_income)
    label_format = f'{span:,}'
    filer_income_label = Label(x=span,
                               y=45,
                               y_units='screen',
                               x_offset=10,
                               text="{}: $".format(mtr_opt) + label_format,
                               text_color='#303030',
                               text_font="arial",
                               text_font_style="italic",
                               text_font_size="10pt")
    fig.add_layout(filer_income_label)
    axis = Span(location=0,
                dimension='width',
                line_color='#bfbfbf',
                line_width=1.5)
    fig.add_layout(axis)

    eitc_base = fig.line(x="Axis",
                         y="EITC",
                         line_color='#2b83ba',
                         muted_color='#2b83ba',
                         line_width=2,
                         legend="Earned Income Tax Credit",
                         muted_alpha=0.1,
                         source=df_base)
    ctc_base = fig.line(x="Axis",
                        y="CTC",
                        line_color='#abdda4',
                        muted_color='#abdda4',
                        line_width=2,
                        legend='Nonrefundable Child Tax Credit',
                        muted_alpha=0.1,
                        source=df_base)
    ctc_refund_base = fig.line(x="Axis",
                               y="CTC Refundable",
                               line_color='#fdae61',
                               muted_color='#fdae61',
                               line_width=2,
                               legend='Refundable Child Tax Credit',
                               muted_alpha=0.1,
                               source=df_base)
    cdcc_base = fig.line(x="Axis",
                         y="Child care credit",
                         line_color='#d7191c',
                         muted_color='#d7191c',
                         line_width=2,
                         legend='Child and Dependent Care Credit',
                         muted_alpha=0.1,
                         source=df_base)

    eitc_reform = fig.line(x="Axis",
                           y="EITC",
                           line_color='#2b83ba',
                           muted_color='#2b83ba',
                           line_width=2,
                           line_dash='dashed',
                           legend="Earned Income Tax Credit",
                           muted_alpha=0.1,
                           source=df_reform)
    ctc_reform = fig.line(x="Axis",
                          y="CTC",
                          line_color='#abdda4',
                          muted_color='#abdda4',
                          line_width=2,
                          line_dash='dashed',
                          legend='Nonrefundable Child Tax Credit',
                          muted_alpha=0.1,
                          source=df_reform)
    ctc_refund_reform = fig.line(x="Axis",
                                 y="CTC Refundable",
                                 line_color='#fdae61',
                                 muted_color='#fdae61',
                                 line_width=2,
                                 line_dash='dashed',
                                 legend='Refundable Child Tax Credit',
                                 muted_alpha=0.1,
                                 source=df_reform)
    cdcc_reform = fig.line(x="Axis",
                           y="Child care credit",
                           line_color='#d7191c',
                           muted_color='#d7191c',
                           line_width=2,
                           line_dash='dashed',
                           legend='Child and Dependent Care Credit',
                           muted_alpha=0.1,
                           source=df_reform)

    ctc_base.muted = True
    ctc_refund_base.muted = True
    cdcc_base.muted = True
    ctc_reform.muted = True
    ctc_refund_reform.muted = True
    cdcc_reform.muted = True

    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    object3.visible = toggle.active
    object4.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base (Solid)",
                         button_type="default",
                         callback=base_callback,
                         active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": eitc_base,
        "object2": cdcc_base,
        "object3": ctc_base,
        "object4": ctc_refund_base
    }

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform (Dashed)",
                           button_type="default",
                           callback=reform_callback,
                           active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": eitc_reform,
        "object2": cdcc_reform,
        "object3": ctc_reform,
        "object4": ctc_refund_reform
    }

    fig.yaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.yaxis.axis_label = "Tax Credits"
    fig.xaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.xaxis.axis_label = mtr_opt
    fig.xaxis.minor_tick_line_color = None

    fig.legend.click_policy = "mute"

    layout = column(fig, row(base_toggle, reform_toggle))

    js_credit, div_credit = components(layout)

    outputs = {
        "media_type":
        "bokeh",
        "title":
        "Tax Credits by {} (Holding Other Inputs Constant)".format(mtr_opt),
        "data": {
            "javascript": js_credit,
            "html": div_credit
        }
    }

    return outputs
Esempio n. 4
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def liability_plot(df_base, df_reform):
    df_base = ColumnDataSource(df_base)
    df_reform = ColumnDataSource(df_reform)
    fig = figure(plot_width=600,
                 plot_height=500,
                 x_range=(0, 300000),
                 y_range=(-20000, 100000))
    fig.yaxis.axis_label = "Tax Liabilities"
    fig.yaxis.formatter = NumeralTickFormatter(format="$0,000")

    iitax_base = fig.line(x="Wages",
                          y="Individual Income Tax",
                          line_color='#2b83ba',
                          muted_color='#2b83ba',
                          line_width=2,
                          legend="Individual Income Tax Liability",
                          muted_alpha=0.1,
                          source=df_base)
    payroll_base = fig.line(x="Wages",
                            y="Payroll Tax",
                            line_color='#abdda4',
                            muted_color='#abdda4',
                            line_width=2,
                            legend='Payroll Tax Liability',
                            muted_alpha=0.1,
                            source=df_base)

    iitax_reform = fig.line(x="Wages",
                            y="Individual Income Tax",
                            line_color='#2b83ba',
                            muted_color='#2b83ba',
                            line_width=2,
                            line_dash='dashed',
                            legend="Individual Income Tax Liability",
                            muted_alpha=0.1,
                            source=df_reform)
    payroll_reform = fig.line(x="Wages",
                              y="Payroll Tax",
                              line_color='#abdda4',
                              muted_color='#abdda4',
                              line_width=2,
                              line_dash='dashed',
                              legend='Payroll Tax Liability',
                              muted_alpha=0.1,
                              source=df_reform)

    iitax_base.muted = False
    payroll_base.muted = False
    iitax_reform.muted = False
    payroll_reform.muted = False

    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base (Solid)",
                         button_type="default",
                         callback=base_callback,
                         active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": iitax_base,
        "object2": payroll_base
    }

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform (Dashed)",
                           button_type="default",
                           callback=reform_callback,
                           active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": iitax_reform,
        "object2": payroll_reform
    }

    fig.xaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.xaxis.axis_label = "Household Wages"
    fig.xaxis.minor_tick_line_color = None

    fig.legend.click_policy = "mute"

    layout = column(fig, row(base_toggle, reform_toggle))

    js_liability, div_liability = components(layout)

    outputs = {
        "media_type": "bokeh",
        "title": "Tax Liabilities by Wage (Holding Other Inputs Constant)",
        "data": {
            "javascript": js_liability,
            "html": div_liability
        }
    }

    return outputs
Esempio n. 5
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def credit_plot(df_base, df_reform):
    df_base = ColumnDataSource(df_base)
    df_reform = ColumnDataSource(df_reform)

    fig = figure(plot_width=600, plot_height=500, x_range=(0, 70000))

    eitc_base = fig.line(x="Wages",
                         y="EITC",
                         line_color='#2b83ba',
                         muted_color='#2b83ba',
                         line_width=2,
                         legend="Earned Income Tax Credit",
                         muted_alpha=0.1,
                         source=df_base)
    ctc_base = fig.line(x="Wages",
                        y="CTC",
                        line_color='#abdda4',
                        muted_color='#abdda4',
                        line_width=2,
                        legend='Nonrefundable Child Tax Credit',
                        muted_alpha=0.1,
                        source=df_base)
    ctc_refund_base = fig.line(x="Wages",
                               y="CTC Refundable",
                               line_color='#fdae61',
                               muted_color='#fdae61',
                               line_width=2,
                               legend='Refundable Child Tax Credit',
                               muted_alpha=0.1,
                               source=df_base)
    cdcc_base = fig.line(x="Wages",
                         y="Child care credit",
                         line_color='#d7191c',
                         muted_color='#d7191c',
                         line_width=2,
                         legend='Child and Dependent Care Credit',
                         muted_alpha=0.1,
                         source=df_base)

    eitc_reform = fig.line(x="Wages",
                           y="EITC",
                           line_color='#2b83ba',
                           muted_color='#2b83ba',
                           line_width=2,
                           line_dash='dashed',
                           legend="Earned Income Tax Credit",
                           muted_alpha=0.1,
                           source=df_reform)
    ctc_reform = fig.line(x="Wages",
                          y="CTC",
                          line_color='#abdda4',
                          muted_color='#abdda4',
                          line_width=2,
                          line_dash='dashed',
                          legend='Nonrefundable Child Tax Credit',
                          muted_alpha=0.1,
                          source=df_reform)
    ctc_refund_reform = fig.line(x="Wages",
                                 y="CTC Refundable",
                                 line_color='#fdae61',
                                 muted_color='#fdae61',
                                 line_width=2,
                                 line_dash='dashed',
                                 legend='Refundable Child Tax Credit',
                                 muted_alpha=0.1,
                                 source=df_reform)
    cdcc_reform = fig.line(x="Wages",
                           y="Child care credit",
                           line_color='#d7191c',
                           muted_color='#d7191c',
                           line_width=2,
                           line_dash='dashed',
                           legend='Child and Dependent Care Credit',
                           muted_alpha=0.1,
                           source=df_reform)

    ctc_base.muted = True
    ctc_refund_base.muted = True
    cdcc_base.muted = True
    ctc_reform.muted = True
    ctc_refund_reform.muted = True
    cdcc_reform.muted = True

    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    object3.visible = toggle.active
    object4.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base (Solid)",
                         button_type="default",
                         callback=base_callback,
                         active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": eitc_base,
        "object2": cdcc_base,
        "object3": ctc_base,
        "object4": ctc_refund_base
    }

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform (Dashed)",
                           button_type="default",
                           callback=reform_callback,
                           active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": eitc_reform,
        "object2": cdcc_reform,
        "object3": ctc_reform,
        "object4": ctc_refund_reform
    }

    fig.yaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.yaxis.axis_label = "Tax Credits"
    fig.xaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.xaxis.axis_label = "Household Wages"
    fig.xaxis.minor_tick_line_color = None

    fig.legend.click_policy = "mute"

    layout = column(fig, row(base_toggle, reform_toggle))

    js_credit, div_credit = components(layout)

    outputs = {
        "media_type": "bokeh",
        "title": "Tax Credits by Wage (Holding Other Inputs Constant)",
        "data": {
            "javascript": js_credit,
            "html": div_credit
        }
    }

    return outputs
from bokeh.io import output_file, show
from bokeh.plotting import figure
from bokeh.layouts import layout
from bokeh.models import Toggle, BoxAnnotation, CustomJS

# We set-up the same standard figure with two lines and now a box over top
p = figure(plot_width=600, plot_height=200, tools='')
visible_line = p.line([1, 2, 3], [1, 2, 1], line_color="blue")
invisible_line = p.line([1, 2, 3], [2, 1, 2], line_color="pink")

box = BoxAnnotation(left=1.5, right=2.5, fill_color='green', fill_alpha=0.1)
p.add_layout(box)

# We write JavaScript to link toggle with visible property of box and line
code = '''\
object.visible = toggle.active
'''

callback1 = CustomJS(code=code, args={})
toggle1 = Toggle(label="Green Box", button_type="success", callback=callback1)
callback1.args = {'toggle': toggle1, 'object': box}

callback2 = CustomJS(code=code, args={})
toggle2 = Toggle(label="Pink Line", button_type="success", callback=callback2)
callback2.args = {'toggle': toggle2, 'object': invisible_line}

output_file("styling_visible_annotation_with_interaction.html")

show(layout([p], [toggle1, toggle2]))
Esempio n. 7
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def rate_plot(df_base, df_reform, span, mtr_opt):
    df_base = ColumnDataSource(df_base)
    df_reform = ColumnDataSource(df_reform)
    tools = "pan, zoom_in, zoom_out, reset"
    fig = figure(plot_width=600,
                 plot_height=500,
                 x_range=(-10000, 300000),
                 y_range=(-0.3, 0.5),
                 tools=tools,
                 active_drag="pan")
    fig.yaxis.axis_label = "Tax Rate"
    fig.yaxis.formatter = NumeralTickFormatter(format="0%")

    filer_income = Span(location=span,
                        dimension='height',
                        line_color='black',
                        line_dash='dotted',
                        line_width=1.5)
    fig.add_layout(filer_income)
    label_format = f'{span:,}'
    filer_income_label = Label(x=span,
                               y=25,
                               y_units='screen',
                               x_offset=10,
                               text="{}: $".format(mtr_opt) + label_format,
                               text_color='#303030',
                               text_font="arial",
                               text_font_style="italic",
                               text_font_size="10pt")
    fig.add_layout(filer_income_label)
    axis = Span(location=0,
                dimension='width',
                line_color='#bfbfbf',
                line_width=1.5)
    fig.add_layout(axis)

    iitax_atr_base = fig.line(x="Axis",
                              y="IATR",
                              line_color='#2b83ba',
                              muted_color='#2b83ba',
                              line_width=2,
                              legend_label="Income Tax Average Rate",
                              muted_alpha=0.1,
                              source=df_base)
    payroll_atr_base = fig.line(x="Axis",
                                y="PATR",
                                line_color='#abdda4',
                                muted_color='#abdda4',
                                line_width=2,
                                legend_label='Payroll Tax Average Rate',
                                muted_alpha=0.1,
                                source=df_base)
    iitax_mtr_base = fig.line(x="Axis",
                              y="Income Tax MTR",
                              line_color='#fdae61',
                              muted_color='#fdae61',
                              line_width=2,
                              legend_label="Income Tax Marginal Rate",
                              muted_alpha=0.1,
                              source=df_base)
    payroll_mtr_base = fig.line(x="Axis",
                                y="Payroll Tax MTR",
                                line_color='#d7191c',
                                muted_color='#d7191c',
                                line_width=2,
                                legend_label='Payroll Tax Marginal Rate',
                                muted_alpha=0.1,
                                source=df_base)

    iitax_atr_reform = fig.line(x="Axis",
                                y="IATR",
                                line_color='#2b83ba',
                                muted_color='#2b83ba',
                                line_width=2,
                                line_dash='dashed',
                                legend_label="Income Tax Average Rate",
                                muted_alpha=0.1,
                                source=df_reform)
    payroll_atr_reform = fig.line(x="Axis",
                                  y="PATR",
                                  line_color='#abdda4',
                                  muted_color='#abdda4',
                                  line_width=2,
                                  line_dash='dashed',
                                  legend_label='Payroll Tax Average Rate',
                                  muted_alpha=0.1,
                                  source=df_reform)
    iitax_mtr_reform = fig.line(x="Axis",
                                y="Income Tax MTR",
                                line_color='#fdae61',
                                muted_color='#fdae61',
                                line_width=2,
                                line_dash='dashed',
                                legend_label="Income Tax Marginal Rate",
                                muted_alpha=0.1,
                                source=df_reform)
    payroll_mtr_reform = fig.line(x="Axis",
                                  y="Payroll Tax MTR",
                                  line_color='#d7191c',
                                  muted_color='#d7191c',
                                  line_width=2,
                                  line_dash='dashed',
                                  legend_label='Payroll Tax Marginal Rate',
                                  muted_alpha=0.1,
                                  source=df_reform)

    iitax_atr_base.muted = False
    iitax_mtr_base.muted = True
    payroll_atr_base.muted = True
    payroll_mtr_base.muted = True
    iitax_atr_reform.muted = False
    iitax_mtr_reform.muted = True
    payroll_atr_reform.muted = True
    payroll_mtr_reform.muted = True

    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    object3.visible = toggle.active
    object4.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base (Solid)",
                         button_type="default",
                         active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": iitax_atr_base,
        "object2": payroll_atr_base,
        "object3": iitax_mtr_base,
        "object4": payroll_mtr_base
    }
    base_toggle.js_on_change('active', base_callback)

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform (Dashed)",
                           button_type="default",
                           active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": iitax_atr_reform,
        "object2": payroll_atr_reform,
        "object3": iitax_mtr_reform,
        "object4": payroll_mtr_reform
    }
    reform_toggle.js_on_change('active', reform_callback)

    fig.xaxis.formatter = NumeralTickFormatter(format="$0,000")
    fig.xaxis.axis_label = mtr_opt
    fig.xaxis.minor_tick_line_color = None

    fig.legend.click_policy = "mute"

    layout = column(fig, row(base_toggle, reform_toggle))

    data = json_item(layout)

    outputs = {
        "media_type": "bokeh",
        "title":
        "Tax Rates by {} (Holding Other Inputs Constant)".format(mtr_opt),
        "data": data
    }

    return outputs
Esempio n. 8
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code = """
    if (0 in checkbox.active) {
        l0.visible = true
    } else {
        l0.visible = false
    }
    if (1 in checkbox.active) {
        l1.visible = true
    } else {
        l1.visible = false
    }
    if (2 in checkbox.active) {
        l2.visible = true
    } else {
        l2.visible = false
    }
"""

p = figure()
props = dict(line_width=4, line_alpha=0.7)
x = np.linspace(0, 4 * np.pi, 100)
l0 = p.line(x, np.sin(x), color=Viridis3[0], legend="Line 0", **props)
l1 = p.line(x, 4 * np.cos(x), color=Viridis3[1], legend="Line 1", **props)
l2 = p.line(x, np.tan(x), color=Viridis3[2], legend="Line 2", **props)

callback = CustomJS(code=code, args={})
checkbox = CheckboxGroup(labels=["Line 0", "Line 1", "Line 2"], active=[0, 1, 2], callback=callback, width=100)
callback.args = dict(l0=l0, l1=l1, l2=l2, checkbox=checkbox)

layout = row(checkbox, p)
show(layout)
Esempio n. 9
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                callback_policy="mouseup")

callback = CustomJS(code=code, args={})

checkbox = CheckboxGroup(labels=[
    "Quantum", "Seismic", "Newtonian", "Suspension thermal",
    "Coating Brownian", "Coating thermo-optic", "Substrate Brownian",
    "Substrate thermo-elastic", "Excess gas"
],
                         active=[0, 1, 2, 3, 4],
                         callback=callback)
callback.args = dict(l_qua=l_qua,
                     l_sei=l_sei,
                     l_new=l_new,
                     l_sth=l_sth,
                     l_cbr=l_cbr,
                     l_cto=l_cto,
                     l_sbr=l_sbr,
                     l_ste=l_ste,
                     l_exg=l_exg,
                     checkbox=checkbox)


def totalnoise_handler(self):
    if (l_tot.visible == True):
        l_tot.visible = False
    else:
        l_tot.visible = True


def totalnoise_handler_aL(self):
    if (l_aL.visible == True):
Esempio n. 10
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			   legend=location, y_range_name='humidity',
			   line_dash="dashed", )
		plot_locations.update({location+"_t": t, location+"_rh": rh})

	code = "console.log('value: ' + multiselect.attributes.value);\n " + "console.log('value_type: ' + Object.prototype.toString.call(multiselect.attributes.value).slice(8, -1));\n " +             "console.log('options: ' + multiselect.attributes.options);\n " + "".join(generate_selector_code(data_per_loc.keys()))
	return p, code, plot_locations

output_file("c:\html\multiselect_val.html")
p, code, plot_locations = generate_plot(data_per_loc) 

ms_options = [(str(i), v) for i , v in enumerate(locations)]
ms_value = [str(i) for i in range(len(locations))]

callback = CustomJS(code=code, args={})
multiselect = MultiSelect(title="Location:", options=ms_options value=ms_value, callback=callback)
callback.args = dict(**plot_locations, multiselect=multiselect)


layout = row(p, multiselect)
show(layout)


output_file("c:\html\multiselect_loc.html")
p, code, plot_locations = generate_plot(data_per_loc)

ms_options = locations
ms_value = locations

callback = CustomJS(code=code, args={})
multiselect = MultiSelect(title="Location:", options=ms_options, value=ms_value, callback=callback)
callback.args = dict(**plot_locations, multiselect=multiselect)
Esempio n. 11
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def bokeh_plot(node, link, name='NetworkMap'):
    from bokeh.plotting import figure, from_networkx, save
    from bokeh.models import ColumnDataSource, HoverTool
    from bokeh.io import export_png
    from bokeh.models import CustomJS, TextInput, CustomJSFilter, CDSView, TapTool
    from bokeh.layouts import column
    from bokeh.plotting import output_file, show
    from bokeh.tile_providers import get_provider, Vendors
    from bokeh.models import Circle, MultiLine, LabelSet, Toggle, CheckboxGroup
    from bokeh.models.graphs import NodesAndLinkedEdges

    text_input = TextInput(value="", title="Filter Nodes:")

    wgs84_to_web_mercator(node)

    node_source_data = ColumnDataSource(
        data=dict(x=node['MX'], y=node['MY'], desc=node['id']))

    # link
    G = nx.from_pandas_edgelist(link, source='id', target='anode')
    nx.set_node_attributes(G, dict(zip(link.id, link.id)), 'desc')
    n_loc = {k: (x, y) for k, x, y in zip(node['id'], node['MX'], node['MY'])}
    nx.set_node_attributes(G, n_loc, 'pos')
    n_color = {k: 'orange' if 'C' in k else 'green' for k in node['id']}
    nx.set_node_attributes(G, n_color, 'color')
    n_alpha = {k: 1 if 'C' in k else 0 for k in node['id']}
    nx.set_node_attributes(G, n_alpha, 'alpha')
    e_color = {(s, t): 'red' if 'C' in s else 'black'
               for s, t in zip(link['id'], link['anode'])}
    nx.set_edge_attributes(G, e_color, 'color')
    e_line_type = {(s, t): 'dashed' if 'C' in s else 'solid'
                   for s, t in zip(link['id'], link['anode'])}
    nx.set_edge_attributes(G, e_line_type, 'line_type')

    tile_provider = get_provider(Vendors.CARTODBPOSITRON)

    bokeh_plot = figure(title="%s network map" %
                        name.split('/')[-1].split('.')[0],
                        sizing_mode="scale_height",
                        plot_width=1300,
                        x_range=(min(node['MX']), max(node['MX'])),
                        tools='pan,wheel_zoom',
                        active_drag="pan",
                        active_scroll="wheel_zoom")
    bokeh_plot.add_tile(tile_provider)

    # This callback is crucial, otherwise the filter will not be triggered when the slider changes
    callback = CustomJS(args=dict(source=node_source_data),
                        code="""
        source.change.emit();
    """)
    text_input.js_on_change('value', callback)

    # Define the custom filter to return the indices from 0 to the desired percentage of total data rows. You could
    # also compare against values in source.data
    js_filter = CustomJSFilter(args=dict(text_input=text_input),
                               code=f"""
    const z = source.data['desc'];
    var indices = ((() => {{
      var result = [];
      for (let i = 0, end = source.get_length(), asc = 0 <= end; asc ? i < end : i > end; asc ? i++ : i--) {{
        if (z[i].includes(text_input.value.toString(10))) {{
          result.push(i);
        }}
      }}
      return result;
    }})());
    return indices;""")

    # Use the filter in a view
    view = CDSView(source=node_source_data, filters=[js_filter])

    callback2 = CustomJS(args=dict(x_range=bokeh_plot.x_range,
                                   y_range=bokeh_plot.y_range,
                                   text_input=text_input,
                                   source=node_source_data),
                         code=f"""
    const z = source.data['desc'];
    const x = source.data['x'];
    const y = source.data['y'];
    var result = [];
    for (let i = 0, end = source.get_length(), asc = 0 <= end; asc ? i < end : i > end; asc ? i++ : i--) {{
      if (z[i].includes(text_input.value.toString(10))) {{
        result.push(i);
      }}
    }}
    var indices = result[0];
    var Xstart = x[indices];
    var Ystart = y[indices];
    y_range.setv({{"start": Ystart-280, "end": Ystart+280}});
    x_range.setv({{"start": Xstart-500, "end": Xstart+500}});
    x_range.change.emit();
    y_range.change.emit();
    """)

    text_input.js_on_change('value', callback2)

    graph = from_networkx(G,
                          nx.get_node_attributes(G, 'pos'),
                          scale=2,
                          center=(0, 0))
    graph.node_renderer.glyph = Circle(radius=15,
                                       fill_color='color',
                                       fill_alpha='alpha')
    graph.node_renderer.hover_glyph = Circle(radius=15, fill_color='red')

    graph.edge_renderer.glyph = MultiLine(
        line_alpha=1, line_color='color', line_width=1,
        line_dash='line_type')  # zero line alpha
    graph.edge_renderer.hover_glyph = MultiLine(line_color='#abdda4',
                                                line_width=5)
    graph.inspection_policy = NodesAndLinkedEdges()

    bokeh_plot.circle('x',
                      'y',
                      source=node_source_data,
                      radius=10,
                      color='green',
                      alpha=0.7,
                      view=view)

    labels = LabelSet(x='x',
                      y='y',
                      text='desc',
                      text_font_size="8pt",
                      text_color='black',
                      x_offset=5,
                      y_offset=5,
                      source=node_source_data,
                      render_mode='canvas')

    code = '''\
    if (toggle.active) {
        box.text_alpha = 0.0;
        console.log('enabling box');
    } else {
        box.text_alpha = 1.0;
        console.log('disabling box');
    }
    '''
    callback3 = CustomJS(code=code, args={})
    toggle = Toggle(label="Annotation", button_type="success")
    toggle.js_on_click(callback3)
    callback3.args = {'toggle': toggle, 'box': labels}

    bokeh_plot.add_tools(HoverTool(tooltips=[("id", "@desc")]), TapTool())
    # Output filepath
    bokeh_plot.renderers.append(graph)
    bokeh_plot.add_layout(labels)
    layout = column(toggle, text_input, bokeh_plot)

    # export_png(p, filename="plot.png")
    output_file(name)
    show(layout)
Esempio n. 12
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def aggregate_plot(tb):
    """
    Function for creating a bokeh plot that shows aggregate tax liabilities for
    each year the TaxBrain instance was run
    Parameters
    ----------
    tb: An instance of the TaxBrain object
    Returns
    -------
    Bokeh figure
    """
    # Pull aggregate data by year and transpose it for plotting
    varlist = ["iitax", "payrolltax", "combined"]
    base_data = tb.multi_var_table(varlist, "base").transpose()
    base_data["calc"] = "Base"
    reform_data = tb.multi_var_table(varlist, "reform").transpose()
    reform_data["calc"] = "Reform"
    base_cds = ColumnDataSource(base_data)
    reform_cds = ColumnDataSource(reform_data)
    num_ticks = len(base_data)
    del base_data, reform_data

    fig = figure(title="Aggregate Tax Liability by Year",
                 width=700,
                 height=500,
                 tools="save")
    ii_base = fig.line(x="index",
                       y="iitax",
                       line_width=4,
                       line_color="#12719e",
                       legend_label="Income Tax - Base",
                       source=base_cds)
    ii_reform = fig.line(x="index",
                         y="iitax",
                         line_width=4,
                         line_color="#73bfe2",
                         legend_label="Income Tax - Reform",
                         source=reform_cds)
    proll_base = fig.line(x="index",
                          y="payrolltax",
                          line_width=4,
                          line_color="#408941",
                          legend_label="Payroll Tax - Base",
                          source=base_cds)
    proll_reform = fig.line(x="index",
                            y="payrolltax",
                            line_width=4,
                            line_color="#98cf90",
                            legend_label="Payroll Tax - Reform",
                            source=reform_cds)
    comb_base = fig.line(x="index",
                         y="combined",
                         line_width=4,
                         line_color="#a4201d",
                         legend_label="Combined - Base",
                         source=base_cds)
    comb_reform = fig.line(x="index",
                           y="combined",
                           line_width=4,
                           line_color="#e9807d",
                           legend_label="Combined - Reform",
                           source=reform_cds)

    # format figure
    fig.legend.location = "top_left"
    fig.yaxis.formatter = NumeralTickFormatter(format="$0.00a")
    fig.yaxis.axis_label = "Aggregate Tax Liability"
    fig.xaxis.minor_tick_line_color = None
    fig.xaxis[0].ticker.desired_num_ticks = num_ticks

    # Add hover tool
    tool_str = """
        <p><b>@calc - {}</b></p>
        <p>${}</p>
    """
    ii_hover = HoverTool(tooltips=tool_str.format("Individual Income Tax",
                                                  "@iitax{0,0}"),
                         renderers=[ii_base, ii_reform])
    proll_hover = HoverTool(tooltips=tool_str.format("Payroll Tax",
                                                     "@payrolltax{0,0}"),
                            renderers=[proll_base, proll_reform])
    combined_hover = HoverTool(tooltips=tool_str.format(
        "Combined Tax", "@combined{0,0}"),
                               renderers=[comb_base, comb_reform])
    fig.add_tools(ii_hover, proll_hover, combined_hover)

    # toggle which lines are shown
    plot_js = """
    object1.visible = toggle.active
    object2.visible = toggle.active
    object3.visible = toggle.active
    """
    base_callback = CustomJS(code=plot_js, args={})
    base_toggle = Toggle(label="Base", button_type="primary", active=True)
    base_callback.args = {
        "toggle": base_toggle,
        "object1": ii_base,
        "object2": proll_base,
        "object3": comb_base
    }
    base_toggle.js_on_change('active', base_callback)

    reform_callback = CustomJS(code=plot_js, args={})
    reform_toggle = Toggle(label="Reform", button_type="primary", active=True)
    reform_callback.args = {
        "toggle": reform_toggle,
        "object1": ii_reform,
        "object2": proll_reform,
        "object3": comb_reform
    }
    fig_layout = layout([fig], [base_toggle, reform_toggle])
    reform_toggle.js_on_change('active', reform_callback)

    # Components needed to embed the figure
    data = json_item(fig_layout)
    outputs = {
        "media_type": "bokeh",
        "title": "",
        "data": data,
    }

    return outputs
Esempio n. 13
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    if (0 in checkbox.active) {
        l0.visible = true
    } else {
        l0.visible = false
    }
    if (1 in checkbox.active) {
        l1.visible = true
    } else {
        l1.visible = false
    }
    if (2 in checkbox.active) {
        l2.visible = true
    } else {
        l2.visible = false
    }
"""

p = figure()
props = dict(line_width=4, line_alpha=0.7)
x = np.linspace(0, 4 * np.pi, 100)
l0 = p.line(x, np.sin(x), color=Viridis3[0], legend="Line 0", **props)
l1 = p.line(x, 4 * np.cos(x), color=Viridis3[1], legend="Line 1", **props)
l2 = p.line(x, np.tan(x), color=Viridis3[2], legend="Line 2", **props)

callback = CustomJS(code=code, args={})
checkbox = CheckboxGroup(labels=["Line 0", "Line 1", "Line 2"], active=[0, 1, 2], callback=callback, width=100)
callback.args = dict(l0=l0, l1=l1, l2=l2, checkbox=checkbox)

layout = row(checkbox, p)
show(layout)