Toggle2_small.py

import logging
logging.basicConfig(level=logging.DEBUG)

import pandas as pd
from pprint import pprint
from bokeh.plotting import figure
from bokeh.models import Plot, ColumnDataSource
from bokeh.properties import Instance
from bokeh.server.app import bokeh_app
from bokeh.server.utils.plugins import object_page
from bokeh.models.widgets import (
    HBox,
    VBoxForm,
    CheckboxGroup)
from os import listdir

# build up list of stock data in the daily folder
# input_fn = 'cumulative-reported-cases-all.csv'
# fn_list = find_csv_filenames('.')
# fn_list.remove(input_fn)

path_to_dir = 'D:/ajoros/Dropbox/AIC/SEIRD/outputtemp/'
# path_to_dir = 'E:/Dropbox/AIC/SEIRD/output/'
# cache stock data as dict of pandas DataFrames
pd_cache = {}


def get_filenames(path_to_dir, suffix=".csv"):
    filenames = listdir(path_to_dir)
    fns = [filename for filename in filenames if filename.endswith(suffix)]
    return fns


def load_csv_to_dflist(path_to_dir, suffix=".csv"):
    fns = get_filenames(path_to_dir, suffix='.csv')
    df_list = []
    for file_ in fns:
        df = pd.read_csv(path_to_dir + file_,
                         usecols=['Date', 'C', 'D', 'Cases', 'Deaths'],
                         parse_dates=['Date'])
        df_list.append(df)
    return df_list


class HackApp(HBox):
    """An example of a browser-based, interactive plot with checkbox controls."""
    extra_generated_classes = [["HackApp", "HackApp", "HBox"]]
    inputs = Instance(VBoxForm)
    toggle = Instance(CheckboxGroup)
    source1 = Instance(ColumnDataSource)
    source2 = Instance(ColumnDataSource)
    source3 = Instance(ColumnDataSource)
    plot = Instance(Plot)

    @classmethod
    def create(cls):
        """One-time creation of app's objects.
        This function is called once, and is responsible for
        creating all objects (plots, datasources, etc)
        """
        obj = cls()
        obj.source1 = ColumnDataSource(data=dict(xs=[], ys=[]))
        obj.source2 = ColumnDataSource(data=dict(xs=[], ys=[]))
        obj.source3 = ColumnDataSource(data=dict(xs=[], ys=[]))

        fns = get_filenames(path_to_dir, suffix='.csv')
        obj.toggle = CheckboxGroup(labels=fns, active=[0])
        print(obj.toggle)

#        colors= ['#3498DB', 'F1C40F', '#16A085', '#C0392B']
        toolset = "crosshair,pan,reset,resize,save,wheel_zoom"
        plot = figure(plot_height=400,
                      plot_width=800,
                      tools=toolset,
                      x_axis_type="datetime"
                      )
        plot.multi_line('xs', 'ys', source=obj.source1,
                  line_width=3,
                  line_color=['red','green','blue','purple']
                  )
        plot.multi_line('xs', 'ys', source=obj.source2,
                  line_width=3,
                  line_color=['red','green','blue','purple']
                  )
        plot.multi_line('xs', 'ys', source=obj.source3,
                  line_width=3,
                  line_color=['red','green','blue','purple']
                  )

        obj.plot = plot
        obj.update_data()

        obj.inputs = VBoxForm(
            children=[
                obj.toggle
            ]
        )

        obj.children.append(obj.inputs)
        obj.children.append(obj.plot)
        return obj

    def checkbox_handler(self, active):
        self.update_data(active)

    def setup_events(self):
        """Attaches the on_change event to the value property of the widget.
        The callback is set to the input_change method of this app.
        """
        super(HackApp, self).setup_events()
        if not self.toggle:
            return
        # pprint(dir(HackApp))
#        sourcenames = [source1']
#        for w in fns:
#            getattr(self, w).on_change('value', self, 'input_change')
#
#        logging.debug('setup_events')

        # WHEN CHECKBOX CHANGES
        self.toggle.on_click(self.checkbox_handler)

    def input_change(self, obj, attrname, old, new):
        """Executes whenever the input form changes.
        It is responsible for updating the plot, or anything else you want.
        Args:
            obj : the object that changed
            attrname : the attr that changed
            old : old value of attr
            new : new value of attr
        """
        self.update_data()
        self.plot.title = self.text.value


    def update_data(self, hide=False):
        """Called each time that any watched property changes.
        This updates the sin wave data with the most recent values of the
        sliders. This is stored as two numpy arrays in a dict into the app's
        data source property.
        """
        logging.debug('update_data')
        df_list = load_csv_to_dflist(path_to_dir, suffix=".csv")
        x1 = x2 = x3 = []
        y1 = y2 = y3 = []
        print(self.toggle.active, "self.toggle")

        for p in self.toggle.active:
            if p == 0:
                DT = df_list[p].Date.tolist()
                print('DT IS TYPE: ' + str(type(DT)))
                x1 = [DT, DT, DT, DT]
                print('x1 IS TYPE: ' + str(type(x1)))
                y1 = [df_list[p].C.tolist(),
                      df_list[p].D.tolist(),
                      df_list[p].Cases.tolist(),
                      df_list[p].Deaths.tolist()]
                print('y1 IS TYPE: ' + str(type(y1)))
            if p == 1:
                DT = df_list[p].Date.tolist()
                print('DT IS TYPE: ' + str(type(DT)))
                x2 = [DT, DT, DT, DT]
                print('x2 IS TYPE: ' + str(type(x2)))
                y2 = [df_list[p].C.tolist(),
                      df_list[p].D.tolist(),
                      df_list[p].Cases.tolist(),
                      df_list[p].Deaths.tolist()]
                print('y2 IS TYPE: ' + str(type(y2)))
            if p == 2:
                DT = df_list[p].Date.tolist()
                print('DT IS TYPE: ' + str(type(DT)))
                x3 = [DT, DT, DT, DT]
                print('x2 IS TYPE: ' + str(type(x3)))
                y3 = [df_list[p].C.tolist(),
                      df_list[p].D.tolist(),
                      df_list[p].Cases.tolist(),
                      df_list[p].Deaths.tolist()]
                print('y2 IS TYPE: ' + str(type(y3)))

        self.source1.data = dict(xs=x1, ys=y1)
        self.source2.data = dict(xs=x2, ys=y2)
        self.source3.data = dict(xs=x3, ys=y3)


@bokeh_app.route("/bokeh/Toggle2/")
@object_page("sin")
def make_hack():
    app = HackApp.create()
    return app