import os
import dash
from dash.dependencies import Input, Output
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import numpy as np

csv_name = os.path.dirname(__file__) + '../statistics.csv'
df = pd.read_csv(csv_name)

# Round floats
df.iloc[:, 1:] = np.round(df.iloc[:, 1:] * 100) / 100

variables = {
    'location': '',
    'H_sig': 'o',
    'H_1%': 'x',
    'H_max': '□',
    'Hm0': '◊',
    'Tp': '',
    'Tp1': '',
}

df = df[variables.keys()]

# add an id column and set it as the index
# in this case the unique ID is just the country name, so we could have just
# renamed 'country' to 'id' (but given it the display name 'country'), but
# here it's duplicated just to show the more general pattern.
df['id'] = df.index
# df.set_index('id', inplace=True, drop=False)

app = dash.Dash(__name__)

app.layout = html.Div([
    dash_table.DataTable(
        id='datatable-row-ids',
        columns=[{
            'name': [val, key],
            'id': key
        } for key, val in variables.items()],
        data=df.to_dict('records'),
        editable=False,
        # filter_action="native",
        sort_action='native',
        sort_mode='multi',
        row_selectable='multi',
        row_deletable=False,
        selected_rows=list(df.index),
        style_as_list_view=True,
    ),
    html.Div(id='datatable-row-ids-container')
])


@app.callback(Output('datatable-row-ids-container', 'children'), [
    Input('datatable-row-ids', 'derived_virtual_row_ids'),
    Input('datatable-row-ids', 'selected_row_ids'),
    Input('datatable-row-ids', 'active_cell')
])
def update_graphs(row_ids, selected_row_ids, active_cell):
    # When the table is first rendered, `derived_virtual_data` and
    # `derived_virtual_selected_rows` will be `None`. This is due to an
    # idiosyncracy in Dash (unsupplied properties are always None and Dash
    # calls the dependent callbacks when the component is first rendered).
    # So, if `rows` is `None`, then the component was just rendered
    # and its value will be the same as the component's dataframe.
    # Instead of setting `None` in here, you could also set
    # `derived_virtual_data=df.to_rows('dict')` when you initialize
    # the component.
    selected_id_set = set(selected_row_ids or [])

    if row_ids is None:
        dff = df
        # pandas Series works enough like a list for this to be OK
        row_ids = df['id']
    else:
        dff = df.loc[row_ids]

    active_row_id = active_cell['row_id'] if active_cell else None

    colors = [
        '#FF69B4' if i == active_row_id else
        '#7FDBFF' if i in selected_id_set else '#0074D9' for i in row_ids
    ]

    return [
        dcc.Graph(
            id=column + '--row-ids',
            figure={
                'data': [{
                    'x': dff['id'],
                    'y': dff[column],
                    'type': 'bar',
                    'marker': {
                        'color': colors
                    },
                }],
                'layout': {
                    'xaxis': {
                        'automargin': True
                    },
                    'yaxis': {
                        'automargin': True,
                        'title': {
                            'text': column
                        }
                    },
                    'height': 250,
                    'margin': {
                        't': 10,
                        'l': 10,
                        'r': 10
                    },
                },
            },
        )
        # check if column exists - user may have deleted it
        # If `column.deletable=False`, then you don't
        # need to do this check.
        for column in ['H_sig', 'H_1%', 'H_max'] if column in dff
    ]


if __name__ == '__main__':
    app.run_server(debug=True)