def display_type(selector):
if selector == 'all':
return list(WELL_TYPES.keys())
elif selector == 'productive':
return ['GD', 'GE', 'GW', 'IG', 'IW', 'OD', 'OE', 'OW']
else:
return []
"value": "prov_name"
},
{
"label": "North West ",
"value": "custom"
},
],
value="productive",
labelStyle={"display": "inline-block"},
className="dcc_control",
),
dcc.Dropdown(
id="well_types",
options=well_type_options,
multi=True,
value=list(WELL_TYPES.keys()),
className="dcc_control",
),
],
className="pretty_container four columns",
id="cross-filter-options",
),
html.Div(
[
html.Div(
[
html.Div(
[
html.H6(id="well_text"),
html.P("Current Water Use (Litres)")
],
def display_type(selector):
if selector == "all":
return list(WELL_TYPES.keys())
elif selector == "productive":
return ["GD", "GE", "GW", "IG", "IW", "OD", "OE", "OW"]
return []
def display_type(selector):
if selector == 'all':
return list(WELL_TYPES.keys())
elif selector == 'productive':
def __init__(self, url_base_pathname=None):
# server = flask.Flask(__name__)
# app = dgc.dash.Dash(__name__, server=server)
# self.app = dgc.dash.Dash(__name__)
# self.app = dgc.dash.Dash(__name__, url_base_pathname='/dev/')
if url_base_pathname is None:
self.app = dgc.dash.Dash(__name__)
else:
self.app = dgc.dash.Dash(__name__,
url_base_pathname=url_base_pathname)
# Create controls
county_options = [{
"label": str(COUNTIES[county]),
"value": str(county)
} for county in COUNTIES]
well_status_options = [{
"label": str(WELL_STATUSES[well_status]),
"value": str(well_status)
} for well_status in WELL_STATUSES]
well_type_options = [{
"label": str(WELL_TYPES[well_type]),
"value": str(well_type)
} for well_type in WELL_TYPES]
# This is taken from Dash Project
df1 = pd.read_csv(os.path.join(DATA_PATH, "wellspublic.csv"),
low_memory=False)
# df1 = get_df_from_dropbox(os.path.join(DATA_PATH,"wellspublic.csv"))
# df1 = get_df_from_dropbox(DATA_PATH + "/wellspublic.csv")
df1["Date_Well_Completed"] = pd.to_datetime(df1["Date_Well_Completed"])
df1 = df1[df1["Date_Well_Completed"] > dt.datetime(1960, 1, 1)]
df1['Year_Well_Completed'] = df1.Date_Well_Completed.apply(
lambda d: d.year)
df1['Month_Well_Completed'] = df1.Date_Well_Completed.apply(
lambda d: d.month)
self.df1 = df1.copy()
trim = df1[["API_WellNo", "Well_Type", "Well_Name"]]
trim.index = trim["API_WellNo"]
dataset = trim.to_dict(orient="index")
points = pickle.load(open(os.path.join(DATA_PATH, "points.pkl"), "rb"))
# points = get_pickle_from_dropbox(os.path.join(DATA_PATH,"points.pkl"))
# points = get_pickle_from_dropbox(DATA_PATH+"/points.pkl")
tgas = 'Gas Produced, MCF'
twater = 'Water Produced, bbl'
toil = 'Oil Produced, bbl'
dict_list = [{
'API_WellNo': k,
'year': y,
'gas': points[k][y][tgas],
'water': points[k][y][twater],
'oil': points[k][y][toil]
} for k in points.keys() for y in points[k].keys()]
df_points = pd.DataFrame(dict_list)
df_points[
'all_types'] = df_points.gas + df_points.water + df_points.oil
self.df_points = df_points.copy()
df_county = pd.DataFrame({
'Cnty': [int(s) for s in list(COUNTIES.keys())],
'cname':
list(COUNTIES.values())
})
df2 = df1.merge(df_county, on='Cnty', how='inner')
# print(len(df2))
df_well_status = pd.DataFrame({
'Well_Status': list(WELL_STATUSES.keys()),
'wstatus': list(WELL_STATUSES.values())
})
df2 = df2.merge(df_well_status, on='Well_Status', how='inner')
df_well_type = pd.DataFrame({
'Well_Type': list(WELL_TYPES.keys()),
'wtype': list(WELL_TYPES.values())
})
df2 = df2.merge(df_well_type, on='Well_Type', how='inner')
df_well_color = pd.DataFrame({
'Well_Type': list(WELL_COLORS.keys()),
'wcolor': list(WELL_COLORS.values())
})
df2 = df2.merge(df_well_color, on='Well_Type', how='inner')
df = df2.copy()
self.df = df.copy()
# Define the static components
# ********************** plotly logo ****************************
img = html.Img(src=self.app.get_asset_url("dash-logo.png"),
className='plogo')
# img = html.Img(src="/static/dash-logo.png",className='plogo')
# ********************** title div ********************************
title = html.Div([
html.H3("New York Oil And Gas", className='ogtitle'),
html.H5("Production Overview", className='ogtitle')
])
# *****You ************* link to plotly info ***********************
adiv = html.A([html.Button(["Learn More"], className='ogabutton')],
href="https://plot.ly/dash/pricing",
className='adiv')
# build row 2, column1 components that help you build your main data store
# ********************* slider *********************************
text_slider = html.Div([
'Filter by construction date (or select range in histogram):',
html.P()
])
yr_slider = dgc.RangeSliderComponent(
'yr_slider',
text_slider,
min_value=df.Year_Well_Completed.min(),
max_value=df.Year_Well_Completed.max())
slider = html.Div(yr_slider.html, className='r2_margin')
# ********************* well status radio *****************************
rs_op = [{
'label': 'All',
'value': 'all'
}, {
'label': 'Active only',
'value': 'active'
}, {
'label': 'Customize',
'value': 'custom'
}]
radio_status = dgc.RadioItemComponent(
'radio_status',
html.Div(['Filter by well status:',
html.P()]),
rs_op,
'active',
style={})
radio1 = html.Div([radio_status.html], className='r2_margin')
# ********************* well status dropdown *****************************
ds_op = well_status_options
self.ds_op = ds_op.copy()
ws_keys = [d['value'] for d in ds_op]
dropdown_status = dgc.DropdownComponent(
'dropdown_status',
'',
ds_op,
ws_keys,
input_tuples=[(radio_status.id, 'value')],
callback_input_transformer=self._select_well_status_list)
dropdown1 = html.Div(dropdown_status.html, className='d1_margin')
# ********************* well type radio *********************************
rt_op = [{
'label': 'All',
'value': 'all'
}, {
'label': 'Productive only',
'value': 'productive'
}, {
'label': 'Customize',
'value': 'custom'
}]
radio_type = dgc.RadioItemComponent(
'radio_type',
html.Div(['Filter by well type:', html.P()]),
rt_op,
'productive',
style={})
radio2 = html.Div([radio_type.html], className='r2_margin')
# ********************* dropdown for well type *********************************
dt_op = well_type_options
wt_keys = [d['value'] for d in dt_op]
self.ws_keys = ws_keys
self.wt_keys = wt_keys
dropdown_type = dgc.DropdownComponent(
'dropdown_type',
'',
dt_op,
wt_keys,
input_tuples=[(radio_type.id, 'value')],
callback_input_transformer=self._select_well_type_list)
dropdown2 = html.Div(dropdown_type.html, className='d1_margin')
# ********************* build the main_data component **********************
lg = dgc.init_root_logger()
input_component_list = [(yr_slider.id, 'value'),
(dropdown_status.id, 'value'),
(dropdown_type.id, 'value')]
main_data = dgc.StoreComponent(
'store_df',
input_component_list=input_component_list,
create_storage_dictionary_from_inputs_callback=lambda v: self.
_build_main_data_dictionary(v, logger=lg))
self.main_data = main_data
main_data.create_storage_dictionary_from_inputs_callback = lambda v: self._build_main_data_dictionary(
v, logger=lg)
aggs_div_comps = [
self._make_agg_div(tc)
for tc in ['no_wells', 'gas_mcf', 'oil_bbl', 'water_bbl']
]
# build the panels
wells = html.Div([aggs_div_comps[0].html, html.P('Wells')])
gas = html.Div([aggs_div_comps[1].html, html.P('Gas')])
oil = html.Div([aggs_div_comps[2].html, html.P('Oil')])
water = html.Div([aggs_div_comps[3].html, html.P('Water')])
xygraph = dgc.XyGraphComponent(
'xygraph',
main_data,
x_column='Year_Well_Completed',
num_x_values=8,
title='Completed Wells/Year',
transform_input=lambda value_list: _trans_df(value_list))
# ************* Build row 3: the map and pie charts ********************************
mapbox_access_token = "pk.eyJ1IjoiamFja2x1byIsImEiOiJjajNlcnh3MzEwMHZtMzNueGw3NWw5ZXF5In0.fk8k06T96Ml9CLGgKmk81w"
self.basic_layout = dict(
autosize=True,
automargin=True,
margin=dict(l=30, r=30, b=20, t=40),
hovermode="closest",
plot_bgcolor="#F9F9F9",
paper_bgcolor="#F9F9F9",
legend=dict(font=dict(size=10), orientation="h"),
title="Satellite Overview",
mapbox=dict(
accesstoken=mapbox_access_token,
style="light",
center=dict(lon=-78.05, lat=42.54),
zoom=7,
),
)
mapgraph = dgc.FigureComponent('mapgraph',
None,
self._create_map_figure,
input_tuple_list=input_component_list)
piegraph = dgc.FigureComponent('piegraph',
None,
self._create_pie_figure,
input_tuple_list=input_component_list)
callback_components = [
yr_slider, radio_status, radio_type, dropdown_status,
dropdown_type, main_data, xygraph, mapgraph, piegraph
] + aggs_div_comps
pn = 'rpanel'
pnnc = 'rpanelnc'
r1 = dgr('r1', [img, title, adiv], child_class=pnnc)
r2c1 = dgr('r2c1', [slider, radio1, dropdown1, radio2, dropdown2],
child_class=pnnc)
r2c2r1 = dgr('r2c2r1', [wells, gas, oil, water],
child_class=pn,
parent_class=pnnc)
r2c2r2 = dgr('r2c2r2', [xygraph.html])
r2c2r3 = html.Div()
r2c2 = dgr('r2c2', [r2c2r1, r2c2r2, r2c2r3],
child_class=None,
parent_class=pnnc)
r2 = dgr('r2', [r2c1, r2c2])
r3 = dgr('r3',
[mapgraph.html, html.Div(' '), piegraph.html],
parent_class=pnnc)
rbot = dgr('rbot', ['the bottom'], child_class=pn)
rside = html.Div(' ')
rall_rows = dgr('rall_rows', [r1, r2, r3, rbot])
rall_cols = dgr('rall_cols', [rside, rall_rows, rside],
parent_class=pnnc)
self.app.layout = html.Div([rall_cols, main_data.html])
for c in callback_components:
c.callback(self.app)
def layout_app(app, well_status_options, well_type_options):
# Create app layout
the_layout = html.Div([
dcc.Store(id='aggregate_data'),
html.Div(
[
html.Div([
html.H2('New York Oil and Gas', ),
html.H4('Production Overview', )
],
className='eight columns'),
html.Img(
src=
"https://s3-us-west-1.amazonaws.com/plotly-tutorials/logo/new-branding/dash-logo-by-plotly-stripe.png",
className='two columns',
),
html.A(html.Button("Learn More", id="learnMore"),
href="https://plot.ly/dash/pricing/",
className="two columns")
],
id="header",
className='row',
),
html.Div([
html.Div([
html.
P('Filter by construction date (or select range in histogram):',
className="control_label"),
dcc.RangeSlider(id='year_slider',
min=1960,
max=2017,
value=[1990, 2010],
className="dcc_control"),
html.P('Filter by well status:', className="control_label"),
dcc.RadioItems(id='well_status_selector',
options=[{
'label': 'All ',
'value': 'all'
}, {
'label': 'Active only ',
'value': 'active'
}, {
'label': 'Customize ',
'value': 'custom'
}],
value='active',
labelStyle={'display': 'inline-block'},
className="dcc_control"),
dcc.Dropdown(id='well_statuses',
options=well_status_options,
multi=True,
value=list(WELL_STATUSES.keys()),
className="dcc_control"),
dcc.Checklist(id='lock_selector',
options=[{
'label': 'Lock camera',
'value': 'locked'
}],
values=[],
className="dcc_control"),
html.P('Filter by well type:', className="control_label"),
dcc.RadioItems(id='well_type_selector',
options=[{
'label': 'All ',
'value': 'all'
}, {
'label': 'Productive only ',
'value': 'productive'
}, {
'label': 'Customize ',
'value': 'custom'
}],
value='productive',
labelStyle={'display': 'inline-block'},
className="dcc_control"),
dcc.Dropdown(id='well_types',
options=well_type_options,
multi=True,
value=list(WELL_TYPES.keys()),
className="dcc_control"),
],
className="pretty_container four columns"),
html.Div([
html.Div([
html.Div([
html.P("No. of Wells"),
html.H6(id="well_text", className="info_text")
],
id="wells",
className="pretty_container"),
html.Div(
[
html.Div([
html.P("Gas"),
html.H6(id="gasText", className="info_text")
],
id="gas",
className="pretty_container"),
html.Div([
html.P("Oil"),
html.H6(id="oilText", className="info_text")
],
id="oil",
className="pretty_container"),
html.Div([
html.P("Water"),
html.H6(id="waterText", className="info_text")
],
id="water",
className="pretty_container"),
],
id="tripleContainer",
)
],
id="infoContainer",
className="row"),
html.Div([dcc.Graph(id='count_graph', )],
id="countGraphContainer",
className="pretty_container")
],
id="rightCol",
className="eight columns")
],
className="row"),
html.Div([
html.Div(
[dcc.Graph(id='main_graph')],
className='pretty_container eight columns',
),
html.Div(
[dcc.Graph(id='individual_graph')],
className='pretty_container four columns',
),
],
className='row'),
html.Div([
html.Div(
[dcc.Graph(id='pie_graph')],
className='pretty_container seven columns',
),
html.Div(
[dcc.Graph(id='aggregate_graph')],
className='pretty_container five columns',
),
],
className='row'),
],
id="mainContainer",
style={
"display": "flex",
"flex-direction": "column"
})
return the_layout
