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# -*- coding: utf-8 -*-
# import json
# import urllib
import plotly.graph_objects as go
from dash import Dash, Input, Output, dcc, html
from dash.exceptions import PreventUpdate
app = Dash(__name__)
app.layout = html.Div(
[
html.H1("Sankey diagram"),
html.P("Data"),
dcc.Input(id="SM1", placeholder="SM1"),
dcc.Input(id="SM2", placeholder="SM2"),
dcc.Input(id="SM3", placeholder="SM3"),
dcc.Input(id="SM4", placeholder="SM4"),
dcc.Input(id="SM5", placeholder="SM5"),
dcc.Input(id="BS1", placeholder="BS1"),
dcc.Input(id="BS2", placeholder="BS2"),
dcc.Input(id="BS3", placeholder="BS3"),
dcc.Input(id="BS4", placeholder="BS4"),
dcc.Input(id="BS5", placeholder="BS5"),
dcc.Input(id="rainfall", placeholder="Rainfall"),
dcc.Input(id="et", placeholder="ET"),
html.Button("Calculate", id="submit"),
html.H4("Water conservation diagram"),
dcc.Graph(id="graph"),
html.P("Opacity"),
dcc.Slider(id="slider", min=0, max=1, value=0.5, step=0.1),
]
)
def get_excess_clipped_moist_ETb(moisture, bucket_size):
excess = 0 if moisture <= bucket_size else moisture - bucket_size
moist_out = moisture if moisture <= bucket_size else bucket_size
moist_out = moist_out if moisture >= 0 else 0
ETb = 0 if moisture >= 0 else -moisture
return ETb, moist_out, excess
def model(prev_state, R, ET, buckets):
old = {x + "_prev": y for x, y in prev_state.items()}
# layer 0 to 5 cm
SM1 = 0.2 * old["SM1_prev"] + R - 0.5 * ET
Exc1, SM1, ETb1 = get_excess_clipped_moist_ETb(SM1, buckets["BS1"])
# layer 5 to 15 cm
SM2 = 0.95 * old["SM2_prev"] + 0.8 * old["SM1_prev"] - 0.2 * ETb1 + Exc1
Exc2, SM2, ETb2 = get_excess_clipped_moist_ETb(SM2, buckets["BS2"])
# Run Off
if (SM1 > buckets["BS1"]) * (SM2 > buckets["BS2"]):
Exc2 = 0
run_off = Exc2
else:
run_off = 0
# layer 15 to 30 cm
SM3 = 0.95 * old["SM3_prev"] + 0.05 * old["SM2_prev"] - 0.15 * ETb2 + Exc2
Exc3, SM3, ETb3 = get_excess_clipped_moist_ETb(SM3, buckets["BS3"])
# layer 30 to 60 cm
SM4 = 0.95 * old["SM4_prev"] + 0.05 * old["SM3_prev"] - 0.1 * ETb3 + Exc3
Exc4, SM4, ETb4 = get_excess_clipped_moist_ETb(SM4, buckets["BS4"])
# layer 60 to 100 cm
SM5 = 0.99 * old["SM5_prev"] + 0.01 * old["SM4_prev"] - 0.05 * ETb4 + Exc4
Exc5, SM5, ETb5 = get_excess_clipped_moist_ETb(SM5, buckets["BS5"])
DD = 0.01 * old["SM5_prev"] + Exc5
return [
{
"SM1": SM1,
"SM2": SM2,
"SM3": SM3,
"SM4": SM4,
"SM5": SM5,
"DD": DD,
},
{
"ETb1": ETb1,
"ETb2": ETb2,
"ETb3": ETb3,
"ETb4": ETb4,
"ETb5": ETb5,
},
{
"Exc1": Exc1,
"Exc2": Exc2,
"Exc3": Exc3,
"Exc4": Exc4,
"Exc5": Exc5,
},
run_off,
]
@app.callback(
Output("graph", "figure"),
Input("slider", "value"),
Input("SM1", "value"),
Input("SM2", "value"),
Input("SM3", "value"),
Input("SM4", "value"),
Input("SM5", "value"),
Input("BS1", "value"),
Input("BS2", "value"),
Input("BS3", "value"),
Input("BS4", "value"),
Input("BS5", "value"),
Input("rainfall", "value"),
Input("et", "value"),
Input("submit", "n_clicks"),
)
def display_sankey(
opacity, SM1, SM2, SM3, SM4, SM5, BS1, BS2, BS3, BS4, BS5, R, ET, submit
):
if submit == 0 or submit is None:
raise PreventUpdate
buckets = {
"BS1": BS1,
"BS2": BS2,
"BS3": BS3,
"BS4": BS4,
"BS5": BS5,
}
prev_state = {
"SM1": SM1,
"SM2": SM2,
"SM3": SM3,
"SM4": SM4,
"SM5": SM5,
}
SMs, ETbs, Excs, run_off = model(prev_state, R, ET, buckets)
node = dict(
pad=15,
thickness=20,
line=dict(color="black", width=0.5),
label=[
"SM1_prev",
"SM2_prev",
"SM3_prev",
"SM4_prev",
"SM5_prev", # 0-4
"SM1",
"SM2",
"SM3",
"SM4",
"SM5", # 5-9
"ETb1",
"ETb2",
"ETb3",
"ETb4",
"ETb5", # 10-14
"Exc1",
"Exc2",
"Exc3",
"Exc4",
"Exc5", # 15-19
"R",
"ET",
"DD",
"runoff",
], # 20, 21, 22, 23
color="blue",
)
link = dict(
source=[0, 0, 1, 1, 2, 2, 3, 3, 4, 4], # indices correspond to labels
target=[5, 6, 6, 7, 7, 8, 8, 9, 9, 22],
value=[],
)
fig = go.Figure(go.Sankey(link=link, node=node))
fig.update_layout(font_size=10)
return fig
app.run_server(debug=True)
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