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Updated Fisher visualizations and narrative instructions
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@cgeraghty1
cgeraghty1 committed Dec 8, 2024
1 parent 5e88099 commit 83e8db1
Showing 1 changed file with 142 additions and 39 deletions.
181 changes: 142 additions & 39 deletions fisher_weight1.py
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import streamlit as st
import pandas as pd
import dash
from dash import dcc, html
from dash.dependencies import Input, Output
import plotly.graph_objects as go
import pandas as pd

# Title
st.title("Fisher Visualization: Subjective Weightings")
# Initialize Dash app
app = dash.Dash(__name__)
app.title = "Fisher Statistical Visualization"

# Generate random data
ethnic_data = pd.DataFrame({
fisher_data = pd.DataFrame({
"Group": ["White", "Black", "Asian", "Hispanic", "Other"],
"IQ": [100, 108, 105, 102, 98],
"Moral Character": [95, 85, 90, 80, 85],
Expand All @@ -15,39 +18,139 @@
"Reproduction Rate": [48, 55, 47, 60, 52]
})

# Sliders for weights
st.sidebar.title("Adjust Weights")
weights = {
"IQ": st.sidebar.slider("IQ", 0.0, 5.0, 1.0, step=0.1),
"Moral Character": st.sidebar.slider("Moral Character", 0.0, 5.0, 1.0, step=0.1),
"Violent Crime": st.sidebar.slider("Violent Crime", 0.0, 5.0, 1.0, step=0.1),
"Income": st.sidebar.slider("Income", 0.0, 5.0, 1.0, step=0.1),
"Reproduction Rate": st.sidebar.slider("Reproduction Rate", 0.0, 5.0, 1.0, step=0.1),
}

# Apply weights to data
weighted_data = ethnic_data.copy()
for col, weight in weights.items():
weighted_data[col] *= weight

# Plot the data
fig = go.Figure()
for col, color in zip(
["IQ", "Moral Character", "Violent Crime", "Income", "Reproduction Rate"],
["#636EFA", "#EF553B", "#00CC96", "#AB63FA", "#FFA15A"]
):
fig.add_trace(go.Bar(x=weighted_data["Group"], y=weighted_data[col], name=col, marker=dict(color=color), opacity=0.75))

fig.update_layout(
barmode="group",
plot_bgcolor="white",
font=dict(family="Avenir"),
xaxis=dict(showgrid=False, showline=True, zeroline=False, title="Group"),
yaxis=dict(showgrid=True, showticklabels=True, title="Value"),
title="Weighted Variables by Group",
margin=dict(l=10, r=10, t=40, b=10),
height=500
# App layout
app.layout = html.Div(style={"font-family": "Avenir", "padding": "10px", "max-width": "1000px", "margin": "0 auto", "font-size": "0.95em"}, children=[
# Clickable variable titles for toggling visibility
html.Div(
style={"display": "flex", "justify-content": "center", "gap": "8px", "margin-bottom": "10px"},
children=[
html.Div("IQ", id="toggle-iq", style={"color": "#636EFA", "font-weight": "bold", "cursor": "pointer"}),
html.Div("Moral Character", id="toggle-moral", style={"color": "#EF553B", "font-weight": "bold", "cursor": "pointer"}),
html.Div("Violent Crime", id="toggle-crime", style={"color": "#00CC96", "font-weight": "bold", "cursor": "pointer"}),
html.Div("Income", id="toggle-income", style={"color": "#AB63FA", "font-weight": "bold", "cursor": "pointer"}),
html.Div("Reproduction Rate", id="toggle-reproduction", style={"color": "#FFA15A", "font-weight": "bold", "cursor": "pointer"})
]
),

# Bar Chart
dcc.Graph(id="fisher-chart", style={"width": "100%", "height": "400px", "border": "none"}),

# Sliders with corresponding value display
html.Div(
style={"display": "flex", "justify-content": "space-around", "align-items": "center", "margin-top": "10px"},
children=[
html.Div([
html.Label("IQ", style={"font-weight": "bold", "font-size": "0.85em", "text-align": "center"}),
dcc.Slider(
id="weight-iq",
min=0,
max=5,
step=0.1,
value=1,
marks={i: str(round(i, 1)) for i in [0, 1, 2, 3, 4, 5]}
),
html.Div(id="weight-iq-value", style={"text-align": "center", "font-size": "0.85em", "margin-top": "-10px"})
], style={"width": "18%"}),
html.Div([
html.Label("Moral Character", style={"font-weight": "bold", "font-size": "0.85em", "text-align": "center"}),
dcc.Slider(
id="weight-moral",
min=0,
max=5,
step=0.1,
value=1,
marks={i: str(round(i, 1)) for i in [0, 1, 2, 3, 4, 5]}
),
html.Div(id="weight-moral-value", style={"text-align": "center", "font-size": "0.85em", "margin-top": "-10px"})
], style={"width": "18%"}),
html.Div([
html.Label("Violent Crime", style={"font-weight": "bold", "font-size": "0.85em", "text-align": "center"}),
dcc.Slider(
id="weight-crime",
min=0,
max=5,
step=0.1,
value=1,
marks={i: str(round(i, 1)) for i in [0, 1, 2, 3, 4, 5]}
),
html.Div(id="weight-crime-value", style={"text-align": "center", "font-size": "0.85em", "margin-top": "-10px"})
], style={"width": "18%"}),
html.Div([
html.Label("Income", style={"font-weight": "bold", "font-size": "0.85em", "text-align": "center"}),
dcc.Slider(
id="weight-income",
min=0,
max=5,
step=0.1,
value=1,
marks={i: str(round(i, 1)) for i in [0, 1, 2, 3, 4, 5]}
),
html.Div(id="weight-income-value", style={"text-align": "center", "font-size": "0.85em", "margin-top": "-10px"})
], style={"width": "18%"}),
html.Div([
html.Label("Reproduction Rate", style={"font-weight": "bold", "font-size": "0.85em", "text-align": "center"}),
dcc.Slider(
id="weight-reproduction",
min=0,
max=5,
step=0.1,
value=1,
marks={i: str(round(i, 1)) for i in [0, 1, 2, 3, 4, 5]}
),
html.Div(id="weight-reproduction-value", style={"text-align": "center", "font-size": "0.85em", "margin-top": "-10px"})
], style={"width": "18%"})
]
)
])

# Callback to update chart and toggle visibility
@app.callback(
Output("fisher-chart", "figure"),
[Input("weight-iq", "value"),
Input("weight-moral", "value"),
Input("weight-crime", "value"),
Input("weight-income", "value"),
Input("weight-reproduction", "value"),
Input("toggle-iq", "n_clicks"),
Input("toggle-moral", "n_clicks"),
Input("toggle-crime", "n_clicks"),
Input("toggle-income", "n_clicks"),
Input("toggle-reproduction", "n_clicks")]
)
def update_fisher_chart(weight_iq, weight_moral, weight_crime, weight_income, weight_reproduction, *toggle_clicks):
visibility = [True, True, True, True, True]

# Toggle visibility based on click counts
for i, clicks in enumerate(toggle_clicks):
if clicks and clicks % 2 == 1:
visibility[i] = False

weighted_data = fisher_data.copy()
weighted_data["IQ"] *= weight_iq
weighted_data["Moral Character"] *= weight_moral
weighted_data["Violent Crime"] *= weight_crime
weighted_data["Income"] *= weight_income
weighted_data["Reproduction Rate"] *= weight_reproduction

fig = go.Figure()
for col, color, is_visible in zip(
["IQ", "Moral Character", "Violent Crime", "Income", "Reproduction Rate"],
["#636EFA", "#EF553B", "#00CC96", "#AB63FA", "#FFA15A"],
visibility
):
if is_visible:
fig.add_trace(go.Bar(x=weighted_data["Group"], y=weighted_data[col], name=col, marker=dict(color=color), opacity=0.75))

fig.update_layout(
barmode="group",
plot_bgcolor="white",
font=dict(family="Avenir"),
xaxis=dict(showgrid=False, showline=True, zeroline=False, title="Group"),
yaxis=dict(showgrid=True, showticklabels=False, title=""),
showlegend=False,
margin=dict(l=10, r=10, t=20, b=10)
)
return fig

# Display the chart
st.plotly_chart(fig)
if __name__ == "__main__":
app.run_server(debug=True, port=8050)

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