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import streamlit as st | |
import plotly.graph_objects as go | |
import numpy as np | |
import pandas as pd | |
# Hugging Face Colors | |
fillcolor = "#FFD21E" | |
line_color = "#FF9D00" | |
fill_color_list = [fillcolor, "#F05998", "#40BAF0"] | |
line_color_list = [line_color, "#5E233C", "#194A5E"] | |
# opacity of the plot | |
opacity = 0.75 | |
# categories to show radar chart | |
categories = ["ARC", "GSM8K", "TruthfulQA", "Winogrande", "HellaSwag", "MMLU"] | |
# Dataset columns | |
columns = ["model_name", "ARC", "HellaSwag", "TruthfulQA", "Winogrande", "GSM8K", | |
"MMLU", "Average"] | |
#@st.cache_data | |
def plot_radar_chart_index(dataframe: pd.DataFrame, index: int, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color): | |
""" | |
plot the index-th row of the dataframe | |
Arguments: | |
dataframe: a pandas DataFrame | |
index: the index of the row we want to plot | |
categories: the list of the metrics | |
fillcolor: a string specifying the color to fill the area | |
line_color: a string specifying the color of the lines in the graph | |
""" | |
fig = go.Figure() | |
data = dataframe.loc[index,categories].to_numpy()*100 | |
data = data.astype(float) | |
# rounding data | |
data = data.round(decimals = 2) | |
# add data to close the area of the radar chart | |
data = np.append(data, data[0]) | |
categories_theta = categories.copy() | |
categories_theta.append(categories[0]) | |
model_name = dataframe.loc[index,"model_name"] | |
#print("Printing data ", data, " for ", model_name) | |
fig.add_trace(go.Scatterpolar( | |
r=data, | |
theta=categories_theta, | |
fill='toself', | |
fillcolor = fillcolor, | |
opacity = opacity, | |
line=dict(color = line_color), | |
name= model_name | |
)) | |
fig.update_layout( | |
polar=dict( | |
radialaxis=dict( | |
visible=True, | |
range=[0, 100.] | |
)), | |
showlegend=False | |
) | |
return fig | |
#@st.cache_data | |
def plot_radar_chart_name(dataframe: pd.DataFrame, model_name: str, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color): | |
""" | |
plot the results of the model named model_name row of the dataframe | |
Arguments: | |
dataframe: a pandas DataFrame | |
model_name: a string stating the name of the model | |
categories: the list of the metrics | |
fillcolor: a string specifying the color to fill the area | |
line_color: a string specifying the color of the lines in the graph | |
""" | |
fig = go.Figure() | |
data = dataframe[dataframe["model_name"] == model_name][categories].to_numpy()*100 | |
data = data.astype(float) | |
# rounding data | |
data = data.round(decimals = 2) | |
# add data to close the area of the radar chart | |
data = np.append(data, data[0]) | |
categories_theta = categories.copy() | |
categories_theta.append(categories[0]) | |
model_name = model_name | |
#print("Printing data ", data, " for ", model_name) | |
fig.add_trace(go.Scatterpolar( | |
r=data, | |
theta=categories_theta, | |
fill='toself', | |
fillcolor = fillcolor, | |
opacity = opacity, | |
line=dict(color = line_color), | |
name= model_name | |
)) | |
fig.update_layout( | |
polar=dict( | |
radialaxis=dict( | |
visible=True, | |
range=[0, 100.] | |
)), | |
showlegend=False | |
) | |
return fig | |
#@st.cache_data | |
def plot_radar_chart_rows(rows: object, columns:list = columns, categories: list = categories, fillcolor_list: str = fill_color_list, line_color_list:str = line_color_list): | |
""" | |
plot the results of the model selected by the checkbox | |
Arguments: | |
rows: an iterable whose elements are dicts with columns as their keys | |
columns: the list of the columns to use | |
categories: the list of the metrics | |
fillcolor: a string specifying the color to fill the area | |
line_color: a string specifying the color of the lines in the graph | |
""" | |
fig = go.Figure() | |
dataset = pd.DataFrame(rows, columns=columns) | |
data = dataset[categories].to_numpy() | |
data = data.astype(float) | |
showLegend = False | |
if len(rows) > 1: | |
showLegend = True | |
# add data to close the area of the radar chart | |
data = np.append(data, data[:,0].reshape((-1,1)), axis=1) | |
categories_theta = categories.copy() | |
categories_theta.append(categories[0]) | |
opacity = 0.75 | |
for i in range(len(dataset)): | |
colors = fillcolor_list[i] | |
fig.add_trace(go.Scatterpolar( | |
r=data[i,:], | |
theta=categories_theta, | |
fill='toself', | |
fillcolor = colors, | |
opacity = opacity, | |
line=dict(color = line_color_list[i]), | |
name= dataset.loc[i,"model_name"] | |
)) | |
fig.update_layout( | |
polar=dict( | |
radialaxis=dict( | |
visible=True, | |
range=[0, 100.] | |
)), | |
showlegend=showLegend | |
) | |
opacity -= .2 | |
return fig |