Spaces:
Sleeping
Sleeping
File size: 1,026 Bytes
d22a7f8 e740ec1 d22a7f8 e740ec1 d22a7f8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import altair as alt
import numpy as np
import pandas as pd
import streamlit as st
"""
# Welcome to the exercises of reinforcement learning!
In this exercise we will train two popular deep reinforcement learning agents that you have learned through your courses.
This is the time to put that knowledge to practice!
"""
num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
indices = np.linspace(0, 1, num_points)
theta = 2 * np.pi * num_turns * indices
radius = indices
x = radius * np.cos(theta)
y = radius * np.sin(theta)
df = pd.DataFrame({
"x": x,
"y": y,
"idx": indices,
"rand": np.random.randn(num_points),
})
st.altair_chart(alt.Chart(df, height=700, width=700)
.mark_point(filled=True)
.encode(
x=alt.X("x", axis=None),
y=alt.Y("y", axis=None),
color=alt.Color("idx", legend=None, scale=alt.Scale()),
size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
)) |