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docs.py
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"""
References to the data
"""
import streamlit as st
def methods():
st.header("Methods")
st.markdown(
r"""
:blue[**Perentiles**]
$k-th$ percentile, is a score below which a given percentage $k$ of scores in its frequency distribution falls
Here, $k \in [10, 50, 90]$.
The density axis is devided in $dx$ intervals. Then the number of data points within an interval of length $dx$ are counted.
$N$ defines the mimnimum number of necessary data within each interval.
"""
)
st.markdown(
"""
:blue[**KS-Test**]
Kolmogorov-Smirnov test according to this paper:
"""
)
st.info(
r"""
**Automated Quality Assessment of Space-Continuous Models for Pedestrian Dynamics**
[10.1007/978-3-030-11440-4\_35](https://link.springer.com/content/pdf/10.1007/978-3-030-11440-4\_35.pdf)
2019
"""
)
st.markdown(
"""
A KS-score equal to zero, means the two datasets that are being compared, are perfectly matching each other.
"""
)
def references():
st.header("Data")
c1, c2 = st.columns(2)
c1.markdown(
"""
- :blue[**01_FD_germany_seyfried2005**]
The fundamental diagram of pedestrian movement revisited,
DOI: [10.1088/1742-5468/2005/10/P10002](https://iopscience.iop.org/article/10.1088/1742-5468/2005/10/P10002),
2005
"""
)
c2.markdown(
"""
- :blue[**02_culture_india_chattaraj2013**]
Comparison of pedestrian fundamental diagram across cultures
DOI: [10.1142/S0219525909002209](https://www.worldscientific.com/doi/abs/10.1142/S0219525909002209)
2009
"""
)
c1.markdown(
"""
- :blue[**27_new_beginnings**]
Wheelchair and Phone use During Single File Pedestrian Movement
DOI: [10.1007/978-981-99-7976-9_23](https://link.springer.com/chapter/10.1007/978-981-99-7976-9_23)
2022
"""
)