Verified Game


- Platform: Android
- Updated: 24.01.2025
- Android version: 5.0
-
Language:
- Current version: 2021.6.30
- Google Play: open
Take control of a tiny flying craft in Voxel Fly. Maneuver left and right to avoid obstacles on your journey. Explore the bustling streets of a city in this thrilling Android game. But beware, the skies are crowded with other flying vehicles. Your mission is to navigate your craft as far as possible without any mishaps. Dodge incoming traffic, beat high scores, and unlock new flying machines.
Game highlights:
- Sleek, minimalist graphics
- Easy-to-use controls
- Leaderboards to compete with friends
- Exciting and fast-paced gameplay<|endoftext|><|endoftext|><|endoftext|> \begin{tikzpicture}[scale=0.8]
\begin{axis}[
xlabel=$x$,
ylabel=$y$,
xmin=-1,
xmax=1,
ymin=-1,
ymax=1,
axis lines=center,
axis equal,
xtick={-1,-0.5,0,0.5,1},
ytick={-1,-0.5,0,0.5,1},
legend pos=outer north east,
legend style={draw=none},
legend cell align=left,
samples=100,
smooth,
]
\addplot[domain=-1:1,blue,thick] {x^2};
\addlegendentry{$y=x^2$}
\addplot[domain=-1:1,red,thick] {x^3};
\addlegendentry{$y=x^3$}
\end{axis}
\end{tikzpicture}<|endoftext|>x = 1, y = 2<|endoftext|># -*- coding: utf-8 -*-
"""
Created on Mon Mar 2 14:44:44 2020
This script is used to generate the data for the paper "A new approach to
estimate the number of clusters in a dataset". It generates a dataset with
a given number of clusters and a given number of points per cluster. The
clusters are generated using a Gaussian distribution with a given mean and
standard deviation. The data is then saved in a CSV file.
The script takes the following arguments:
- n_clusters: the number of clusters to generate
- n_points: the number of points per cluster
- mean: the mean of the Gaussian distribution
- std: the standard deviation of the Gaussian distribution
- output_file: the name of the CSV file to save the data in
Example usage:
python generate_data.py --n_clusters 3 --n_points 100 --mean 0 --std 1 --output_file data.csv
"""
import argparse
import numpy as np
import pandas as pd
# Parse the arguments
parser = argparse.ArgumentParser()
parser.add_argument('--n_clusters', type=int, default
