LU-Data-Visualisation/main.py
2023-12-25 20:03:29 +02:00

156 lines
4.0 KiB
Python
Executable File

#!/usr/bin/env python
import platform
import subprocess
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from loguru import logger
from matplotlib.backends.backend_pdf import PdfPages
logger.add(
Path("logs", "data.log"),
format="{time} | {level} | {message}",
level="INFO",
rotation="1 MB",
compression="zip",
)
BASE_PATH = Path(__file__).parent
WIND_GUSTS_PATH = BASE_PATH.joinpath("data", "vejaAtrumsBrazmas.xlsx")
WIND_SPEED_PATH = BASE_PATH.joinpath("data", "vejaAtrumsFaktiskais.xlsx")
AIR_TEMP_PATH = BASE_PATH.joinpath("data", "gaisaTemperatura2022.xlsx")
PDF_PATH = BASE_PATH.joinpath("plots.pdf")
BLUE = "#1f77b4"
ORANGE = "#ff7f0e"
BLACK = "#000000"
@logger.catch
def read_data(path: Path) -> pd.DataFrame:
dataframe = pd.read_excel(path, parse_dates=["Datums"], index_col="Datums", date_format="%d.%m.%Y")
logger.info(f"Read data from {path}")
return dataframe
@logger.catch
def create_bar_chart() -> plt.Figure:
df_avg: pd.Series = read_data(WIND_SPEED_PATH).mean(axis=1)
df_max: pd.Series = read_data(WIND_GUSTS_PATH).max(axis=1) - df_avg
df_combined: pd.DataFrame = pd.concat(
[df_avg, df_max],
axis=1,
)
fig, ax = plt.subplots(figsize=(12, 8))
df_combined.columns = ["Vidējais", "Maksimālais"]
df_combined.plot.bar(
stacked=True,
figsize=(12, 8),
color=[ORANGE, BLUE],
width=0.6,
ax=ax,
)
date_format = df_combined.index.strftime("%d.%m.%Y")
ax.set_xticks(np.arange(len(date_format)))
ax.set_xticklabels(date_format, rotation=45)
ax.set_yticks(np.arange(0, df_combined.max().max() + 2.5, 2.5))
ax.set_title("Vidējais un maksimālais vēja ātrums 2023. gada augustā")
ax.set_xlabel("Mērījumu Datums")
ax.set_ylabel("Vēja ātrums (m/s)")
logger.info("Created bar chart")
return fig
SEASONS: dict[int, str] = {
1: "Ziema",
2: "Pavasaris",
3: "Vasara",
4: "Rudens",
}
@logger.catch
def create_box_plot() -> plt.Figure:
df: pd.DataFrame = read_data(AIR_TEMP_PATH)
df["Season"] = df.index.month % 12 // 3 + 1
df["Season"] = df["Season"].map(SEASONS)
df["Average"] = df.iloc[:, 0:24].mean(axis=1)
seasonal_data: list[pd.Series] = [df[df["Season"] == season]["Average"] for season in SEASONS.values()]
fig, ax = plt.subplots(figsize=(12, 8))
ax.boxplot(
seasonal_data,
labels=SEASONS.values(),
showfliers=True,
boxprops=dict(facecolor=BLUE), # box
medianprops=dict(color=ORANGE), # median line
whiskerprops=dict(color=BLACK), # whiskers (vertical line between box and min/max)
patch_artist=True,
widths=0.4,
)
min_value: float = np.floor(df["Average"].min() / 5) * 5
max_value: float = np.ceil(df["Average"].max() / 5) * 5
tick_step: int = 5
ax.set_yticks(np.arange(min_value, max_value, tick_step))
ax.set_title("Gaisa temperatūra Rīgā četros gadalaikos")
ax.set_ylabel("Gaisa temperatūra (Celsija grādos)")
ax.set_xlabel("")
logger.info("Created box plot")
return fig
@logger.catch
def open_pdf(pdf_path: Path) -> None:
logger.info(f"Opening {pdf_path}")
system = platform.system().lower()
if system == "linux":
subprocess.run(["xdg-open", pdf_path], check=True)
elif system == "windows":
subprocess.run(["start", "", pdf_path], check=True)
elif system == "darwin": # macOS
subprocess.run(["open", pdf_path], check=True)
else:
logger.warning(f"Unsupported platform: {system}. Please open the PDF manually.")
@logger.catch
def main() -> None:
with PdfPages(PDF_PATH) as pdf:
fig1 = create_bar_chart()
pdf.savefig(fig1)
plt.close(fig1)
fig2 = create_box_plot()
pdf.savefig(fig2)
plt.close(fig2)
try:
open_pdf(PDF_PATH)
except Exception as e:
logger.error(e)
logger.warning("Something went wrong while opening the PDF. Please open it manually.")
if __name__ == "__main__":
main()