app.py

import gradio as gr
import numpy as np
from mdutils import MdUtils
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import base64
import io
import json

WIDTH = 10
HEIGHT = 4


def generate_charts(unique, counts, d, format="png", grayscale: bool = True) -> dict:
    plot = io.BytesIO()
    hist = io.BytesIO()
    pie = io.BytesIO()

    # Generate Plot
    fig = plt.figure(figsize=(WIDTH, HEIGHT))
    ax = fig.add_subplot()
    ax.yaxis.set_major_locator(ticker.MultipleLocator(1))
    if grayscale:
        ax.plot(unique.astype("str"), counts, marker="o", color="black")
    else:
        ax.plot(unique.astype("str"), counts, marker="o", color="blue")
    plt.savefig(plot, bbox_inches="tight", orientation="landscape", format=format)

    # Generate Histogram
    fig, ax = plt.subplots(figsize=(WIDTH, HEIGHT))
    if grayscale:
        ax.bar(x=[str(i) for i in unique], height=counts, width=0.5, color=["black"])
    else:
        ax.bar(x=[str(i) for i in unique], height=counts, width=0.5, color=["blue"])
    plt.savefig(hist, bbox_inches="tight", format=format)

    # Generate Pie Chart
    fig, ax = plt.subplots(figsize=(WIDTH, HEIGHT))
    if grayscale:
        ax.pie(
            list(d.values()),
            labels=list(d.keys()),
            colors=["black", "grey"],
            wedgeprops={
                "edgecolor": "white",
                "linewidth": 0.7,
            },
        )
    else:
        ax.pie(
            list(d.values()),
            labels=list(d.keys()),
            wedgeprops={
                "edgecolor": "white",
                "linewidth": 0.7,
            },
        )
    plt.savefig(pie, format=format)

    plot.seek(0)
    hist.seek(0)
    pie.seek(0)

    plot_content = base64.b64encode(plot.read()).decode()
    hist_content = base64.b64encode(hist.read()).decode()
    pie_content = base64.b64encode(pie.read()).decode()

    return {"plot": plot_content, "hist": hist_content, "pie": pie_content}


def add_image_b64(mdfile: MdUtils, image_content: str, format: str = "png"):
    mdfile.new_paragraph(f"<img src='data:image/{format};base64,{image_content}'>")
    mdfile.new_line()


def make_all(numbers, grayscale: bool):
    arr = np.array(numbers)

    unique, counts = np.unique(arr, return_counts=True)
    d = dict(zip(unique, counts))  # Counts of number of occurences
    mode = ", ".join(
        [
            str(unique[i])
            for i in np.argwhere(counts == np.max(counts)).flatten().tolist()
        ]
    )
    mean = np.mean(arr)
    rng = np.max(arr) - np.min(arr)
    vrnc = np.var(arr)

    mdFile = MdUtils(
        file_name="Практическая работа по статистике",
        title="Практическая работа по статистике",
    )

    mdFile.new_paragraph(",".join([str(x) for x in arr]))
    mdFile.new_paragraph(",".join([str(x) for x in sorted(arr)]))
    mdFile.new_paragraph(f"Размах: {rng}")
    mdFile.new_paragraph(f"Мода: {mode}")
    mdFile.new_paragraph(f"А ср.: {mean:.2f}")
    mdFile.new_paragraph(f"D = {vrnc:.2f}")
    list_of_strings = ["Элемент"]

    for x in d:
        list_of_strings.extend([f"{str(x)}"])
    list_of_strings.append("Кол-во")
    for value in d.values():
        list_of_strings.extend([f"{str(value)}"])

    mdFile.new_line()
    mdFile.new_table(
        columns=len(d) + 1, rows=2, text=list_of_strings, text_align="center"
    )
    mdFile.new_line()

    # Insert Images
    charts = generate_charts(unique, counts, d, "png", grayscale)

    mdFile.new_paragraph("<center>")

    add_image_b64(mdFile, charts["plot"], "png")
    add_image_b64(mdFile, charts["hist"], "png")
    add_image_b64(mdFile, charts["pie"], "png")

    mdFile.new_paragraph("</center>")

    # mdFile.create_md_file()

    mdFile2 = MdUtils(file_name="Практическая работа по статистике_2")
    mdFile2.new_paragraph("## Расчет дисперсии по отклонениям и их квадратам")
    mdFile2.new_line()

    mdFile2.new_paragraph("<br><br>\n\n<center>")

    list_of_strings = ["Элемент", "Отклонение", "Квадрат отклонения"]

    for x in sorted(arr):
        list_of_strings.extend([f"{x}", f"{(mean - x):.2f}", f"{(mean - x) ** 2:.2f}"])

    mdFile2.new_line()
    mdFile2.new_table(
        columns=3,
        rows=len(arr) + 1,
        text=list_of_strings,
    )
    mdFile2.new_line()
    mdFile2.new_paragraph("</center>")

    mdfile_enc = mdFile.get_md_text()
    mdfile_var_enc = mdFile2.get_md_text()

    return mdfile_enc, mdfile_var_enc


def getints(numbers: str, grayscale: bool = True):
    ls = list(map(int, numbers.split(" ")))
    return make_all(ls, grayscale)


with open("examples.json") as jf:
    examples = json.load(jf)

iface = gr.Interface(
    fn=getints,
    inputs=[gr.Textbox(show_copy_button=True, label="Numbers"), "checkbox"],
    outputs=[
        gr.Textbox(show_copy_button=True, label="Chart"),
        gr.Textbox(show_copy_button=True, label="Variance"),
    ],
    title="Tilted Calculator",
    examples=examples,
)
iface.launch()