main.py

import sys

import matplotlib.pyplot as plt
import numpy as np

import read_pdf
from utils.calculate_growth_rate import calculate_growth_rate
from utils.replace_text import replace_text

# Step 1: Extract data from the PDF
data = read_pdf.extract_data_from_pdf(sys.argv[1])

# Step 2: Assign data to variables
quarters = data['quarters']
data_center = data['data_center']
gaming = data['gaming']
professional_visualization = data['professional_visualization']
auto = data['auto']
oem_other = data['oem_other']
total = data['total']

# Step 3: Calculate growth rates as percentages with + or -
growth_rates = [calculate_growth_rate(total[i], total[i - 1]) if i != 0 else 0 for i in range(len(total))]

# Step 4: Print growth rates
for quarter, rate in zip(quarters[1:], growth_rates[1:]):
    print(f"{quarter}: {rate}%")

# Step 5: Plotting
x = np.arange(len(quarters))  # the label locations
width = 0.15  # the width of the bars
bar_positions = [x - 2 * width, x - width, x, x + width, x + 2 * width, x + 3 * width]
bar_labels = ['data_center', 'gaming', 'professional_visualization', 'auto', 'oem_other', 'total']
bar_data = [data_center, gaming, professional_visualization, auto, oem_other, total]

fig, ax = plt.subplots(figsize=(14, 8))

rects = []
for pos, label, data in zip(bar_positions, bar_labels, bar_data):
    rect = ax.bar(pos, data, width, label=replace_text(label))
    rects.append(rect)

# Step 6: Add growth rate annotations
for i, rate in enumerate(growth_rates):
    ax.annotate(f'{rate}%', (x[i], total[i]), textcoords="offset points", xytext=(0, 5), ha='center')

# Step 7: Add some text for labels, title, and custom x-axis tick labels, etc.
ax.set_xlabel('Quarter')
ax.set_ylabel('Revenue ($ in millions)')
ax.set_title('NVIDIA Quarterly Revenue Trend by Market')
ax.set_xticks(x)
ax.set_xticklabels(quarters)
ax.legend()

# Rotate the tick labels for better readability
plt.xticks(rotation=45)

# Step 8: Adjust layout and save the figure
fig.tight_layout()
plt.savefig('nvidia-revenue-trend.png')
plt.show()