example.py

import matplotlib.pyplot as plt
import numpy as np

from plots import plot_map_rain, project_to_latlon

# Load the file
data = np.load("2020/202004201700.npz")  # Adjust path as needed
rain = data["arr_0"]  # The array is stored under 'arr_0'
print("Array shape:", rain.shape)  # Shape = (1536, 1536)

# Negative values indicate no data, replace them with NaN:
rain = np.where(rain < 0, np.nan, rain)

# Visualize
print("Making basic plot...")
plt.imshow(rain, cmap="Blues")
plt.colorbar(label="Rainfall (x0.01 mm / 5min)")
plt.title("Rainfall Accumulation – 2020-04-20 17:00 UTC")
plt.savefig("rainfall_20200420_1700_basic.png")
plt.close()

print("Converting and projecting rainfall data...")
rain = rain / 100  # Convert from mm10-2 to mm
rain = rain * 60 / 5  # Convert from mm to mm/h
da_reproj = project_to_latlon(rain)
print(da_reproj)

print("Plotting projected rainfall data...")
plot_map_rain(
    data=da_reproj,
    title="Rainfall Rate – 2020-04-20 17:00 UTC",
    path="rainfall_20200420_1700_map.png",
)