ledmap.py

#!/usr/bin/env python3

# This script generates a wled mapping for the Hackbow LED sculpture at NYC Resistor.
import json
import pandas as pd

number_bars = 18
number_leds = 60
height = 100

# Relative offsets from left to right, in centimeters. 0.0 is highest.
# Max is 32.9, min is 9.1, diff is 23.8 = 39.6666 LEDs. 
offsets = [
    21.2, 13.8, 12.2, 9.1, 11.3, 19.7, 22.8, 29.8, 32.9, 28.1,
    25.2, 22.2, 16.2, 14.3, 18, 21.7, 24.5, 25.8,
]

max_virtual_leds = int(max(offsets) / (height / number_leds))

# Create an empty DataFrame
led_df = pd.DataFrame()

for bar in range(0, number_bars):
    distance_above_bottom = max(offsets) - offsets[bar]
    bottom_virtual_leds = round(distance_above_bottom / (height / number_leds))
    distance_below_top = offsets[bar] - min(offsets)
    top_virtual_leds = round(distance_below_top / (height / number_leds))

    led_column = []

    for bottom_virtual_led in range(0, bottom_virtual_leds):
        led_column.append(-1)

    if bar % 2 == 1:
        for led in range(bar * number_leds, (bar + 1) * number_leds):
            led_column.append(led)
    else:
        for led in range((bar + 1) * number_leds - 1, bar * number_leds - 1, -1):
            led_column.append(led)

    for top_virtual_led in range(0, top_virtual_leds):
        led_column.append(-1)

    # Add the column to the DataFrame, reversed
    led_df[f'Bar_{bar}'] = pd.Series(led_column[::-1])

# Get the height and width of the DataFrame
df_height, df_width = led_df.shape

# Flatten the DataFrame values into a 1D list
flat_list = led_df.values.flatten().tolist()

# Define a variable for the n parameter
n = "Hackbow with virtual LEDs"

# Create a JSON object with the required format
output_json = {
    "n": n,
    "width": df_width,
    "height": df_height,
    "map": flat_list
}

# Print the JSON object
print(json.dumps(output_json))