File:Inserter Efficiency Graph (No Capacity Bonus).png

Graph showing efficiency of different inserters at different throughputs. This version has no capacity bonus. Intersection point at [~1.25418, 25] where stack inserters become more efficient than blue inserters has been marked with a dot.

This is the matplot code used to generate this graph in python, in case it needs to be updated:

import matplotlib.pyplot as plt import numpy as np

burner_speed = 60 / 76 yellow_speed = 60 / 70 red_speed = 60 / 50 blue_speed = 60 / 24

yellow_drain = 0.4 blue_drain = 0.5 green_drain = 1

burner_energy = 66.9 yellow_energy = 6.65 red_energy = 7 blue_energy = 8.12 green_energy = 23.2 stack_energy = 46.4

stack_size = 1 green_stack = 2 stack_stack = 6

x = np.linspace(0, blue_speed * stack_stack, 300)

yellow_count = np.trunc(x / (yellow_speed * stack_size)) + 1 red_count = np.trunc(x / (red_speed * stack_size)) + 1 blue_count = np.trunc(x / (blue_speed * stack_size)) + 1 green_count = np.trunc(x / (blue_speed * green_stack)) + 1

dynamic_stack = x / stack_size dynamic_green = x / green_stack dynamic_stacker = x / stack_stack

burner = burner_energy * dynamic_stack yellow = (yellow_energy * dynamic_stack) + (yellow_drain * yellow_count) red = (red_energy * dynamic_stack) + (yellow_drain * red_count) blue = (blue_energy * dynamic_stack) + (blue_drain * blue_count) green = (green_energy * dynamic_green) + (green_drain * green_count) stack = (stack_energy * dynamic_stacker) + green_drain

fig = plt.figure(figsize = (20, 15)) ax = plt.axes()

ax.plot(x, burner, label = "Burner", color = "black") ax.plot(x, yellow, label = "Yellow", color = "orange") ax.plot(x, red, label = "Red", color = "red") ax.plot(x, blue, label = "Blue", color = "blue") ax.plot(x, green, label = "Green", color = "green") ax.plot(x, stack, label = "Stack", color = "purple")

xlim = blue_speed * stack_stack ylim = (stack_energy / stack_stack) * xlim

ax.set_ylim(0, ylim) ax.set_xlim(0, xlim)

xtick = 0.5 ytick = 2

ax.set_xticks(np.arange(0, xlim + xtick, xtick)) ax.set_yticks(np.arange(0, ylim + ytick, ytick))

ax.set_title("Inserter Efficiency (No Capacity Bonus)") ax.set_xlabel("Items / second", fontweight = "bold") ax.set_ylabel("Power Cost (kW)", fontweight = "bold")

ax.grid() ax.legend(loc = "best")

intersect = np.argwhere(np.diff(np.sign(blue - stack))).flatten() plt.plot(x [intersect], stack[intersect] , 'ro')

plt.show()

The wiki seems to not parse line breaks correctly but that can easily be handled by the end user.