This project creates a metal detector using an Adafruit CLUE with a few common components and an easy-to-make coil.

The program is written in CircuitPython for version 5.1.0 or later. The code also runs on the Circuit Playground Bluefruit (CPB) with the TFT Gizmo screen. The program can be used without a screen on the CPB in audio/light mode only.

Alligator clips to male jumpers can be used with or without the Adafruit Dragontail to connect the CLUE and the coil to the breadboard. The pictures feature alternate products.

This project was inspired by an old Ray Marston book featuring a metal detector project and the Detectorists BBC TV series.

An Adafruit CLUE with a simple circuit on a breadboard detecting a metallised sticker with a coil.


CLUE version

1 x Adafruit CLUE
Adafruit CLUE - nRF52840 Express with Bluetooth LE
1 x Adafruit DragonTail
Adafruit DragonTail for micro:bit - Fully Assembled (or use 3 Alligator Clip to Male Jumper Wires)
1 x 1k Resistor
Through-Hole Resistors - 1.0K ohm 5% 1/4W - Pack of 25 (1 needed)

Circuit Playground Bluefruit with TFT Gizmo version

1 x Circuit Playground Bluefruit (CPB)
Circuit Playground Bluefruit - Bluetooth Low Energy
1 x Circuit Playground TFT Gizmo (LCD Screen)
Circuit Playground TFT Gizmo - Bolt-on Display + Audio Amplifier
2 x STEMMA 3-Pin to Male Header Cable
STEMMA JST PH 3-Pin to Male Header Cable - 200mm

Circuit Playground Bluefruit only version

1 x Circuit Playground Bluefruit (CPB)
Circuit Playground Bluefruit - Bluetooth Low Energy
1 x 1k Resistor
Through-Hole Resistors - 1.0K ohm 5% 1/4W - Pack of 25 (1 needed)


1 x USB 1m cable - A to Micro-B
USB cable - USB A to Micro-B - 3 foot long
1 x Half-size breadboard
Half-size breadboard
1 x Alligator Clip to Male Jumper Wires
Small Alligator Clip to Male Jumper Wire Bundle - 6 Pieces (2 needed for coil)
1 x Male/Male Jumper Wires
Premium Male/Male Jumper Wires - 40 x 3" (75mm)
1 x Signal Diode
1N4148 Signal Diode - 10 pack (1 needed)
1 x 0.1uF Capacitor
0.1uF ceramic capacitors - 10 pack (1 needed)
1 x 36ft (11m) Wire
Enameled Copper Magnet Wire – 11 meters / 0.1mm diameter (5-8m of most insulated wire will work fine)
1 x 3 x AAA Switched Battery Holder
3 x AAA Battery Holder with On/Off Switch and 2-Pin JST (if you want to be mobile!)
1 x AAA Batteries
Pack of 3
Michael Faraday's experiment to demonstrate inductance in 1831, engraving from Magnetism and Electricity by Arthur Poyser (1892). Primary coil (A) attached to battery (on right), secondary coil (B) attached to galvanometer (C).

Inductance is a key part of many technologies in daily life, for example:

  • charging - electric toothbrushes, the latest smartphones and some wireless, in-ear headphones;
  • heating - induction cooking with metal cookware;
  • communication - contactless smartcards using NFC, RFID tags and traditional tuning circuits for radios;
  • power supplies - transformers reduce the mains AC voltage to a more practical level;
  • metal detection - airport security, automatic car park exit gates, pipe/cable finders and hunting for treasure.

Leon Theremin's The Thing is an interesting, minimalist example of a resonant cavity microphone, the equivalent of using an inductor for LC tuning, an application of band-pass filtering.

Inductance and Permeability

A current flowing produces a magnetic field around it. Inductors are electrical components designed to store energy in that magnetic field. These are typically coils and often wrapped around a core. The magnetic field can be affected by:

  • the material it passes through, this property is referred to as magnetic permeability;
  • the presence of a conductor nearby changing the effective inductance of the coil from the induced eddy currents in that conductor creating their own magnetic field;
  • other magnetic fields.

These first two properties make the inductor useful for detecting conductive objects.

MAKE Presents: The Inductor is an excellent video introduction to inductors by Collin Cunningham.

Metal Detection

The effect of nearby conductors on an inductor makes them a useful component for detecting metal. A classic implementation of this in electronics uses heterodyning where the beat frequency from mixing an inductor-based search oscillator with a reference oscillator is output to headphones.

Beat Frequency From An Oscillator Pair

The schematic on the left from R.M. Marston's 20 Solid State Projects For The Home (1969) shows a transitor-based detector with two colpitts oscillators. One oscillator uses the search coil and the other a tuneable reference coil which the users adjust to reduce the beat frequency audio output to near 0Hz away from the target material.

RLC Filters

Filters can easily be created with a resistor (R), an inductor (L) and a capacitor (C). There are a variety of configurations of RLC filters and many of them could be used to filter the square wave output from a microcontroller which could then be sampled to check the attenuation of the filter which would vary with the inductance.

An initial test of this approach with an Adafruit CLUE and a low-pass filter didn't yield promising results. The plots below show theoretical plots for a band-stop (notch) filter made with a resistor and a parallel LC circuit which might be worth exploring.

Bode plot for a band-stop (notch) passive R-LC filter. The different lines are for various resistor values. The animation varies the inductance to show the frequency shift.

The lower resistor values might not be practical as they put a higher current demand on the GPIO port.

The annotated linear plot below is better for seeing how this attenuation could potentially be used to detect small variations in inductance.

A linear plot with an example measurement of signal magnitude at a specific frequency as the inductance varies.

This would require sampling the 989Hz signal to determine the attenuation by the filter. A high inductance is attractive here as it will lower the frequency making the determination of the attenuation more accurate.

A frequency sweeping approach is an alternative for finding the frequency of the filter. This is likely to be slower but it would be less ambiguous. A simple measurement approach at one frequency, say 2.741V, corresponds to two frequencies and therefore two different inductance values.

Charging a Capacitor with RLD

An Arduino-based project on Instructables uses an RL circuit with the output rectified with a diode which then charges a capacitor. The steps in the measurement of the inductance are:

  1. A few pulses are output through the circuit to charge the capacitor. A higher inductance will result in a higher final voltage across the capacitor.
  2. An analogue input then measures the capacitor's voltage with over-sampling aiming to improve the accuracy.
  3. The analogue input is changed momentarily to output mode to empty (sink) the charge from the capacitor.

A C++ program (sketch) on the Arduino Uno offers precise timing. This is essential for this approach to give accurate results for the inductance.

In CircuitPython, the pulseio library can be used for creating PWM signals and pulse trains with microsecond precision. In general, as an interpreted language with garbage collection, it does not offer precise timing. The unpredictable delay between step 1 and step 2 is likely to affect the final accuracy of the measurement causing sporadic, spurious indications.

Continuous Charge/Discharge with RLD

The previous approach can be used in a continuous fashion where a constant series of pulses flow through the RLD. A circuit diagram from the Falstad Circuit Simulator is shown below.

Circuit simulation of the continuous charging approach. The 200 milliohm resistor represents the parasitic resistance of the coil. The 400k is an estimate of the input impedance of the GPIO in analogue input mode. (This is a short animated loop hence the incorrect current flow on the right side of the diode.)

This design could be considered as an RL filter with an envelope detector.

The value of the capacitor affects how quickly it discharges. A tiny capacitance will cause a rapid discharge causing a ripple which may reduce the accuracy or complicate the voltage measurement. A large capacitor value will take time to charge and discharge and this could make the sensing unresponsive.

A value of 0.1uF (which can be written as 100nF) was chosen from experimental testing. For comparison, a simulation with 100pF (top left) shows a very undesirable 197mV of ripple whereas 0.1uF only has ~1mV ripple.

A small amount of steady voltage drop around 1mV is actually useful here to ensure over-sampling is an effective technique to improve the resolution. In the (unlikely) absence of noise or variation, a theoretically perfect analogue to digital converter (ADC) would output the same value repeatedly for a constant voltage. The ADC Analysis page takes a closer look at this.

Two Coil Systems

Modern metal detectors using the induction balanced approach use two, often partially overlapping search coils. One is used for transmitting and one for receiving. A relatively small overlap will create a section with increased sensitivity. These detectors can discriminate to some extent between metals by reporting on the phase difference between the transmitted and received signal. This is typically presented to the user as a numerical value with different ranges giving an approximate identification. Garrett's chart for their AT Pro metal detector is shown below.

Garrett AT Pro metal detector numeric target identifier chart.

CLUE Metal Detector

Some initial testing of the Continuous Charge/Discharge with RLD approach worked well so this was selected for the project.

The CLUE has an onboard LIS3MDL, a triple-axis magnetometer. This is a useful addition for finding magnets and magnetised items.

Microcontrollers vs Inductors

Three LEDs with a combined forward voltage of approximately 9V lit by a 1.5V battery with an inductor in series shown at 0.5x speed from Magic of Magnetism and Inductors by ElectroBOOM.

Microcontrollers vs Inductors

Inductors can generate high voltages which may exceed the desired levels in a circuit. The video above shows a single-cell battery connected to an inductor (top right) in series with three white LEDs. The white LEDs require over 9V to illuminate but a mere 1.5V battery is able to briefly illuminate them due to the inductor's effect.

In this case the red wire is being used to briefly short across the non-conducting LEDs to allow current to flow from the battery through the inductor. The inductor is storing energy in its magnetic field and this field products the momentary higher voltage as the red wire is removed from the circuit. This demonstration of voltage spikes suggests care is required when using inductors in circuits to keep voltage levels at normal levels to avoid damaging sensitive components.

TDK, a company founded on the invention of ferrite, offers an explanation of this below with a parallel version of the circuit lighting a 70V neon lamp from a 4.5V battery. This is from TDK's The Wonders of Electromagnetism: Power Inductors in Mobile Phones.

Explanation of self induction and generating voltage spikes with an inductor in parallel. Copyright TDK Corporation.

GPIO Protection

The general-purpose input/output (GPIO) pins on microcontrollers typically have some limited protection built-in for adverse voltages often to deal with static electricity (ESD). The CLUE board uses an nRF52 series chip and this has two internal diodes on each GPIO pin. The partial schematic below shows an example of how these these two diodes are used for one pin.

Partial schematic showing one example of a reverse-biased diode pair inside the nRF52840 microcontroller protecting input and output against over/under voltage. The CLUE board's 1M resistor to facilitate touch input is also shown.

The schematic shows the CLUE board's 1 Megaohm resistor. There's one resistor per large pad used for the capacitive touch implementation. The schematic also shows an external resistor. This is another precaution that's typically used to limit output current but it will also reduce any current flowing through these very small, protective diodes in the microcontroller.

The metal detector circuit on the next page uses a resistor primarily to limit the current from the P1 output but it will also reduce any adverse currents from under or over voltages caused by the inductor.

The square wave (3.3V pk-pk, 84% duty cycle) can be seen with and without the inductor in the circuit here. The inductor does cause a small negative voltage which briefly "peaks" at -0.6V on the P1 pin/pad. The magnitude and brevity of this spike and the current protection from the external 1k resistor mean the microcontroller is not at risk.

Larger Coil Currents

If more current was being used through the coil then an external protection diode capable of handling this higher current would be a wise precaution. The CLUE's nRF52840 can only supply low currents, higher currents would need a separate power supply and switching with a transistor. This could aid isolation of the GPIO from the maleffects of the voltage spikes.

Diodes are commonly found across motors, relays and solonoids protecting against back EMF and are sometimes referred to as "flyback" diodes.

Second version of coil, 28 turns around an 84mm (3.3in) diameter cylinder.

This page describes how the components are used on the breadboard to make the circuit for the metal detector. It also describes how to make and connect the coil.


The components in the circuit are:

  • R1 - 1k resistor.
  • D2 - 1N4148 signal diode (there is no D1).
  • C1 - 0.1uF (100nF) ceramic capacitor. These small capacitors are often labelled "104".
  • L1 - home-made coil.

The prototype was made with a 1N4004 rectifier diode and also tested with a germanium diode from a crystal radio set, both worked well and could be used as alternatives to the 1N4148 diode.

Coil Construction

A coil with about 4-8m (13-26ft) is a good starting point to avoid using too much wire. Insulated wire will work but "enamelled" copper wire allows a more compact coil. The enamel is a misnomer, the coating will be something like polyurethane varnish. This insulation must be scraped or burnt off with a soldering iron at the ends to expose the copper to connect it to the circuit.

The coil shown at the top of the page is enamelled 0.56mm wire wrapped around an 84mm tube (3.3in). It has 12 coils then 9 more coils over those then 7 coil more coils over those totalling 28. Placing the coils close to the edge improves the effective search range but care needs to be taken to ensure the coil does not fall off! A tiny ridge has been made on end of the tube with masking tape to reduce that risk.

The coil either needs to be very tight or held in place as movement of the wire in the coil will subtly affect the inductance and parasitic capacitance of the coil.

A prototype coil was also made (not shown) with 20 turns around a core of a roll of masking tape with diameter 116mm (4.6in). This worked well too.

Circuit Construction

The diagrams and pictures below show how the circuit can be implemented on a breadboard for the three different configurations.

CLUE board

The breadboard showing the use of the Dragontail breakout board to connect CLUE's #0 (P0) and #1 (P1) pads to circuit. The small inductor coil represents the large coil.

The coil needs to be connected to the breadboard. The options are:

  • Thick solid core wire may be directly inserted into the breadboard. Tinning the end with solder will increase the diameter of a wire and tame multi-strand wire.
  • A connector cable with male pins to alligator (crocodile) clips or hooks (shown below). These will be needed for the Adafruit enamelled wire.
Breadboard for metal detector circuit. The CLUE is connected via a KItronik Edge Connector Breakout Board out of shot. The blue and black leads at the bottom go to the coil. The diode is a 1N4148 signal diode.

The CLUE board can be connected using the Dragontail or alligator clips.

  • #0 (P0) yellow wire - this is the square wave output.
  • #1 (P1) green wire - this is an analogue input measuring the voltage across the capacitor.
  • GND black wire - this is only required if not using the  Dragontail. The Dragontail directly connects to the power rails on one side of the breadboard.
It's best to insert or remove a CLUE board from an edge connector with the power off to prevent inadvertent, transient short circuits.

Everything can be seen connected together in the picture below. A Kitronik Edge Connector Breakout Board for BBC micro:bit (over the top half of the breadboard) and Pimoroni IC hooks with pigtails (to connect the coil) have been used for this implementation.

Metal detector fully assembled. The blue and black wires/hooks to the inductor have been accidentally swapped around for this photo - the electrons will not be concerned about this.

The circuit can only be tested once the CLUE has the CircuitPython program on it. This is described on the next page.

If alligator clips are used they need to be carefully placed in the centre of the pad and protected from accidental nudges which could cause the alligator clip to connect across the small pads either side of #0, #1 or GND.

Circuit Playground Bluefruit with TFT Gizmo

The CPB board pads are not really accessible when the TFT Gizmo is attached and most of them are used for the Gizmo. The Gizmo has 3-pin STEMMA connectors for accessing A1 and A2. A pair of STEMMA 3-Pin to male cables are required to connect this to the breadboard.

The breadboard showing the Gizmo's STEMMA connections to the circuit. The small inductor coil represents the large coil. Note: 1k resistor is not needed here.

The connections are:

  • A1 STEMMA (square wave output):
    • red - breadboard red (+) rail (not used).
    • white (yellow sleeves) - breadboard b22.
    • black - breadboard black (-) rail.
  • A2 STEMMA (analogue input):
    • red - breadboard red (+) rail (not used).
    • white (green sleeves) - breadboard e26.
    • black - breadboard black (-) rail.
Metal Detector fully assembled. The TFT Gizmo is mounted on a Circuit Playground Bluefruit. The STEMMA cables have small sleeves on white signal cable to help distinguish them.

The TFT Gizmo has its own 1k resistors on the A1/A2 GPIO making the resistor on the breadboard superfluous.

The red power lines are not used but plugging the pins into the breadboard prevents them from accidentally contacting other components or shorting to ground.

The red power lines from the STEMMA connector on the TFT Gizmo are at VOUT level, i.e. 5V for USB power or the battery voltage.

Circuit Playground Bluefruit board only

The program still runs without a screen on a CPB board in audio/light mode.

The connections are:

  • A1 (square wave output) - yellow wire - breadboard a18.
  • A2 (analogue input) - green wire - breadboard e26.
  • GND - black wire - breadboard black (-) rail.
The breadboard showing the Circuit Playground Bluefruit connections to the circuit. The small inductor coil represents the large coil. Note: 1k resistor is needed here.

CircuitPython on CLUE

CircuitPython is a derivative of MicroPython designed to simplify experimentation and education on low-cost microcontrollers. It makes it easier than ever to get prototyping by requiring no upfront desktop software downloads. Simply copy and edit files on the CIRCUITPY flash drive to iterate.

The following instructions will show you how to install CircuitPython. If you've already installed CircuitPython but are looking to update it or reinstall it, the same steps work for that as well!

Set up CircuitPython Quick Start!

Follow this quick step-by-step for super-fast Python power :)

Click the link above to download the latest version of CircuitPython for the CLUE.

Download and save it to your desktop (or wherever is handy).

Plug your CLUE into your computer using a known-good USB cable.

A lot of people end up using charge-only USB cables and it is very frustrating! So make sure you have a USB cable you know is good for data sync.

Double-click the Reset button on the top (magenta arrow) on your board, and you will see the NeoPixel RGB LED (green arrow) turn green. If it turns red, check the USB cable, try another USB port, etc. Note: The little red LED next to the USB connector will pulse red. That's ok!

If double-clicking doesn't work the first time, try again. Sometimes it can take a few tries to get the rhythm right!

You will see a new disk drive appear called CLUEBOOT.

Drag the adafruit-circuitpython-clue-etc.uf2 file to CLUEBOOT.

The LED will flash. Then, the CLUEBOOT drive will disappear and a new disk drive called CIRCUITPY will appear.

If this is the first time you're installing CircuitPython or you're doing a completely fresh install after erasing the filesystem, you will have two files - boot_out.txt, and, and one folder - lib on your CIRCUITPY drive.

If CircuitPython was already installed, the files present before reloading CircuitPython should still be present on your CIRCUITPY drive. Loading CircuitPython will not create new files if there was already a CircuitPython filesystem present.

That's it, you're done! :)

CircuitPython on Circuit Playground Bluefruit

Install or Update CircuitPython

Follow this quick step-by-step to install or update CircuitPython on your Circuit Playground Bluefruit.

Click the link above and download the latest UF2 file

Download and save it to your Desktop (or wherever is handy)

Plug your Circuit Playground Bluefruit into your computer using a known-good data-capable USB cable.

A lot of people end up using charge-only USB cables and it is very frustrating! So make sure you have a USB cable you know is good for data sync.

Double-click the small Reset button in the middle of the CPB (indicated by the red arrow in the image). The ten NeoPixel LEDs will all turn red, and then will all turn green. If they turn all red and stay red, check the USB cable, try another USB port, etc. The little red LED next to the USB connector will pulse red - this is ok!

If double-clicking doesn't work the first time, try again. Sometimes it can take a few tries to get the rhythm right!

(If double-clicking doesn't do it, try a single-click!)

You will see a new disk drive appear called CPLAYBTBOOT.




Drag the adafruit_circuitpython_etc.uf2 file to CPLAYBTBOOT.

The LEDs will turn red. Then, the CPLAYBTBOOT drive will disappear and a new disk drive called CIRCUITPY will appear.

That's it, you're done! :)



Once you've gotten CircuitPython onto your CLUE or Circuit Playground Bluefruit (CPB) board, it's time to add some libraries. You can follow this guide page for the basics of downloading and transferring libraries to the board.

Libraries for Metal Detector for CLUE

From the library bundle you downloaded in that guide page, transfer the following libraries onto the CLUE board's /lib directory:

  • adafruit_apds9960
  • adafruit_bus_device
  • adafruit_display_notification
  • adafruit_display_text
  • adafruit_register
  • adafruit_display_shapes
  • adafruit_bmp280.mpy
  • adafruit_clue.mpy
  • adafruit_lis3mdl.mpy
  • adafruit_lsm6ds.mpy
  • adafruit_sht31d.mpy
  • adafruit_slideshow.mpy
  • neopixel.mpy

There are many libraries with similar names, take care on the selection.

Libraries for Metal Detector for Circuit Playground Bluefruit with TFT Gizmo

From the library bundle you downloaded in that guide page, transfer the following libraries onto the CPB board's /lib directory:

  • adafruit_gizmo
  • adafruit_circuitplayground
  • adafruit_display_shapes
  • adafruit_bus_device
  • adafruit_display_notification
  • adafruit_display_text
  • adafruit_register
  • adafruit_lis3dh.mpy
  • adafruit_thermistor.mpy
  • adafruit_st7789.mpy
  • neopixel.mpy

Development Testing

During development, the application was tested on a CLUE using CircuitPython 5.2.0 with libraries from the bundle. It should work on subsequent versions, the latest version is recommended for the CLUE.

A small amount of testing was also performed on a Circuit Playground Bluefruit with a TFT Gizmo.

Metal Detector

Metal detector start-up screen presenting the button guide shown on a TFT Gizmo attached to a Circuit Playground Bluefruit (CPB).

Download the CircuitPython file below renaming the to by clicking on the links and then using Save as... / Save link as... in the browser. The files are hosted on Adafruit's GitHub repo for this project.

Plug your CLUE/CPB board into your computer via a known-good USB data cable. A flash drive named CIRCUITPY should appear in your file explorer/finder program. Copy the file to the CIRCUITPY drive ensuring the is renamed to

Example Video

The video shows the CLUE version powered by a lithium polymer battery similar to the Adafruit 1200mAh Lithium Ion Polymer battery. Note: the CLUE and the CPB do not have an integrated charger.

In the video, when no object is being sensed, the voltage shown on the screen is around 1474mV and magnitude of the magnetic flux density difference is 0uT. The five hidden objects, in order, show the following voltages:

  • Through a large hardback book
    • a large metallic sticker, 1467mV.
  • Through a magazine
    • another Adafruit CLUE board, 1463mV;
    • a ferrite core from an inductor, 1477mV (note the value has increased);
    • a neodymium magnet, 1474mV and 28uT;
    • a large silver coin 1469mV.

The voltage will vary based on the inductance of the coil created for the metal detector. It will be about 300mV less if a rectifier diode like a 1N1004 is used. The voltage is about 200mV less on the Circuit Playground Bluefruit with TFT Gizmo for the same coil.


If the metal detector is not working, here's some tips based on observing the voltage.

  • Around 2950mV: the coil is not connected or the connection is hampered by insulation left on the enamelled wire.
  • Around 0mV: diode may be the wrong way around or something is not connected properly.
  • A few tens of mV: the yellow connection is probably from a high (3.3V) pin.
  • Voltage jumps around: probably a loose connection and/or ground is not attached. Wiggle and re-insert connections to find problematic one. Using alternate holes/rows on the breadboard can help sometimes.


The mV value across the capacitor is shown on screen. This value represents the inductance value. The detection of metal is based on a positive or negative change from the baseline value when no object is being sensed. A difference is indicated by a beeping sound, a bar graph with green for positive and red for negative and flashing of the NeoPixel(s) with a matching colour. The baseline value is assigned when the code first starts. It will also follow any changes after about ten seconds.

The uT reading (CLUE board only) is the magnitude of the difference between the magnetometer's z component only and the first value measured at start-up. This value is also shown as a filled blue circle, a slightly different beeping sound and flashing of the NeoPixel(s) in blue alternating with any mV related colour.

The use of the z component only is a crude approach to make the detector ignore the Earth's magnetic field. This allows the detector to be rotated as this changes the x and y values but not the z value. Tilting the device, as seen in the video when the metal detector is at the top of the screen, will unfortunately increase the value slightly.

The right button can be used to immediately reset the baseline for the voltage and the magnetic flux density. The left button toggles the audio, NeoPixel(s), screen and Mu output on and off depending on the duration of the button press.

Magnets at close proximity can permanently magnetise components on the CLUE board affecting the magnetometer! Keep them at least 10cm (4in) away from the CLUE.


A code discussion follows the code.

# clue-metal-detector v1.6
# A simple metal detector using a minimum number of external components

# Tested with an Adafruit CLUE (Alpha) and CircuitPython 5.2.0
# Tested with an Adafruit Circuit Playground Bluefruit with TFT Gizmo
# and CircuitPython 5.2.0

# CLUE: Pad P0 is an output and pad P1 is an input
# CPB: Pad/STEMMA A1 is an output and Pad/STEMMA A2 is an input

# copy this file to CLUE/CPB board as

# MIT License

# Copyright (c) 2020 Kevin J. Walters

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.


# pylint: disable=global-statement

import time
import math
import array
import os
import gc

import board
import pulseio
import analogio
import ulab

from displayio import Group
import terminalio

# These imports works on CLUE, CPB (and CPX on 5.x)
from audiocore import RawSample
    from audioio import AudioOut
except ImportError:
    from audiopwmio import PWMAudioOut as AudioOut

# displayio graphical objects
from adafruit_display_text.label import Label
from adafruit_display_shapes.rect import Rect
from import Circle

# Assuming CLUE if it's not a Circuit Playround (Bluefruit)
clue_less = "Circuit Playground" in os.uname().machine

if clue_less:
    # CPB with TFT Gizmo (240x240)
    from adafruit_circuitplayground import cp
    from adafruit_gizmo import tft_gizmo

    # Outputs
    display = tft_gizmo.TFT_Gizmo()
    audio_out = AudioOut(board.SPEAKER)
    min_audio_frequency = 100
    max_audio_frequency = 4000
    pixels = cp.pixels
    board_pin_output = board.A1

    # Enable the onboard amplifier for speaker
    cp._speaker_enable.value = True  # pylint: disable=protected-access

    # Inputs
    board_pin_input = board.A2
    magnetometer = None  # This indicates device is not present
    button_left = lambda: cp.button_b
    button_right = lambda: cp.button_a

    # CLUE with builtin screen (240x240)
    from adafruit_clue import clue

    # Outputs
    display = board.DISPLAY
    audio_out = AudioOut(board.SPEAKER)
    min_audio_frequency = 100
    max_audio_frequency = 5000
    pixels = clue.pixel
    board_pin_output = board.P0

    # Inputs (buttons reversed as it is used upside-down with Gizmo)
    board_pin_input = board.P1
    magnetometer = lambda: clue.magnetic
    button_left = lambda: clue.button_a
    button_right = lambda: clue.button_b

# Globals variables used r/w in functions
last_frequency = 0
last_negbar_len = None
last_posbar_len = None
last_mag_radius = None
text_overlay_gob = None
voltage_barneg_dob = None
voltage_sep_dob = None
voltage_barpos_dob = None
magnet_circ_dob = None

# Globals
debug = 1
screen_height = display.height
screen_width = display.width
samples = []

# Other globals
quantize_tones = True
audio_on = True
screen_on = True
mu_output = False
neopixel_on = True

# Used to alternate/flash the NeoPixel
neopixel_alternate = True

# Some constants used in start_beep()
BASE_NOTE = 261.6256  # C4 (middle C)
QUANTIZE = 4          # determines the "scale"


# There's room for 80 pixels but 60 draws a bit quicker

VOLTAGE_FMT = "{:6.1f}"
MAG_FMT = "{:6.1f}"

INFO_FG_COLOR = 0x000080
INFO_BG_COLOR = 0xc0c000
BLACK_TUPLE = (0, 0, 0)

RED     = 0xff0000
GREEN75 = 0x00c000
BLUE    = 0x0000ff
WHITE75 = 0xc0c0c0

FONT_WIDTH, FONT_HEIGHT = terminalio.FONT.get_bounding_box()

# Thresholds below which audio is silent and NeoPixels are dark
threshold_voltage = 0.002
threshold_mag = 2.5

def d_print(level, *args, **kwargs):
    """A simple conditional print for debugging based on global debug level."""
    if not isinstance(level, int):
        print(level, *args, **kwargs)
    elif debug >= level:
        print(*args, **kwargs)

# Adapted and borrowed from clue-plotter v1.14
def wait_release(text_func, button_func, menu):
    """Calls button_func repeatedly waiting for it to return a false value
       and goes through menu list as time passes.

       The menu is a list of menu entries where each entry is a
       two element list of time passed in seconds and text to display
       for that period. Text is displayed by calling text_func(text).
       The entries must be in ascending time order."""

    start_t_ns = time.monotonic_ns()
    menu_option = None
    selected = False

    for menu_option, menu_entry in enumerate(menu):
        menu_time_ns = start_t_ns + int(menu_entry[0] * 1e9)
        menu_text = menu_entry[1]
        if menu_text:
        while time.monotonic_ns() < menu_time_ns:
            if not button_func():
                selected = True
        if menu_text:
        if selected:

    return (menu_option, (time.monotonic_ns() - start_t_ns) * 1e-9)

def popup_text(text_func, text, duration=1.0):
    """Place some text on the screen using info property of Plotter object
       for duration seconds."""

def show_text(text):
    """Place text on the screen. Empty string or None clears it."""
    global screen_group, text_overlay_gob

    if text:
        font_scale = 3
        line_spacing = 1.25

        text_lines = text.split("\n")
        max_word_chars = max([len(word) for word in text_lines])
        # If too large reduce the scale to 2 and hope!
        if (max_word_chars * font_scale * FONT_WIDTH > screen_width
                or (len(text_lines) * font_scale
                    * FONT_HEIGHT * line_spacing) > screen_height):
            font_scale -= 1

        text_overlay_gob = Label(terminalio.FONT,
        # Centre the (left justified) text
        text_overlay_gob.x = (screen_width
                              - font_scale * FONT_WIDTH * max_word_chars) // 2
        text_overlay_gob.y = screen_height // 2
        if text_overlay_gob is not None:
            text_overlay_gob = None

def voltage_bar_set(volt_diff):
    """Draw a bar based on positive or negative values.
       Width of 60 is performance compromise as more pixels take longer."""
    global voltage_sep_dob, voltage_barpos_dob, voltage_barneg_dob
    global last_negbar_len, last_posbar_len

    if voltage_sep_dob is None:
        voltage_sep_dob = Rect(160, VOLTAGE_BAR_HEIGHT,
                               VOLTAGE_BAR_WIDTH, VOLTAGE_BAR_SEP_HEIGHT,

    if volt_diff < 0:
        negbar_len = max(min(-round(volt_diff * 5e3),
                             VOLTAGE_BAR_HEIGHT), 1)
        posbar_len = 1
        negbar_len = 1
        posbar_len = max(min(round(volt_diff * 5e3),
                             VOLTAGE_BAR_HEIGHT), 1)

    if posbar_len == last_posbar_len and negbar_len == last_negbar_len:

    if voltage_barpos_dob is not None:
    if posbar_len > 0:
        voltage_barpos_dob = Rect(160, VOLTAGE_BAR_HEIGHT - posbar_len,
                                  VOLTAGE_BAR_WIDTH, posbar_len,
        last_posbar_len = posbar_len

    if voltage_barneg_dob is not None:
    if negbar_len > 0:
        voltage_barneg_dob = Rect(160,
                                  VOLTAGE_BAR_HEIGHT + VOLTAGE_BAR_SEP_HEIGHT,
                                  VOLTAGE_BAR_WIDTH, negbar_len,
        last_negbar_len = negbar_len

def magnet_circ_set(mag_ut):
    """Display a filled circle to represent the magnetic value mag_ut in microteslas."""
    global magnet_circ_dob
    global last_mag_radius

    # map microteslas to a radius with minimum of 1 and
    # maximum of MAG_MAX_RADIUS
    radius = min(max(round(math.sqrt(mag_ut) * 4), 1), MAG_MAX_RADIUS)

    if radius == last_mag_radius:

    if magnet_circ_dob is not None:
    magnet_circ_dob = Circle(60, 180, radius, fill=BLUE)

def manual_screen_refresh(disp):
    """Refresh the screen as immediately as is currently possibly with refresh method."""
    refreshed = False
    while True:
            # 1000fps is fastest library allows - this high value
            # minimises any delays this refresh() method introduces
            refreshed = disp.refresh(minimum_frames_per_second=0,
        except RuntimeError:
        if refreshed:

def neopixel_set(pix, d_volt, mag_ut):
    """Set all the NeoPixels to an alternating colour
       based on voltage difference and
       magnitude of magnetic flux density difference."""
    global neopixel_alternate

    np_r, np_g, np_b = BLACK_TUPLE
    if neopixel_alternate:
        # RGB values are 8bit, hence the cap of 255 using min()
        if abs(d_volt) > threshold_voltage:
            if d_volt < 0.0:
                np_r = min(round(-d_volt * 8e3), 255)
                np_g = min(round(d_volt * 8e3), 255)
            if mag_ut > threshold_mag:
                np_b = min(round(mag_ut * 6), 255)

    pix.fill((np_r, np_g, np_b))  # Note: double brackets to pass tuple
    neopixel_alternate = not neopixel_alternate

def start_beep(freq, wave, wave_idx):
    """Start playing a continous beep based on freq and waveform specified by wave_idx.
       A frequency of 0 will stop the note playing.
       This quantizes the notes into a scale to make beeping sound more pleasant.
       This modifies the sample_rate property of the RawSample objects.
    global last_frequency
    if freq == 0:
        if last_frequency != 0:
            last_frequency = 0

    if quantize_tones:
        note_freq = BASE_NOTE * 2**((round(math.log(freq / BASE_NOTE)
                                           * POSTLOG_FACTOR)) / QUANTIZE)
        d_print(3, "Quantize", freq, note_freq)
        note_freq = freq

    (waveform, wave_samples_n) = wave[wave_idx]
    new_freq = round(note_freq * wave_samples_n)
    # Only set the new frequency if it's not the same as last one
    if new_freq != last_frequency:
        waveform.sample_rate = new_freq, loop=True)
        last_frequency = new_freq

def make_sample_list(levels=10,
    """Make a list of tuples of (RawSample, sample_length)
       with a sine wave of varying resolution from high to low.
       The lower resolutions sound crunchier and louder on the CLUE."""

    # Make a range of sample lengths, default is between 32 and 8
    sample_lens = [int((x*(range_l + .99)/(levels - 1)) + start_l)
                   for x in range(0, levels)]

    wavefs = []
    for s_len in sample_lens:
        raw_samples = array.array("H",
                                  [round(volume * math.sin(2 * math.pi
                                                           * (idx / s_len)))
                                   + AUDIO_MIDPOINT
                                   for idx in range(s_len)])
        sound_samples = RawSample(raw_samples)
        wavefs.append((sound_samples, s_len))

    return wavefs

waveforms = make_sample_list()

# For testing the waveforms
if debug >= 4:
    for idx in range(len(waveforms)):
        start_beep(440, waveforms, idx)
    start_beep(0, waveforms, 0)  # This silences it

# See for
# a comparison and performance analysis of alternate techniques for this
def sample_sum(pin, num):
    """Sample the analogue value from pin num times and return the sum
       of the values."""
    global samples   # Not strictly needed - indicative of r/w use
    samples[:] = [pin.value for _ in range(num)]
    return sum(samples)

# Initialise detector display
# The units are created as separate text objects as they are static
# and this reduces the amount of redrawing for the dynamic numbers

if magnetometer is not None:
    magnet_value_dob = Label(font=terminalio.FONT,
    magnet_value_dob.y = 90

    magnet_units_dob = Label(font=terminalio.FONT,
    magnet_units_dob.x = len(magnet_value_dob.text) * FONT_WIDTH * FONT_SCALE
    magnet_units_dob.y = magnet_value_dob.y

voltage_value_dob = Label(font=terminalio.FONT,
voltage_value_dob.y = 30

voltage_units_dob = Label(font=terminalio.FONT,
voltage_units_dob.y = voltage_value_dob.y
voltage_units_dob.x = len(voltage_value_dob.text) * FONT_WIDTH * FONT_SCALE

# 9 elements, 4 added immediately, 4 later, 1 spare for on-screen text
screen_group = Group(max_size=4 + 4 + 1)
if magnetometer is not None:

# Initialise some displayio objects and append them
# The following four variables are set by these two functions
# voltage_barneg_dob, voltage_sep_dob, voltage_barpos_dob
# magnet_circ_dob
if magnetometer is not None:

# Start-up splash screen

# Start-up splash screen
           "\n".join(["Button Guide",
                      "Left: audio",
                      "  2secs: NeoPixel",
                      "  4s: screen",
                      "  6s: Mu output",
                      "Right: recalibrate"]), duration=10)

# P1 or A2 for analogue input
pin_input = analogio.AnalogIn(board_pin_input)
CONV_FACTOR = pin_input.reference_voltage / 65535

# Start pwm output on P0 or A1
# 400kHz and 55000 (84%) duty_cycle were chosen empirically to maximise
# the voltage and the voltage drop detecting a small pair of metal scissors
pwm = pulseio.PWMOut(board_pin_output, frequency=400 * 1000,
                     duty_cycle=0, variable_frequency=True)
pwm.duty_cycle = 55000

# Get a baseline value for magnetometer
totals = [0.0] * 3
mag_samples_n = 10
if magnetometer is not None:
    for _ in range(mag_samples_n):
        mx, my, mz = magnetometer()
        totals[0] += mx
        totals[1] += my
        totals[2] += mz

base_mx = totals[0] / mag_samples_n
base_my = totals[1] / mag_samples_n
base_mz = totals[2] / mag_samples_n

# Wait a bit for P1/A2 input to stabilise
_ = sample_sum(pin_input, 3000) / 3000 * CONV_FACTOR
base_voltage = sample_sum(pin_input, 1000) / 1000 * CONV_FACTOR
voltage_value_dob.text = "{:6.1f}".format(base_voltage * 1000.0)

# Auto refresh off
display.auto_refresh = False

# Store two previous values of voltage to make a simple
# filtered value
voltage_zm1 = None
voltage_zm2 = None
filt_voltage = None

# Initialise the magnitude of the
# magnetic flux density difference from its baseline
mag_mag = 0.0

# Keep some historical voltage data to calculate median for re-baselining
# aiming for about 10 reads per second so this gives
# 20 seconds
voltage_hist = ulab.zeros(20 * 10 + 1, dtype=ulab.float)
voltage_hist_idx = 0
voltage_hist_complete = False
voltage_hist_median = None

# Reduce the frequency of the more heavyweight graphical changes
update_basic_graphics_period = 2
update_complex_graphics_period = 4
update_median_period = 5

counter = 0
while True:
    # Garbage collect now to reduce likelihood it occurs
    # during sample reading
    if debug >=2:
        d_print(2, "mem_free=" + str(gc.mem_free()))

    screen_updates = 0  # Used to determine if the screen needs a refresh

    # Take arithmetic mean of 500 samples but take a few more samples
    # if the loop isn't doing other work
    samples_to_read = 500  # About 23ms worth on CLUE
    update_basic_graphics = (screen_on
                             and counter % update_basic_graphics_period == 0)
    if not update_basic_graphics:
        samples_to_read += 150
    update_complex_graphics = (screen_on
                               and counter % update_complex_graphics_period == 0)
    if not update_complex_graphics:
        samples_to_read += 400
    update_median = counter % update_median_period == 0
    if not update_median:
        samples_to_read += 50
    # Read the analogue values from P1/A2
    sample_start_time_ns = time.monotonic_ns()
    voltage = (sample_sum(pin_input, samples_to_read)
               / samples_to_read * CONV_FACTOR)

    # Store the previous two voltage values
    voltage_zm2 = voltage_zm1
    voltage_zm1 = voltage

    if voltage_zm1 is None:
        voltage_zm1 = voltage
    if voltage_zm2 is None:
        voltage_zm2 = voltage

    filt_voltage = (voltage * 0.4
                    + voltage_zm1 * 0.3
                    + voltage_zm2 * 0.3)

    update_basic_graphics = counter % update_basic_graphics_period == 0
    update_complex_graphics = counter % update_complex_graphics_period == 0

    # Update text
    if update_basic_graphics:
        voltage_value_dob.text = VOLTAGE_FMT.format(filt_voltage * 1000.0)
        screen_updates += 1

    # Read magnetometer
    if magnetometer is not None:
        mx, my, mz = magnetometer()
        diff_x = mx - base_mx
        diff_y = my - base_my
        diff_z = mz - base_mz
        # Use the z value as a crude measure as this is
        # constant if the device is rotated and kept level
        mag_mag = math.sqrt(diff_z * diff_z)
        mag_mag = 0.0

    # Calculate a new audio frequency based on the absolute difference
    # in voltage being read - turn small voltages into 0 for silence
    # between 100Hz (won't be audible)
    # and 5000 (loud on CLUE's miniscule speaker)
    diff_v = filt_voltage - base_voltage
    abs_diff_v = abs(diff_v)
    if audio_on:
        if abs_diff_v > threshold_voltage or mag_mag > threshold_mag:
            frequency = min(min_audio_frequency + abs_diff_v * 5e5,
            frequency = 0  # silence
        start_beep(frequency, waveforms,
                   min(int(mag_mag / 2), len(waveforms) - 1))

    # Update the NeoPixel(s) if enabled
    if neopixel_on:
        neopixel_set(pixels, diff_v, mag_mag)

    # Update voltage bargraph
    if update_complex_graphics:
        screen_updates += 1

    # Update the magnetometer text value and the filled circle representation
    if magnetometer is not None:
        if update_basic_graphics:
            magnet_value_dob.text = MAG_FMT.format(mag_mag)
            screen_updates += 1
        if update_complex_graphics:
            screen_updates += 1

    # Update the screen with a refresh if needed
    if screen_updates:

    # Send output to Mu in tuple format
    if mu_output:
        print((diff_v, mag_mag))

    # Check for buttons and just for this section of code turn back on
    # the screen auto-refresh so the menus actually appear!
    display.auto_refresh = True
    if button_left():
        opt, _ = wait_release(show_text,
                                "Audio "
                                + ("off" if audio_on else "on")),
                                "NeoPixel "
                                + ("off" if neopixel_on else "on")),
                                "Screen "
                                + ("off" if screen_on else "on")),
                                "Mu output "
                                + ("off" if mu_output else "on"))
        if not screen_on or opt == 2:  # Screen toggle
            screen_on = not screen_on
            if screen_on:
                display.brightness = 1.0
                display.brightness = 0.0
        elif opt == 0:  # Audio toggle
            audio_on = not audio_on
            if not audio_on:
                start_beep(0, waveforms, 0)  # Silence
        elif opt == 1:  # NeoPixel toggle
            neopixel_on = not neopixel_on
            if not neopixel_on:
                neopixel_set(pixels, 0.0, 0.0)
        else:  # Mu toggle
            mu_output = not mu_output

    # Set new baseline voltage and magnetometer on right button press
    if button_right():
                     [(2, "Recalibrate")])
        d_print(1, "Recalibrate")
        base_voltage = voltage
        voltage_hist_idx = 0
        voltage_hist_complete = False
        voltage_hist_median = None
        if magnetometer is not None:
            base_mx, base_my, base_mz = mx, my, mz

    display.auto_refresh = False

    # Add the current voltage to the historical list
    voltage_hist[voltage_hist_idx] = voltage
    if voltage_hist_idx >= len(voltage_hist) - 1:
        voltage_hist_idx = 0
        voltage_hist_complete = True
        voltage_hist_idx += 1

    # Adjust the reference base_voltage to the median of historical values
    if voltage_hist_complete and update_median:
        voltage_hist_median = ulab.numerical.sort(voltage_hist)[len(voltage_hist) // 2]
        base_voltage = voltage_hist_median

    d_print(2, counter, sample_start_time_ns / 1e9,
            voltage * 1000.0,
            filt_voltage * 1000.0, base_voltage, voltage_hist_median)

    counter += 1

Code Discussion

The high level design is straightforward.

  1. Output a square wave on a pin.
  2. Store a baseline value from the other pin configured as an analogue input which is measuring the voltage across the capacitor.
  3. Store a baseline value for the z component of the magnetometer (if present).
  4. Take the difference from the current analogue input and the baseline and present this value to the user.
  5. Take the magnitude of the difference from the current z component of the magnetometer and the baseline and present this value to the user.
  6. Check the two buttons for user inputs.
  7. Go to step 4.

Only the buttons are used for the user interface on the CLUE. There is one spare touch capable pad but this isn't really accessible if an edge connector is used.

Voltage from ADC Values

The ADC values are easily read in CircuitPython using an AnalogIn object's value property. This value ranges from 0 to 65535 (a 16bit value) regardless of the number of bits returned by the ADC. The nRF52840 is configured in 12bit ADC mode by the CircuitPython interpreter. This means values will always be multiples of 16.

One surprise is these values can vary even with a stable voltage source like a battery. An extreme example from some real data for consecutive values is:

  1. 25152 = 1266.5mV
  2. 28848 = 1452.6mV
  3. 28608 = 1440.5mV

In the case of this metal detector, a 3mV difference represents a small metallic object, but the ADC is infrequently producing output which hugely deviates from the actual value. Even the second and third values have a 12.1mV difference.

A common approach is to take multiple samples and then take the average (arithmetic mean) of those values with the aim of reducing the effect of this variance. The sample_sum() function below does most of this job, it leaves the division by num to the caller.

Download: file
def sample_sum(pin, num):
    """Sample the analogue value from pin num times and return the sum
       of the values."""
    global samples
    samples[:] = [pin.value for _ in range(num)]
    return sum(samples)

This is one of the most efficient ways to read multiple samples with a rate of around 21-22 thousand samples per second (ksps) on an nRF52840. It also stores them in case further data analysis is required. The use of global here isn't strictly required but arguably it's useful to indicate the function changes the global list samples. The values are intentionally processed here as int and not float to improve the performance. The use of slice assignment is an attempt. probably unsuccessful, to stop the interpreter generating a temporary list to store all the sample values.

The performance of different approaches to reading many samples is shown in Adafruit Forums: Analogue Sampling at high rates plus ulab.

The validity of using the average of a number of consecutive samples to accurately represent the real voltage is examined on the next page.

Using Global Variables in Python

In Python, global must be used inside a function (or method) to declare usage of a variable if assignment occurs. This prevents Python from creating a new local variable. An example from the program is shown below.

Download: file
def magnet_circ_set(mag_ut):
    """Display a filled circle to represent the magnetic value mag_ut in microteslas."""
    global magnet_circ_dob
    global last_mag_radius

    radius = min(max(round(math.sqrt(mag_ut) * 4),

    if radius == last_mag_radius:

    if magnet_circ_dob is not None:
    magnet_circ_dob = Circle(60, 180, radius, fill=BLUE)

Pylint picks up on use of global and issues a W0603: Using the global statement (global-statement) warning. Variables with a large scope which are not truly constant can make a program difficult to understand and lead to bugs - global variables are the most extreme version of this. In a small program they tend not to be problematic but small programs can gradually become much larger ones. In the above case the variables have:

  • a clear, specific, semi-documented purpose
  • and a very low probability of being used elsewhere in the code in the future.

The current code does limit the display to a single circle/value. If the program was likely to grow over time or there was a potential need to display multiple circles/values then creating a new class would be an attractive option to encapsulate this data replacing the use of global variables.

In other languages, global variables can cause limitations or bugs from ill-considered use due to multi-threading or re-entrancy issues. The evolution of errno is one important example of a global variable used by UNIX libraries which had to be enhanced to support true multi-threading by conversion into a function.

Positional Arguments

The majority of programming languages use positional arguments (parameters) to functions. An example from the code is show below with the body of the procedure not shown for brevity.

Download: file
def neopixel_set(pix, d_volt, mag_ut):
    """Set all the NeoPixels to an alternating colour
       based on voltage difference and
       magnitude of magnetic flux density difference."""

The three values are clearly very different:

  1. pix - an object for the NeoPixels, the fill() method is used on it.
  2. d_volt - a difference value which may be positive or negative in volts.
  3. mag_ut - a magnetic value in microteslas which happens to be a magnitude of a difference value so is always non-negative.

A scientist would clearly see there are two quantities with very different units. Python traditionally didn't have any typing that would indicate if the procedure was used with the arguments in the wrong order and during development the numerical arguments were briefly reversed by accident. The use of keyword (named) arguments can make this less likely to occur, particularly with functions which take a huge number of arguments. Keyword arguments are only mandatory in Python after * in the argument list.

CircuitPython supports type hints (PEP-484) which improves the results from static analysis tools like pylint. This can reduce bugs in this area but will not eliminate them.

Practical Issues with displayio Graphics

Drawing items on the TFT LCD screen on these boards is a slow process compared to a modern desktop computer. This is particularly noticeable when drawing large objects using the adafruit_display_shapes library.

The program uses a variety of techniques to try and keep the main loop executing at a reasonable and approximately constant rate both especially when a significant object is detected.

  1. The default automatic screen refresh is replaced by a manual refresh once per loop to CPU cycles are not spent on interim, fruitless, partial screen updates.
  2. The MAG_MAX_RADIUS seen in the magnet_circ_set() procedure above serves to ensure the filled circle fits on screen. It's set slightly smaller than the screen area it occupies to reduce the performance impact of drawing very large circles.
  3. Screen objects which are slow to update are reduced in frequency with an "only every N times" approach in the main loop.
  4. The number of samples read adapts to other balance other activity in the loop to keep the execution rate more constant.
  5. Graphical objects are not updated if the screen has been turned off in the program by the user.
  6. The numerical values on screen are split into two Label objects to separate the dynamic value and the static units ("uT" and "mV").

The third, fourth and fifth optimisations are shown in an excerpt below from the main loop.

Download: file
# An excerpt from main loop
    samples_to_read = 500  # About 23ms worth on CLUE
    update_basic_graphics = (screen_on
                             and counter % update_basic_graphics_period == 0)
    if not update_basic_graphics:
        samples_to_read += 150
    update_complex_graphics = (screen_on
                               and counter % update_complex_graphics_period == 0)
    if not update_complex_graphics:
        samples_to_read += 400
    update_median = counter % update_median_period == 0
    if not update_median:
        samples_to_read += 50

This is setting three boolean variables, update_basic_graphics, update_complex_graphics and update_median, which are used to selectively execute certain computationally expensive parts of the loop and to increase the amount of sample reading if those operations are not taking place to balance the loop time and make practical use of this time. The first two values are calculated using screen_on to ensure they are False if the screen is not being used.

The displayio library has a builtin optimisation. Only areas of the screen which have been changed are sent to the TFT LCD screen. Internally these are processed as rectangular areas and marked as "dirty" when they've been changed to indicate the need to send them to the screen on the next refresh.

Filters with and without ulab Library

The main loop also has an extra level of filtering to try to further reduce any brief, transient variations of voltage - these could give a distracting, false indication. The simple code below shows how two previous voltage values can be stored in simple variables. The _zm1 suffix refers to z-1 which represents the unit delay in digital filter implementations

Download: file
# Store the previous two voltage values
    voltage_zm2 = voltage_zm1
    voltage_zm1 = voltage

These are then used to make a "filtered" version of the voltage by a multiplication by weights (coefficients) and summation.

Download: file
# Make a filtered voltage from three values
    filt_voltage = (voltage * 0.4
                    + voltage_zm1 * 0.3
                    + voltage_zm2 * 0.3)

This tiny low-pass, causal filter was improvised rather than designed but appears to work reasonably well to reduce the effect of transient spikes without introducing obvious delay.

CircuitPython 5.1.0 introduced the ulab library for boards with larger CPUs like the nRF52840 on the CLUE/CPB. This library is a cut-down version of numpy, providing very fast vector operations and efficient, flexible storage for arrays. The ulab approach for this can be seen on Low pass filtering: Measuring barometric Pressure. This type of filter is know as a Finite Impulse Response (FIR) filter. There is also a convolve function in ulab which can be used to perform this type of filtering across arrays.

The program does make some use of ulab. The unfiltered voltage values are continually stored in a fixed size 201 element float-based ulab ndarray. This is used in the style of a circular buffer storing the most recent 201 values. These values are then used to calculate the median voltage with the code shown below.

Download: file
# Adjust the reference base_voltage to the median of historical values
    if voltage_hist_complete and update_median:
        voltage_hist_median = ulab.numerical.sort(voltage_hist)[len(voltage_hist) // 2]
        base_voltage = voltage_hist_median

The code is updating the baseline voltage used as the datum for calculating the voltage difference used to indicate metal. This allows the code to deal with gradual shifts in the voltage level. An inevitable side-effect of this approach is the detector will incorrectly adjust the baseline if held over a metal object constantly for about ten seconds.

Magnetometer Baseline and Code Reviews

An informal code review by Jeff Epler highlighted an inconsistency in the program for setting the baseline value for the magnetometer. The code which initialises the values is shown below.

Download: file
# Get a baseline value for magnetometer
totals = [0.0] * 3
mag_samples_n = 10
if magnetometer is not None:
    for _ in range(mag_samples_n):
        mx, my, mz = magnetometer()
        totals[0] += mx
        totals[1] += my
        totals[2] += mz
base_mx = totals[0] / mag_samples_n
base_my = totals[1] / mag_samples_n
base_mz = totals[2] / mag_samples_n

The code used within the loop if the user pressed the right button to "Recalibrate" is a much simpler affair, shown below.

Download: file
# Excerpt from main loop inside if button_right():
        if magnetometer is not None:
            base_mx, base_my, base_mz = mx, my, mz

The issues here could be summarised as:

  • There's no explanation in comments or documentation for this inconsistency.
  • There's no explanation for the 0.05 (50ms) pause in the for loop.
  • A developer working on this code in the future is left to guess the reasons for this and possibly duplicate them without being able to justify the difference. 

The actual reason for the difference is the calibration feature was added very late in the development process and was not part of any initial design. The metal detector automatically adjusts the baseline for the voltage which represents the inductance and presence of metal. It does not do this for the magnetometer as this is a more stable value. In testing it turned out to be useful sometimes to set a new baseline for the magnetometer so this was added as a feature initiated by pressing the right button.

The small delay in the first code sample was based on prior observations whilst developing the code for CLUE Sensor Plotter in CircuitPython. The magnetometer issues duplicate values if read as fast as possible (~230Hz) in CircuitPython. This suggests it has a fixed rate for producing new values and the library does not wait (block) for a new value to be produced. The adafruit_lis3mdl library shows a set of different rates but does not document the default (the code shows it as 155Hz). The adafruit_clue library does not set an explicit rate which explains the duplication of results.

There's no particular reason for the difference in the number of samples. This is worth checking particularly on power-up to see if the sensor takes time to stabilise. The use case for user-initiated recalibration may specify it occurs within a certain amount of time - that would limit how many samples could be taken. In practical use, the magnetometer value is fairly stable for tenths of microteslas (uT).

This could be enhanced with:

  • A concise explanation in the comments and any documentation.
  • For both uses, call a single function which includes a parameter for the number of samples. This also ensures any future modifications (software maintenance) to the code are applied to both.

ADC Analysis

The normal distribution, also known as a Bell Curve, is a favourite of statisticians. The image is an engraving of second Big Ben Bell from The Illustrated News of the World (1858).

The CLUE and Circuit Playground Bluefruit boards both use the nRF52840 System on a Chip (SoC). This includes an analogue-to-digital converter (ADC) using the successive approximation design. This is used in this project to measure the voltage across a capacitor. CircuitPython configures this ADC in 12bit mode making each bit equivalent to 0.806mV.

This page explores the consistency of the ADC and the distribution of noise to determine if an average value (arithmetic mean) over a certain number of samples is a valid approach to calculate an accurate voltage.

Voltage across Capacitor in the Metal Detector

The graph below shows 1000 successive samples from the same function used in the program.

The samples are shown as dots which grow in size and are coloured relative to their distance from a fitted (straight) line. This visualisation appears useful in confirming:

  • most values are near the line,
  • the distribution looks fairly even above and below the line(s),
  • a few values are significantly above or below the line but these also look reasonably evenly distributed either side for this number of samples.

A second weighted line is also shown - this is a refinement created by weighting the points based on their distance from the first line on a scale of 4 to 1. This reduces the large effect that outliers have using the least squares approach to line fitting. There's only a 0.2mV difference between this potentially more accurate line's arithmetic mean value and the samples suggesting a basic, quick-to-calculate mean value gives a voltage with good accuracy. If the sampling was reduced to, say 50 samples (over 2.4ms), then this looks more risky for an outlier having a pronounced, adverse effect on the calculated mean voltage.

The curve fitting is an unnecessary leftover from when this graphing analysis code was used previously on a capacitor discharging. In this case the capacitor is charging and discharging at a 400kHz rate. The samples here have been gathered over ~47ms which covers over 18 thousand charge cycles. This means the voltage will be largely constant with a miniscule amount of ripple.

In this case, it's possible these outliers are genuine but it seems unlikely that the voltage is really jumping around because the:

  1. difference is so great,
  2. there's not an obvious "trail" of dots joining the spikes and
  3. there's a capacitor involved.

The use of weighting for this analysis means they are not ignored, just downplayed based on the previous justification. Statistics by Jim has a useful guide on distinguishing outliers and deciding what to do with them. Discarding inconvenient results is not a good justification!

This is a zoomed-in look at the lines. The scale exaggerates the tiny gradient. The discrete ADC levels from 12bit sampling can be see with the clearly defined rows of samples.

The P-P plot and Q-Q plot are common plots for visually comparing the data to another distribution, in this case the normal distribution. A matching distribution will overlap the straight line.

The histogram here is more of a bar chart as it's carefully aligned with the quantized sample values. Only the central portion of values is shown on this bar chart. This could show any ADC peculiarities particularly with more graphs of samples. There's nothing that jumps out as concerning here.

The choice of bucket size (width) for a histogram can have a large effect on the visual representation of the data. If the data is quantised in some way then this effect can be more pronounced. Checking and presenting varying bucket sizes is one way to avoid creating misleading charts. The animated graph below shows different bucket sizes across the full range of sample values (voltages) with the data presented with the mean subtracted making the central voltage 0mV.

A steady voltage reference source like a battery is a better test to look at the ADC. The results for two 1000 sample runs against an old alkaline AAA battery are very similar to the graphs above.

These tests were all conducted with the CLUE board powered by USB power from a desktop computer. Some further testing would be useful, like:

  1. Powering the CLUE from battery power with USB power removed to examine any adverse effects on the ADC from noise on the power supply.
  2. Comparing multiple CLUE boards and other boards based on the nRF52840.
  3. Checking the distribution on the samples when measuring GND and 3.3V.
  4. Checking different ADC acquisition times - this requires use of C++/Arduino.
  5. Comparing software over-sampling with nRF52840 hardware over-sampling - this requires use of C++/Arduino.
  6. Looking at the sample data in the frequency domain to look for any periodic peculiarities. This will be imperfect as the code in CircuitPython is not taking samples at a precise rate and the jitter will muddy everything except the very low frequencies.

Going Further

Ideas for Areas to Explore

  • Vary the coil size and windings to see how this affects the sensitivity.
  • Improve the magnetometer value as it currently only makes use of the z dimension.
  • Add a recent peak feature to the voltage bar graph and magnetometer circle.
  • If you are using the CPB without a screen:
    • Add some audio cues as time passes when the left button is depressed to give an indication of the current menu option.
    • Conditionally disable the screen update code for a faster main loop or for better voltage stability from increased sampling. The TFT Gizmo screen is not designed to be detectable but the approach outlined in Adafruit Forums: Is it possible to detect presence of Gizmo? is likely to work.

Related Projects

Further Reading

This guide was first published on May 13, 2020. It was last updated on May 13, 2020.