Results for
I'm facing an issue where my Thinkspeak graph is not displaying, even though I'm using exactly the same code as my friend. The code works perfectly in their Thinkspeak account, but not on mine. I've checked the API keys, channel settings, and data formats, but everything seems similar. Has anyone else faced this problem, or do you have tips on what to check next? Suggestions are welcome!
Hi!
I'm having trouble sending data to a channel using MQTT. I'm using a program that was working perfectly until just a few days ago, but after making some minor changes yesterday, it stopped working. I’ve also tested it manually using the MQTTX client. If I send data using CURL and GET, it works fine.
It’s a bit strange...
Thankfully,
Ernesto.
Is it possible to create a Simulink model that is independent of specific microcontrollers?
For example, in the model, the STM32 block is used for CAN transmission. But if I want to deploy the same model to an Arduino, I have to replace the STM32 block with an Arduino-compatible one.
So, is it possible to create a custom block or abstraction that works across multiple microcontrollers like STM32, PIC32, and Arduino without changing the hardware-specific block each time?
Hello,
I've successfully tested the Processor-in-the-Loop (PIL) workflow in Simulink using a TI F28069M LaunchPad, following the standard examples provided by MathWorks. The PIL block, code generation, and communication all worked without issues.
Now, I’d like to run a similar PIL setup using the Infineon TLE9879 EVALKIT (based on an ARM Cortex-M0), which is not officially supported by Simulink as a target.
I’m wondering if it’s possible to configure PIL manually or via custom workflows. For example:
- Can I create a custom PIL target using Embedded Coder?
- Would I need to port rtiostream manually for communication over UART?
- Could I somehow integrate with Keil µVision (which I use for TLE9879) to build and run the generated code?
- Is there a workaround to simulate PIL behavior using a non-supported board?
My setup:
- Simulink R2024b
- Infineon TLE9879 EVALKIT
- Keil µVision 5 + Infineon Config Wizard
- UART and JTAG interfaces available
The main purpose is to validate control algorithms and measure execution time, not to implement a full HIL system.
Has anyone attempted PIL with a custom or unsupported microcontroller before? Any tips or resources would be greatly appreciated. Thanks in advance!
Hey MATLAB enthusiasts!
I just stumbled upon this hilariously effective GitHub repo for image deformation using Moving Least Squares (MLS)—and it’s pure gold for anyone who loves playing with pixels! 🎨✨
- Real-Time Magic ✨
- Precomputes weights and deformation data upfront, making it blazing fast for interactive edits. Drag control points and watch the image warp like rubber! (2)
- Supports affine, similarity, and rigid deformations—because why settle for one flavor of chaos?
- Single-File Simplicity 🧩
- All packed into one clean MATLAB class (mlsImageWarp.m).
- Endless Fun Use Cases 🤹
- Turn your pet’s photo into a Picasso painting.
- "Fix" your friend’s smile... aggressively.
- Animate static images with silly deformations (1).
Try the Demo!
You are not a jedi yet !
20%
We not grant u the rank of master !
0%
Ready are u? What knows u of ready?
0%
May the Force be with you !
80%
5 votes
Sto tentando inutilmente di salvare il valore dell'enegia che consumo ogni giorno nel field5 di questo canale: https://thingspeak.mathworks.com/channels/2851490 , ma inutilemte in quanto vengono visualizzati sempre e solo 2 dati anche se ho impostato days=30. Ho provato ad aumentare a 365 ma senza variazioni. Come mai?
Untapped Potential for Output-arguments Block
MATLAB has a very powerful feature in its arguments blocks. For example, the following code for a function (or method):
- clearly outlines all the possible inputs
- provides default values for each input
- will produce auto-complete suggestions while typing in the Editor (and Command Window in newer versions)
- checks each input against validation functions to enforce size, shape (e.g., column vs. row vector), type, and other options (e.g., being a member of a set)
function [out] = sample_fcn(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
% function logic ...
end
If you do not already use the arguments block for function (or method) inputs, I strongly suggest that you try it out.
The point of this post, though, is to suggest improvements for the output-arguments block, as it is not nearly as powerful as its input-arguments counterpart. I have included two function examples: the first can work in MATLAB while the second does not, as it includes suggestions for improvements. Commentary specific to each function is provided completely before the code. While this does necessitate navigating back and forth between functions and text, this provides for an easy comparison between the two functions which is my main goal.
Current Implementation
The input-arguments block for sample_fcn begins the function and has already been discussed. A simple output-arguments block is also included. I like to use a single output so that additional fields may be added at a later point. Using this approach simplifies future development, as the function signature, wherever it may be used, does not need to be changed. I can simply add another output field within the function and refer to that additional field wherever the function output is used.
Before beginning any logic, sample_fcn first assigns default values to four fields of out. This is a simple and concise way to ensure that the function will not error when returning early.
The function then performs two checks. The first is for an empty input (x) vector. If that is the case, nothing needs to be done, as the function simply returns early with the default output values that happen to apply to the inability to fit any data.
The second check is for edge cases for which input combinations do not work. In this case, the status is updated, but default values for all other output fields (which are already assigned) still apply, so no additional code is needed.
Then, the function performs the fit based on the specified model_type. Note that an otherwise case is not needed here, since the argument validation for model_type would not allow any other value.
At this point, the total_error is calculated and a check is then made to determine if it is valid. If not, the function again returns early with another specific status value.
Finally, the R^2 value is calculated and a fourth check is performed. If this one fails, another status value is assigned with an early return.
If the function has passed all the checks, then a set of assertions ensure that each of the output fields are valid. In this case, there are eight specific checks, two for each field.
If all of the assertions also pass, then the final (successful) status is assigned and the function returns normally.
function [out] = sample_fcn(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
arguments(Output)
out struct
end
%%
out.fit = [];
out.total_error = [];
out.R_squared = NaN;
out.status = "Fit not possible for supplied inputs.";
%%
if isempty(in.x)
return
end
%%
if ((in.model_type == "2-factor") && (in.number_of_terms == 5)) || ... % other possible logic
out.status = "Specified combination of model_type and number_of_terms is not supported.";
return
end
%%
switch in.model_type
case "2-factor"
out.fit = % code for 2-factor fit
case "3-factor"
out.fit = % code for 3-factor fit
case "4-factor"
out.fit = % code for 4-factor fit
end
%%
out.total_error = % calculation of error
if ~isfinite(out.total_error)
out.status = "The total_error could not be calculated.";
return
end
%%
out.R_squared = % calculation of R^2
if out.R_squared > 1
out.status = "The R^2 value is out of bounds.";
return
end
%%
assert(iscolumn(out.fit), "The fit vector is not a column vector.");
assert(size(out.fit) == size(in.x), "The fit vector is not the same size as the input x vector.");
assert(isscalar(out.total_error), "The total_error is not a scalar.");
assert(isfinite(out.total_error), "The total_error is not finite.");
assert(isscalar(out.R_squared), "The R^2 value is not a scalar.");
assert(isfinite(out.R_squared), "The R^2 value is not finite.");
assert(isscalar(out.status), "The status is not a scalar.");
assert(isstring(out.status), "The status is not a string.");
%%
out.status = "The fit was successful.";
end
Potential Implementation
The second function, sample_fcn_output_arguments, provides essentially the same functionality in about half the lines of code. It is also much clearer with respect to the output. As a reminder, this function structure does not currently work in MATLAB, but hopefully it will in the not-too-distant future.
This function uses the same input-arguments block, which is then followed by a comparable output-arguments block. The first unsupported feature here is the use of name-value pairs for outputs. I would much prefer to make these assignments here rather than immediately after the block as in the sample_fcn above, which necessitates four more lines of code.
The mustBeSameSize validation function that I use for fit does not exist, but I really think it should; I would use it a lot. In this case, it provides a very succinct way of ensuring that the function logic did not alter the size of the fit vector from what is expected.
The mustBeFinite validation function for out.total_error does not work here simply because of the limitation on name-value pairs; it does work for regular outputs.
Finally, the assignment of default values to output arguments is not supported.
The next three sections of sample_fcn_output_arguments match those of sample_fcn: check if x is empty, check input combinations, and perform fit logic. Following that, though, the functions diverge heavily, as you might expect. The two checks for total_error and R^2 are not necessary, as those are covered by the output-arguments block. While there is a slight difference, in that the specific status values I assigned in sample_fcn are not possible, I would much prefer to localize all these checks in the arguments block, as is already done for input arguments.
Furthermore, the entire section of eight assertions in sample_fcn is removed, as, again, that would be covered by the output-arguments block.
This function ends with the same status assignment. Again, this is not exactly the same as in sample_fcn, since any failed assertion would prevent that assignment. However, that would also halt execution, so it is a moot point.
function [out] = sample_fcn_output_arguments(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
arguments(Output)
out.fit (:, 1) {mustBeSameSize(out.fit, in.x)} = []
out.total_error (1, 1) {mustBeFinite(out.total_error)} = []
out.R_squared (1, 1) {mustBeLessThanOrEqual(out.R_squared, 1)} = NaN
out.status (1, 1) string = "Fit not possible for supplied inputs."
end
%%
if isempty(in.x)
return
end
%%
if ((in.model_type == "2-factor") && (in.number_of_terms == 5)) || ... % other possible logic
out.status = "Specified combination of model_type and number_of_terms is not supported.";
return
end
%%
switch in.model_type
case "2-factor"
out.fit = % code for 2-factor fit
case "3-factor"
out.fit = % code for 3-factor fit
case "4-factor"
out.fit = % code for 4-factor fit
end
%%
out.status = "The fit was successful.";
end
Final Thoughts
There is a significant amount of unrealized potential for the output-arguments block. Hopefully what I have provided is helpful for continued developments in this area.
What are your thoughts? How would you improve arguments blocks for outputs (or inputs)? If you do not already use them, I hope that you start to now.
I saw this on Reddit and thought of the past mini-hack contests. We have a few folks here who can do something similar with MATLAB.
I had an error in the web version Matlab, so I exited and came back in, and this boy was plotted.
Bom dia se alguém puder me ajudar, meu código abaixo, não estou conseguintdo conectar o meu Esp8266 ao ThingSpeak, o erro tá na conexão. Estou usando o MicroPython e NodeMCU na plataforma Pytohn o sistema operacional Ubuntu 20
# DHT11 -> ESP8266/ESP32
# 1(Vcc) -> 3v3
# 2(Data) -> GPIO12
# 4(Gnd) -> Gnd
import time, network, machine
from dht import DHT11
from machine import Pin
from umqtt.simple import MQTTClient
print("Iniciando...")
dht = DHT11(Pin(12, Pin.IN, Pin.PULL_UP))
estacao = network.WLAN(network.STA_IF)
estacao.active(True)
estacao.connect('xxxxxxx', 'xxxxxxxxx')
while estacao.isconnected() == False:
machine.idle()
print('Conexao realizada.')
print(estacao.ifconfig())
SERVIDOR = "mqtt.thingspeak.com"
CHANNEL_ID = "XXXXXXXXXXXXXXXXX"
WRITE_API_KEY = "XXXXXXXXXXXXXXXXXXXXX"
topico = "channels/" + CHANNEL_ID + "/publish/" + WRITE_API_KEY
cliente = MQTTClient("umqtt_client", SERVIDOR)
try:
while True:
dht.measure()
temp = dht.temperature()
umid = dht.humidity()
print('Temperatura: %3.1f °C' %temp)
print('Umidade: %3.1f %%' %umid)
conteudo = "field1=" + str(temp) + "&field2=" + str(umid)
print ('Conectando a ThingSpeak...')
cliente.connect()
cliente.publish(topico, conteudo)
cliente.disconnect()
print ('Envio realizado.')
time.sleep(600.0)
except KeyboardInterrupt:
estacao.disconnect()
estacao.active(False)
print("Fim.")
*****************************************************************************************************
No shell aparece como resposta:
MPY: soft reboot
Iniciando...
Conexao realizada.
('192.168.0.23', '255.255.255.0', '192.168.0.1', '8.8.8.8')
Temperatura: 29.0 °C
Umidade: 63.0 %
Conectando a ThingSpeak...
Traceback (most recent call last):
File "<stdin>", line 38, in <module>
File "umqtt/simple.py", line 67, in connect
OSError: -2
linha 38 é cliente.connect()
It seems like the financial news is always saying the stock market is especially volatile now. But is it really? This code will show you the daily variation from the prior day. You can see that the average daily change from one day to the next is 0.69%. So any change in the stock market from the prior day less than about 0.7% or 1% is just normal "noise"/typical variation. You can modify the code to adjust the starting date for the analysis. Data file (Excel workbook) is attached (hopefully - I attached it twice but it's not showing up yet).
% Program to plot the Dow Jones Industrial Average from 1928 to May 2025, and compute the standard deviation.
% Data available for download at https://finance.yahoo.com/quote/%5EDJI/history?p=%5EDJI
% Just set the Time Period, then find and click the download link, but you ned a paid version of Yahoo.
%
% If you have a subscription for Microsoft Office 365, you can also get historical stock prices.
% Reference: https://support.microsoft.com/en-us/office/stockhistory-function-1ac8b5b3-5f62-4d94-8ab8-7504ec7239a8#:~:text=The%20STOCKHISTORY%20function%20retrieves%20historical,Microsoft%20365%20Business%20Premium%20subscription.
% For example put this in an Excel Cell
% =STOCKHISTORY("^DJI", "1/1/2000", "5/10/2025", 0, 1, 0, 1,2,3,4, 5)
% and it will fill out a table in Excel
%====================================================================================================================
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures if you have the Image Processing Toolbox.
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 14;
filename = 'Dow Jones Industrial Index.xlsx';
data = readtable(filename);
% Date,Close,Open,High,Low,Volume
dates = data.Date;
closing = data.Close;
volume = data.Volume;
% Define start date and stop date
startDate = datetime(2011,1,1)
stopDate = dates(end)
selectedDates = dates > startDate;
% Extract those dates:
dates = dates(selectedDates);
closing = closing(selectedDates);
volume = volume(selectedDates);
% Plot Volume
hFigVolume = figure('Name', 'Daily Volume');
plot(dates, volume, 'b-');
grid on;
xticks(startDate:calendarDuration(5,0,0):stopDate)
title('Dow Jones Industrial Average Volume', 'FontSize', fontSize);
hFig = figure('Name', 'Daily Standard Deviation');
subplot(3, 1, 1);
plot(dates, closing, 'b-');
xticks(startDate:calendarDuration(5,0,0):stopDate)
drawnow;
grid on;
caption = sprintf('Dow Jones Industrial Average from %s through %s', dates(1), dates(end));
title(caption, 'FontSize', fontSize);
% Get the average change from one trading day to the next.
diffs = 100 * abs(closing(2:end) - closing(1:end-1)) ./ closing(1:end-1);
subplot(3, 1, 2);
averageDailyChange = mean(diffs)
% Looks pretty noisy so let's smooth it for a nicer display.
numWeeks = 4;
diffs = sgolayfilt(diffs, 2, 5*numWeeks+1);
plot(dates(2:end), diffs, 'b-');
grid on;
xticks(startDate:calendarDuration(5,0,0):stopDate)
hold on;
line(xlim, [averageDailyChange, averageDailyChange], 'Color', 'r', 'LineWidth', 2);
ylabel('Percentage', 'FontSize', fontSize);
caption = sprintf('Day-to-Day Change Percentage. Average Daily Change (from prior day) = %.2f%%', averageDailyChange);
title(caption, 'FontSize', fontSize);
drawnow;
% Get the stddev over a 5 trading day window.
sd = stdfilt(closing, ones(5, 1));
% Get it relative to the magnitude.
sd = sd ./ closing * 100;
averageVariation = mean(sd)
numWeeks = 2;
% Looks pretty noisy so let's smooth it for a nicer display.
sd = sgolayfilt(sd, 2, 5*numWeeks+1);
% Plot it.
subplot(3, 1, 3);
plot(dates, sd, 'b-');
grid on;
xticks(startDate:calendarDuration(5,0,0):stopDate)
hold on;
line(xlim, [averageVariation, averageVariation], 'Color', 'r', 'LineWidth', 2);
ylabel('Percentage', 'FontSize', fontSize);
caption = sprintf('Weekly Standard Deviation, Averaged Over %d Weeks (%d trading days). Mean SD = %.2f', ...
numWeeks, 5*numWeeks+1, averageVariation);
title(caption, 'FontSize', fontSize);
% Maximize figure window.
g = gcf;
g.WindowState = 'maximized';
w = logspace(-1,3,100);
[m,p] = bode(tf(1,[1 1]),w);
size(m)
and therefore plotting requires an explicit squeeze (or rehape, or colon)
% semilogx(w,squeeze(db(m)))
Similarly, I'm using page* functions more regularly and am now generating 3D results whereas my old code would generate 2D. For example
x = [1;1];
theta = reshape(0:.1:2*pi,1,1,[]);
Z = [cos(theta), sin(theta);-sin(theta),cos(theta)];
y = pagemtimes(Z,x);
Now, plotting requires squeezing the inputs
% plot(squeeze(theta),squeeze(y))
Would there be any drawbacks to having plot, et. al., automagically apply squeeze to its inputs?
The ability to plot multiple signals on a plot and then use the plot browser to interactively control which ones are displayed has been one of the most useful features of the plotting tools and many of my scripts embed the command to open it after results analysis and plotting. It's been removed in 2025A with the comment that the Property Inspector provides the alternative. It doesn't. Having to go back into the menu to select the plot edit features to get to the Property Inspector (which doesn't provide an efficient alternative to the plot browser) has made the workflow very inefficient. Please bring it back a.s.a.p. !!!!
I want to use Simulink for model-based development of the TC3XX series development board, but I am not sure about the development process and toolchain? Is there a free toolchain available for me to use? Do you have a detailed development tutorial?
I have a pressure vs. time plot resulting from the input of an elastic wave, which I obtained from an Abaqus simulation. So, I have access to all the data. Now, I want to convert this time-domain graph into a frequency-domain graph using FFT in MATLAB.
I came across a code through ChatGPT, but I’m not fully confident in relying on it. Could anyone kindly clarify whether the formulas used for FFT in MATLAB are universal for all types of signals? Or is there a more effective and reliable method I should consider for this purpose?
Hi guys!
Im doing a project where i need to simulate a ship connected to the grid. I have a grid->converter AC-DC-AC -> dynamic load. My converter has to keep the voltage consistent and what changes is the current. Can somebody help me?
I've long used the Tensor Toolbox from Sandia in order to use tensors in Matlab, but recently found myself wanting to apply it on symbolic arguments, which don't appear supported. Some google-fu'ing resulted in (non-free) Tensorlab and some file-exchange entries of mixed quality. And of course, there's the recent tensorprod, which a) doesn't support symbolics and b) arguments aren't strictly tensors (rather "representations of tensors in a matrix type").
This all got me to thinking that it would be mighty nice to have general / native / comprehensive support for a tensor class in official Matlab - even if it were in a separate toolbox.
Hello ThingSpeak Community,
I have an energy meter sending data of energy consumed in 4 rooms in hexadecimal values to Sigfox and I was trying to decode the payload and route it to ThingSpeak.
All the datas are sent at the same time.
But ThingSpeak only receives 1 of them and plots them.
However, the rest 3 are missing. Is this because I am trying the free version ?
Would the payed version be capable of receiving all the 4 messages ?
