Résultats pour
- 昨日までちゃんと動いていたのに・・
- ヘルプページ通りに書いているのに・・
MATLAB 関数がエラーを出すようになることありますよね（？）そんな時にみなさんがまず確認するもの、何かありますか？教えてください！
例えば
which -all plot
をコマンドウィンドウで実行して、もともと MATLAB で定義されている plot 関数（MATLAB のインストールフォルダにある plot 関数）がちゃんと頭に出てくるかどうか確認します。
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.
キーと値の組み合わせでデータを格納できるディクショナリ。R2022bでdictionaryコマンドが登場し、最近のバージョンではreaddictionaryとwritedictionaryでJSONファイルからの読み込み・書き込みにも対応しました。
私はMIDIデータからピアノの演奏動画を作るプログラムで、ディクショナリを使いました。音のノート番号をキーにして、patchで白と黒で鍵盤を塗りつぶしたmatlab.graphics.Graphicsデータ型を値にしたディクショナリで保存して、MIDIで鳴らされた音のノート番号からlookupでグラフのオブジェクトを取得し、FaceColorを変更してハイライトするというもの。
コード例
%% MIDIデータの.matファイルを読み取ってピアノを描画するサンプル
fig = figure('Position', [34 328 1626 524]);
ax = axes;
whiteKeyY = [0 0 150 150];
whiteKeyColor = [1 1 1];
blackKeyY = [50 50 150 150];
blackKeyColor = [0.1 0.1 0.1];
edgeColor = [0 0 0];
% ディクショナリの定義
d = configureDictionary("double", "matlab.graphics.Graphics");
% 白鍵を描画
for n = 1:9
pos = 23*7*(n-1);
d = insert(d, 21 + (n-1)*12, patch([pos+5 pos+28 pos+28 pos+5],whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 21 + (n-1)*12));
d = insert(d, 23 + (n-1)*12, patch([pos+28 pos+51 pos+51 pos+28], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 23 + (n-1)*12));
d = insert(d, 24 + (n-1)*12, patch([pos+51 pos+74 pos+74 pos+51], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 24 + (n-1)*12));
if n < 9
d = insert(d, 26 + (n-1)*12, patch([pos+74 pos+97 pos+97 pos+74], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 26 + (n-1)*12));
d = insert(d, 28 + (n-1)*12, patch([pos+97 pos+120 pos+120 pos+97], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 28 + (n-1)*12));
d = insert(d, 29 + (n-1)*12, patch([pos+120 pos+143 pos+143 pos+120], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 29 + (n-1)*12));
d = insert(d, 31 + (n-1)*12, patch([pos+143 pos+166 pos+166 pos+143], whiteKeyY, whiteKeyColor, 'EdgeColor', edgeColor, 'UserData', 31 + (n-1)*12));
end
end
% 黒鍵を描画。白鍵の上になるようにループを分けています
for n = 1:9
pos = 23*7*(n-1);
d = insert(d, 22 + (n-1)*12, patch([pos+23 pos+33 pos+33 pos+23], blackKeyY, blackKeyColor, 'EdgeColor', [0 0 0], 'UserData', 22 + (n-1)*12));
if n < 9
d = insert(d, 25 + (n-1)*12, patch([pos+69 pos+79 pos+79 pos+69], blackKeyY, blackKeyColor, 'EdgeColor', [0 0 0], 'UserData', 25 + (n-1)*12));
d = insert(d, 27 + (n-1)*12, patch([pos+92 pos+102 pos+102 pos+92], blackKeyY, blackKeyColor, 'EdgeColor', [0 0 0], 'UserData', 27 + (n-1)*12));
d = insert(d, 30 + (n-1)*12, patch([pos+138 pos+148 pos+148 pos+138], blackKeyY, blackKeyColor, 'EdgeColor', [0 0 0], 'UserData', 30 + (n-1)*12));
d = insert(d, 32 + (n-1)*12, patch([pos+161 pos+171 pos+171 pos+161], blackKeyY, blackKeyColor, 'EdgeColor', [0 0 0], 'UserData', 32 + (n-1)*12));
end
end
xticklabels({})
yticklabels({})
xlim([5 1362])
drawnow
%% MIDI音源の.matファイルを読み込み
matData = load('fur-elise.mat');
msg = matData.receivedMessages;
eventTimes = [msg.Timestamp] - msg(1).Timestamp;
n = 1;
numNotes = 0;
lastNote = 0;
highlightedCircles = cell(1, 127);
% 音が鳴った鍵盤だけハイライトする
tic
while toc < max(eventTimes)
if toc > eventTimes(n)
thisMsg = msg(n);
if thisMsg.Type == "NoteOn"
numNotes = numNotes + 1;
lastNote = thisMsg.Note;
thisPatch = lookup(d, thisMsg.Note);
thisPatch.FaceColor = '#CCFFCC';
drawnow
elseif thisMsg.Type == "NoteOff"
numNotes = 0;
thisPatch = lookup(d, thisMsg.Note);
[~, ~, wOrB] = calcNotePos(thisMsg.Note);
if wOrB == "w"
thisPatch.FaceColor = 'white';
else
thisPatch.FaceColor = 'black';
end
drawnow
end
n = n+1;
end
end
%% サブ関数
function [pianoPos, centerPos, wOrB] = calcNotePos(note)
tempVar = idivide(int64(note), int64(12)); % 12で割った商
pos = 23*7*(tempVar-1);
switch mod(note, 12)
case 0 % C
pianoPos = pos + 62.5;
centerPos = 30;
wOrB = "w";
case 2 % D
pianoPos = pos + 85.5;
centerPos = 30;
wOrB = "w";
case 4 % E
pianoPos = pos + 108.5;
centerPos = 30;
wOrB = "w";
case 5 % F
pianoPos = pos + 131.5;
centerPos = 30;
wOrB = "w";
case 7 % G
pianoPos = pos + 154.5;
centerPos = 30;
wOrB = "w";
case 9 % A
pianoPos = pos + 177.5;
centerPos = 30;
wOrB = "w";
case 11 % B
pianoPos = pos + 200.5;
centerPos = 30;
wOrB = "w";
case 1 % C#
pianoPos = pos + 69;
centerPos = 100;
wOrB = "b";
case 3 % D#
pianoPos = pos + 92;
centerPos = 100;
wOrB = "b";
case 6 % F#
pianoPos = pos + 138;
centerPos = 100;
wOrB = "b";
case 8 % G#
pianoPos = pos + 161;
centerPos = 100;
wOrB = "b";
case 10 % A#
pianoPos = pos + 184;
centerPos = 100;
wOrB = "b";
end
end
皆さんはディクショナリを使ってますか？ もし使っていたら、どういう活用をしているか、聞かせてください！
どの方法を使う事が多いですか？他によく使う方法があれば教えてくださいー。
方法①
Livescript 上で for ループ内で描画を編集させて描いた動画は「アニメーションのエクスポート」から動画ファイルに出力するのが一番簡単ですね。再生速度やら細かい設定ができない点は要注意。
方法②
exportgraphics 関数で "Append" オプション指定で実現できるようになった（R2022a から）のでこれも便利ですね。
N = 100;
x = linspace(0,4*pi,N);
y = sin(x);
filename = 'animation_sample.gif'; % Specify the output file name
if exist(filename,'file')
delete(filename)
end
h = animatedline;
axis([0,4*pi,-1,1]) % x軸の表示範囲を固定
for k = 1:length(x)
addpoints(h,x(k),y(k)); % ループでデータを追加
exportgraphics(gca,filename,"Append",true)
end
方法③
R2021b 以前のバージョンだとこんな感じ。
各ループで画面キャプチャして、imwrite で動画ファイルにフレーム追加していくイメージです。"DelayTime" を使って細かい指定ができるので、必要に応じて今でも利用します。
for k = 1:length(x)
addpoints(h,x(k),y(k)); % ループでデータを追加
drawnow % グラフアップデート
frame = getframe(gcf); % Figure 画面をムービーフレーム（構造体）としてキャプチャ
tmp = frame2im(frame); % 画像に変更
[A,map] = rgb2ind(tmp,256); % RGB -> インデックス画像に
if k == 1 % 新規 gif ファイル作成
imwrite(A,map,filename,'gif','LoopCount',Inf,'DelayTime',0.2);
else % 以降、画像をアペンド
imwrite(A,map,filename,'gif','WriteMode','append','DelayTime',0.2);
end
end
これからは生成AIでコードを１から書くという事が減ってくるのかと思いますが，皆さんがMATLABのコードを書く時に意識しているご自身のルールのようなものがあれば教えてください．
MATLAB言語は柔軟に書けますが，自然と個人個人のルールというものが出来上がってきているのでは，と思います．
私はParameter, Valueペアの引数がある関数はそれぞれのペアを新しい行に書く，というのをよくやります．
h = plot(x, y, "ro-", ...
"LineWidth", 2, ...
"MarkerSize", 10, ...
"MarkerFaceColor", "g");
Parameter=Valueでも同じです．
h = plot(x, y, "ro-", ...
LineWidth = 2, ...
MarkerSize = 10, ...
MarkerFaceColor = "g");
また，一時期は "=" を揃えることもやってました（今はやってませんが）．
h = plot(x, y, "ro-", ...
LineWidth = 2, ...
MarkerSize = 10, ...
MarkerFaceColor = "g");
皆さんにはどのようなルールがありますか？
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()
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?
昨日 5/29 にお台場で MATLAB EXPO が開催されました。ご参加くださった方々ありがとうございました！
私は AI 関連のデモ展示で解説員としても立っておりましたが、立ち寄ってくださる方が絶えず、ずっと喋り続けてました。また、講演後に「さっきのすごくね？」という会話が漏れ聞こえてきたのがハイライト。
参加されたみなさま、印象に残ったこと・気になった講演・ポスター・デモ・新機能等あったら教えてください！（次回に向けて運営面での感想も）
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?
以前のEXPOでも参加・聴講したことがある
67%
知り合いから聞いた
0%
MathWorksからのプロモーション，EXPOサイトで知った
0%
今年のEXPO会場でたまたま見かけた
0%
ライトニングトークって何？
33%
3 votes
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 ?
Imagine you are developing a new toolbox for MATLAB. You have a folder full of a few .m files defining a bunch of functions and you are thinking 'This would be useful for others, I'm going to make it available to the world'
What process would you go through? What's the first thing you'd do?
I have my own opinions but don't want to pollute the start of the conversation :)
It is time to support the cameraIntrinsics function to accept a 3-by-3 intrinsic matrix K as an input parameter for constructing the object. Currently, the built-in cameraIntrinsics function can only be constructed by explicitly specifying focalLength, principalPoint, and imageSize. This approach has drawbacks, as it is not very intuitive. In most application scenarios, using the intrinsic matrix
K=[fx,0,cx;
0,fy,cy;
0,0,1]
is much more straightforward and effective!
intrinsics = cameraIntrinsics(K)
MATLAB FEX(MATLAB File Exchange) should support Markdown syntax for writing. In recent years, many open-source community documentation platforms, such as GitHub, have generally supported Markdown. MATLAB is also gradually improving its support for Markdown syntax. However, when directly uploading files to the MATLAB FEX community and preparing to write an overview, the outdated document format buttons are still present. Even when directly uploading a Markdown document, it cannot be rendered. We hope the community can support Markdown syntax!
BTW，I know that open-source Markdown writing on GitHub and linking to MATLAB FEX is feasible, but this is a workaround. It would be even better if direct native support were available.
