Good afternoon @ Crsitiano, I don't know if you've managed to solve your problem, here I did this way: $graf = new Lavacharts; $valor = \Lava::DataTable(); $valores = Produtos::select("nome as 0", "preco as 1")->get()->toArray(); $valor->addStringColumn("Preço") ->addNumberColumn("Nome") ->addRows(["NomeDaLinha", $valores]); \Lava::BarChart( 'Preço', $valor, [ 'title' =&gt; 'Seu título aqui: '. $valores, 'height' =&gt; 400 ] ); return view('home'); In the view it was like this:<div id="poll_div"></div> <?= Lava::render('BarChart', 'valor', 'poll_div') ?> And it worked out, of course I adapted a code of mine for your... Try who knows doesn't work...Abs...

To get the real name of the variable you need to use deparse(substitute(y)) in the chart title:Validação <- function(y){ plot(y, main= paste('Gráfico', deparse(substitute(y)))) } This is worth so much for the package charts base, as for the ggplot2 and lattice...

One way to do this is to create a vector with the function seq. As the name suggests, the function seq creates a sequence of numbers. Just inform the initial value, the final value and the increment. In the example below, I create a sequence that starts in 30 and goes up to 32, increasing from 0.1 to 0.1:seq(from=30, to=32, by=0.1) [1] 30.0 30.1 30.2 30.3 30.4 30.5 30.6 30.7 30.8 30.9 31.0 31.1 31.2 31.3 31.4 [16] 31.5 31.6 31.7 31.8 31.9 32.0 Now just put this command inside the function axis of your code:t_mean = c(30.24, 30.73, 30.94, 31.97, 31.28, 31.84, 31.56, 32.00) time = c(0,2,4,6,8,10,12,14) plot(t_mean~time, type ="l", ylim=c(30.0,32), yaxt ="n") axis(2, at=seq(from=30, to=32, by=0.1)) Attention: depending on the size of your computer screen or its resolution, it may not appear all the desired numbers when running the code I passed. See what happens when I run this same image on my computer, which has 13 inch screen and without zooming: Note that the numbers are no longer ranging from 0.2 to 0.2, but from 0.3 to 0.3. If I wanted the variation to be identical to the originally defined, from 0.1 to 0.1, I will have to necessarily reduce the source of the graph through the function par with the argument cex Suitable:par(cex=.5) plot(t_mean~time, type ="l", ylim=c(30.0,32), yaxt ="n") axis(2, at=seq(from=30, to=32, by=0.1)) Note that all decimal values between 30 and 32 appeared, but the visualization was not good. It is the duty of those who are producing the graphic to decide which is the best way to present it. None of the three I presented here is wrong, but in my opinion, the first (ranging from 0.2 to 0.2) is the best.

Just create a control variable for the scrollbar camera:int camera = 0; In this passage it would be like this:for (int i = camera; i < (camera + (pictureBox.Width / 0.2)); i++) and at the scrollbar event:hscrollBar_scroll(EventArgs e, object sender) { camera = hScrollBar.Value * 6000 / 100; DrawANALISE();//esqueci de por para redesenhar o gráfico. } If I couldn't help you with that, I can make a full control if you prefer.

Code profile is the way I suggest. Use https://www.microsoft.com/en-us/download/details.aspx?id=16273 that will allow to collect the execution trace and with this allow to see where exactly the bottlenecks occur.My second suggestion. Log in by instrumenting the code with the execution times of each excerpt involved ( https://stackoverflow.com/a/10107640/47733 ). So you will see where times are being spent.

An update rate of 3ms is higher than the refresh rate of the screen both at 60fps (16.6ms) or 120fps (8ms). Even if you force Invalidate every 3 ms, it will not update at the same time. Try optimizing the datareceived to work asyncronous and see the possibility of either increasing the update time or leaving the Invalidate async call.

I solved it with:counts.plot(kind='pie', labels = None, figsize=(11,8), legend=True)

I made a check, see if it helps you. Define the properties of MinValue and MaxValue and DataCount - Quantity of data that will.. Just create a timer and call the AddValue method every time.using System.Collections.Generic; using System.Drawing; using System.Drawing.Drawing2D; using System.Windows.Forms; namespace WindowsFormsApp2 { public class GraphControl : Control { private int _minValue = -100; private int _maxValue = 100; private int _dataCount = 25; private List<int> _values = new List<int>(); public int MinValue { get =&gt; _minValue; set { _minValue = value; Invalidate(); } } public int MaxValue { get =&gt; _maxValue; set { _maxValue = value; Invalidate(); } } public int DataCount { get =&gt; _dataCount; set { _dataCount = value; Invalidate(); } } public GraphControl() { Size = new System.Drawing.Size(500, 300); SetStyle(ControlStyles.OptimizedDoubleBuffer | ControlStyles.ResizeRedraw, true); } public void AddValue(int value) { _values.Add(value); Invalidate(); } protected override void OnPaint(PaintEventArgs e) { e.Graphics.SmoothingMode = SmoothingMode.AntiAlias; e.Graphics.FillRectangle(Brushes.White, ClientRectangle); e.Graphics.DrawRectangle(Pens.Gray, 0, 0, Width - 1, Height - 1); e.Graphics.DrawLine(Pens.LightGray, 0F, (float)Height * 0.5F, (float)Width, (float)Height * 0.5F); var wid = (float)Width / (float)_dataCount; for (var i = 0; i &lt; _dataCount; i++) e.Graphics.DrawLine(Pens.LightGray, wid * i, 0F, wid * i, Height); var lastPoint = new PointF(0F, (float)Height * 0.5F); var idInit = _values.Count - _dataCount; if (idInit &lt; 0) idInit = 0; for (int i = idInit, a = 0; i &lt; _values.Count; i++, a++) { var value = (float)(_values[i] - MinValue); var total = (float)(MaxValue - MinValue); var porcent = value / total; var hg = porcent * Height; var newPoint = new PointF((a + 1) * wid, Height - hg); using (var p = new Pen(Color.Maroon, 2)) e.Graphics.DrawLine(p, lastPoint, newPoint); lastPoint = newPoint; } base.OnPaint(e); } } } Add control to your project, compile and then add to Windows Forms by the toolbox.Example with random values: private void timer1_Tick(object sender, EventArgs e) { var rd = new Random(); var num = (rd.Next() % 200) - 100; graphControl1.AddValue(num); }

The problem is that the way you are calculating, x2 turns a two-dimensional matrix, the outermost dimension only has 1 element.Thus, x2[1:] and x2[:-1] nothing returns, because they are empty slices.A way to solve is by extracting the internal vector, that is, before plotting, surround:x2 = x2[0] The result:

You can do a function that stays in loop, always taking the value ( https://www.mathworks.com/matlabcentral/answers/87466-real-time-plot-from-streaming-data ).You can also create a class and add event and listener ( https://www.mathworks.com/help/matlab/matlab_oop/learning-to-use-events-and-listeners.html ). But maybe it's more complex than the first.For integrations with other languages and that you can use on the Web, take a look at MATLAB Compiler and MATLAB Compiler SDK.You can still do the opposite, board the HTML in MATLAB and treat by AppDesigner. See if https://www.mathworks.com/help/matlab/ref/uihtml.html Help.

SolutionConvert to CIELAB using OpenCV.First illustrates the 2D chart, with each color channel. Then the 3D chart for each Channel.Codeimport numpy as np import cv2 from matplotlib import pyplot as plt from mpl_toolkits.mplot3d import Axes3D def mostrar_imagem_Lab(nome, img): plt.figure(nome) plt.subplot(2, 2, 1) plt.imshow(img) plt.subplot(2, 2, 2) plt.imshow(img[:, :, 0], cmap='Greys') plt.subplot(2, 2, 3) plt.imshow(img[:, :, 1], cmap='PuBuGn_r') plt.subplot(2, 2, 4) plt.imshow(img[:, :, 2], cmap='YlGnBu_r') img = cv2.imread("C:\Users\usuario\Desktop\teste\4-cube_horribly_scrambled.png") lab_image = cv2.cvtColor(img, cv2.COLOR_BGR2LAB) h, w, c = img.shape y = range(h) x = range(w) X, Y = np.meshgrid(x, y) mostrar_imagem_Lab('Gráfico Lab', lab_image) plt.figure('Canal L') ax = plt.axes(projection='3d') ax.plot_surface(X, Y, lab_image[:, :, 0], cmap='Greys') plt.figure('Canal a') ax = plt.axes(projection='3d') ax.plot_surface(X, Y, lab_image[:, :, 1], cmap='PuBuGn_r') plt.figure('Canal b') ax = plt.axes(projection='3d') ax.plot_surface(X, Y, lab_image[:, :, 2], cmap='YlGnBu_r') plt.show() ResultsWith the following test image: The following 2D result was obtained: 3D result for channel L: 3D result for channel a: 3D result for channel b: ObservationIf the colormap is different (RGB, BGR, HSV, etc), check the following links: https://matplotlib.org/examples/color/colormaps_reference.html https://matplotlib.org/users/colormaps.html http://mpastell.com/2013/05/02/matplotlib_colormaps/

You can use HoloGraphLibrary. I never used it but it seems simple https://github.com/Androguide/HoloGraphLibrary In github has this example:PieGraph pg = (PieGraph)findViewById(R.id.graph); PieSlice slice = new PieSlice(); slice.setColor(Color.parseColor("#99CC00")); slice.setValue(2); pg.addSlice(slice); slice = new PieSlice(); slice.setColor(Color.parseColor("#FFBB33")); slice.setValue(3); pg.addSlice(slice); slice = new PieSlice(); slice.setColor(Color.parseColor("#AA66CC")); slice.setValue(8); pg.addSlice(slice);

What you want is an interpolation of points.This consists of finding a function f(x) that given n points p1,p2,...,pn, f(x) pass through all points.How is that done?Let's think of the simplest case, 2 points (n=2), in this case we want to find a straight (remember, there is always a straight that goes through 2 non-coincidents), a straight is a function of the form f(x) = ax + bNote that f(x) is a grade 1 polynomial, in the case of polynomial interpolation, we want f(x) to be a minor polynomial possible.There are several interpolation algorithms, you can find their description here, but most languages already have a lib with this implemented https://pt.wikipedia.org/wiki/Polin%C3%B3mio_de_Newton https://pt.wikipedia.org/wiki/Polin%C3%B4mio_de_Lagrange

This problem has no solution with the data set provided. The function help summarySE says the following:Gives count, mean, standard deviation, standard error of the mean, and confidence interval (default 95%).The three measures I highlighted above are measures of dispersion or variability. All these three are measures that depend on the sample variance. Sample variance formula is given by Note that the sum is divided by No. Therefore, in order to measure variability in a dataset, we need at least two observations. After all, if #, we will have a division for zero.In your original question by grouping the data by ID (groupvars=c("ID","INT"), you are saying you want to calculate the variability by ID of the subjects. But see the following code, in which I count the number of subjects per ID:library(dplyr) pmed %>% select(ID) %>% count() ID freq 1 2 2 2 3 2 4 2 5 2 6 1 7 1 8 2 9 1 10 2 11 2 12 2 13 2 15 2 16 1 17 1 18 1 19 1 20 1 21 1 22 1 23 1 24 1 25 1 26 1 27 1 29 1 30 1 Many IDs have only one subject. Therefore, it is impossible to calculate a measure of variability in these cases, because data are missing. So you got a warning about the NaN (single) NO a Naber) which are created.

I solved the problem by making an Ajax page for the graphics page: <?php error_reporting(E_ALL); ini_set('display_errors', 1); include("conn.php"); if(isset($_POST['id'])) { $id = $_POST['id']; $PREV = mysqli_query($lnk, "Select JAN_PREV, FEV_PREV, MAR_PREV, ABR_PREV, MAI_PREV, JUN_PREV, JUL_PREV, AGO_PREV, SET_PREV, OUT_PREV, NOV_PREV, DEZ_PREV from qualite where ID = ". $id . ""); $REAL = mysqli_query($lnk, "Select JAN_REAL, FEV_REAL, MAR_REAL, ABR_REAL, MAI_REAL, JUN_REAL, JUL_REAL, AGO_REAL, SET_REAL, OUT_REAL, NOV_REAL, DEZ_REAL from qualite where ID = ". $id .""); $resultPREV = mysqli_fetch_assoc($PREV); $resultREAL = mysqli_fetch_assoc($REAL); $ListaP = $resultPREV; $ListaR = $resultREAL; $ListaPTotal = array(); $ListaRTotal = array(); foreach ($ListaP as $i =&gt; $value) { array_push($ListaPTotal, $value); } foreach ($ListaR as $i =&gt; $value) { array_push($ListaRTotal, $value); } } $html2 = " &lt;div id='container-tt' style='min-width: 310px; height: 400px; margin: 0 auto'&gt;&lt;/div&gt; &lt;script type='text/javascript'&gt; Highcharts.chart('container-tt', { chart: { type: 'column' }, title: { text: 'OBEYA DOPM 2018' }, xAxis: { categories: [ 'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec' ], crosshair: true }, yAxis: { min: 0, title: { } }, tooltip: { shared: true, useHTML: true }, plotOptions: { column: { pointPadding: 0.2, borderWidth: 0 } }, series: [{ name: 'Previsto', data: [" . join(", ", $ListaPTotal) . "] }, { name: 'Realizado', data: [" . join(", ", $ListaRTotal) . "] }] }); </script> </div>"; echo $html2; //erro no php ?>

Hard to respond with little information, but follow an attempt#os dados set.seed(123) tss=abs(matrix(rnorm(50*3,1000,1000),ncol=3)) meta=colMeans(tss)*c(0.8,1.2,1.4) # suposto mcol=apply(tss-meta,2,function(vx)ifelse(vx>=0,"Sup.Meta","Inf.Meta")) library(ggplot2) library(reshape) tssdf=data.frame(tss) tssdf$data=1:nrow(tssdf) #melt(mcol) tssdfm=melt(tssdf, id = "data") tssdfm$supmeta=factor(melt(mcol)$value) ggplot(data=tssdfm, aes(x=data, y=value, colour=variable)) +theme_bw() + geom_line()+ geom_point(aes(col=supmeta), size=3)

Hello, have you heard of C3? It is a graphics js library that is very beautiful and easy to use. http://c3js.org/ Maybe I can help you! Hugs

You can do this to show a chart with the categories as it is in the database.Database Registration: Code in php to be fed the chart:$mysqli = new mysqli('servidor', 'usuario', 'senha', 'banco'); // Aqui você pode fazer um select alimentando normal uma váriavel com as categorias a ser exibida $categories = array(); $sql = $mysqli->query("SELECT nome from categorias"); while ($result = mysqli_fetch_array($sql)) { $categories[] = $result['nome']; } // Select para pegar os dados da tabela $sql = $mysqli->query("SELECT coluna, valor from grafico"); $valores = array(); // while dos registros alimentando um array while ($result = mysqli_fetch_array($sql)) { $valores[$result['coluna']][] = floatval($result['valor']); } // aqui irá ser colocado a váriavel que foi alimentada por array no while acima // para deixar no padrão que o highcharts reconhece foreach($valores as $key => $value) { $series[] = array('name' => utf8_encode($key), 'data' => array_values($value)); } Code in js of highcharts:Highcharts.chart('container', { chart: { type: 'bar' }, title: { text: 'Chart title' }, xAxis: { categories: <?=json_encode($categories); ?> // Transforma array em json para mostrar as categorias }, yAxis: { min: 0, title: { text: 'Total fruit consumption' } }, legend: { reversed: true }, plotOptions: { series: { stacking: 'normal' } }, series: <?=json_encode($series); ?> // Transforma array em json para mostrar as informações do gráfico }); Result:

You can use the library matplotlib to plot the chart, see only:import matplotlib.pyplot as plt def obterProgresso( linha ): p = [ 0 ] x = 0 for i in linha: if i == 0: x-=1 else: x+=1 p.append(x) return p; Linha1 = [1,1,1,0,1,0,1] Linha2 = [0,0,0,0,1,1,1] Prog1 = obterProgresso( Linha1 ) Prog2 = obterProgresso( Linha2 ) print "Linha1 = ", Prog1 print "Linha2 = ", Prog2 plt.plot( Prog1, 'bo' ); plt.plot( Prog1, 'k--', color='blue' ); plt.plot( Prog2, 'ro' ); plt.plot( Prog2, 'k--', color='red' ); plt.grid(True) plt.xlabel("Tempo") plt.ylabel("Progresso") plt.show() Output: Progressions:Linha1 = [0, 1, 2, 3, 2, 3, 2, 3] Linha2 = [0, -1, -2, -3, -4, -3, -2, -1]

I made some changes to your code.I changed the name of the variables df2 For Q.1, Q.2, Q.3, Q.4 and Q.5.In long2 I called the variable gabarito because it represents the amount of students who have settled their questions, right?After I join long and long2 by ITENS and what you called turma (so I modified the variable names in df2). Follow code and result:ITENS <-c("A","B","C","D","E") Q.1 <-c(10,20,10,40,10); Q.2 <-c(5,25,0,50,10); Q.3 <-c(15,20,5,40,10) Q.4 <-c(15,30,5,30,5); Q.5 <-c(20,25,5,20,15); Q.6 <-c(10,20,10,40,10) df <- data.frame(ITENS,Q.1,Q.2,Q.3,Q.4,Q.5,Q.6) Q.1 <-c(0,20,0,0,0); Q.2 <-c(5,0,0,0,0); Q.3 <-c(0,0,5,0,0) Q.4 <-c(0,0,0,30,0); Q.5 <-c(20,0,0,0,0); Q.6 <-c(0,0,10,0,0) df2 <- data.frame(ITENS,Q.1,Q.2,Q.3,Q.4,Q.5,Q.6) library(tidyr) long <- df %>% gather(turma, quantidade, Q.1:Q.6) long2 <- df2 %>% gather(turma, gabarito, Q.1:Q.6) library(dplyr) l <- left_join(long, long2, by = c("ITENS", "turma")) ggplot(l, aes(x = ITENS)) + geom_bar(aes(y = quantidade, fill = "red"), stat = "identity", position = "identity") + guides(fill = F) + geom_bar(aes(y = gabarito, fill = "blue"), stat = "identity", position = "identity") + facet_wrap(~turma)