Matlab plot color depending value

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Matlab plot color depending value

Answered: actinium on 22 Aug 2019 Hello! I want to change the color of a line in a plot so it depends on the y-value using a colormap. I have find much code that help when you work with surfaces, but I do not know how to do it for just a line. I have managed something (see the picture) but for this I have used surf and I would like not to do that since I can't make it work with the rest of my code. (I have other lines in the same plot that I do not want to change color.) I have also managed to add a colormap to a line, but not to let it depend on the y-value. Any suggestions? MATLAB Function Reference plot Linear 2-D plot Syntax plot(Y) plot(X1,Y1,...) plot(X1,Y1,LineSpec,...) plot(...,'PropertyName',PropertyValue,...) plot(axes_handle,...) h = plot(...) hlines = plot('v6',...) Description plot(Y) plots the columns of Y versus their index if Y is a real number. If Y is complex, plot(Y) is equivalent to plot(real(Y),imag(Y)). In all other uses of plot, the imaginary component is ignored. plot(X1,Y1,...) plots all lines defined by Xn versus Yn pairs. If only Xn or Yn is a matrix, the vector is plotted versus the rows or columns of the matrix, depending on whether the vector's row or column dimension matches the matrix. plot(X1,Y1,LineSpec,...) plots all lines defined by the Xn,Yn,LineSpec triples, where LineSpec is a line specification that determines line type, marker symbol, and color of the plotted lines. You can mix Xn,Yn,LineSpec triples with Xn,Yn pairs: plot(X1,Y1,X2,Y2,LineSpec,X3,Y3). Note See LineSpec for a list of line style, marker, and color specifiers. plot(...,'PropertyName',PropertyValue,...) sets properties to the specified property values for all lineseries graphics objects created by plot. (See the "Examples" section for examples.) plot(axes_handle,...) plots into the axes with handle axes_handle instead of the current axes (gca). h = plot(...) returns a column vector of handles to lineseries graphics objects, one handle per line. Backward Compatible Version hlines = plot('v6',...) returns the handles to line objects instead of lineseries objects. Remarks If you do not specify a color when plotting more than one line, plot automatically cycles through the colors in the order specified by the current axes ColorOrder property. After cycling through all the colors defined by ColorOrder, plot then cycles through the line styles defined in the axes LineStyleOrder property. The default LineStyleOrder property has a single entry (a solid line with no marker). Cycling Through Line Colors and Styles By default, MATLAB resets the ColorOrder and LineStyleOrder properties each time you call plot. If you want changes you make to these properties to persist, then you must define these changes as default values. For example, set(0,'DefaultAxesColorOrder',[0 0 0],... 'DefaultAxesLineStyleOrder','-|-.|--|:') sets the default ColorOrder to use only the color black and sets the LineStyleOrder to use solid, dash-dot, dash-dash, and dotted line styles. Prevent Resetting of Color and Styles with hold all The all option to the hold command prevents the ColorOrder and LineStyleOrder from being reset in subsequent plot commands. In the following sequence of commands, MATLAB continues to cycle through the colors defined by the axes ColorOrder property (see above). plot(rand(12,2)) hold all plot(randn(12,2)) Additional Information Examples Specifying the Color and Size of Markers You can also specify other line characteristics using graphics properties (see line for a description of these properties): LineWidth -- Specifies the width (in points) of the line. MarkerEdgeColor -- Specifies the color of the marker or the edge color for filled markers (circle, square, diamond, pentagram, hexagram, and the four triangles). MarkerFaceColor -- Specifies the color of the face of filled markers. MarkerSize -- Specifies the size of the marker in units of points. For example, these statements, x = -pi:pi/10:pi; y = tan(sin(x)) - sin(tan(x)); plot(x,y,'--rs','LineWidth',2,... 'MarkerEdgeColor','k',... 'MarkerFaceColor','g',... 'MarkerSize',10) produce this graph. Specifying Tick-Mark Location and Labeling You can adjust the axis tick-mark locations and the labels appearing at each tick. For example, this plot of the sine function relabels the x-axis with more meaningful values: x = -pi:.1:pi; y = sin(x); plot(x,y) set(gca,'XTick',-pi:pi/2:pi) set(gca,'XTickLabel',{'-pi','-pi/2','0','pi/2','pi'}) Now add axis labels and annotate the point -pi/4, sin(-pi/4). Adding Titles, Axis Labels, and Annotations MATLAB enables you to add axis labels and titles. For example, using the graph from the previous example, add an x- and y-axis label: xlabel('-\pi \leq \Theta \leq \pi') ylabel('sin(\Theta)') title('Plot of sin(\Theta)') text(-pi/4,sin(-pi/4),'\leftarrow sin(\pi\div4)',... 'HorizontalAlignment','left') Now change the line color to red by first finding the handle of the line object created by plot and then setting its Color property. In the same statement, set the LineWidth property to 2 points. set(findobj(gca,'Type','line','Color',[0 0 1]),... 'Color','red',... 'LineWidth',2) See Also axis, bar, grid, hold, legend, line, LineSpec, loglog, plot3, plotyy, semilogx, semilogy, subplot, title, xlabel, xlim, ylabel, ylim, zlabel, zlim, stem See the text String property for a list of symbols and how to display them. See the Plot Editor for information on plot annotation tools in the figure window toolbar. See Basic Plots and Graphs for related functions.

playshow plot3 ? 1994-2005 The MathWorks, Inc. np.random.seed(19680801) fig, ((ax, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(8, 6)) # Replicate the above example with a different font size and colormap. im, _ = heatmap(harvest, vegetables, farmers, ax=ax, cmap="Wistia", cbarlabel="harvest [t/year]") annotate_heatmap(im, valfmt="{x:.1f}", size=7) # Create some new data, give further arguments to imshow (vmin), # use an integer format on the annotations and provide some colors. data = np.random.randint(2, 100, size=(7, 7)) y = ["Book {}".format(i) for i in range(1, 8)] x = ["Store {}".format(i) for i in list("ABCDEFG")] im, _ = heatmap(data, y, x, ax=ax2, vmin=0, cmap="magma_r", cbarlabel="weekly sold copies") annotate_heatmap(im, valfmt="{x:d}", size=7, threshold=20, textcolors=["red", "white"]) # Sometimes even the data itself is categorical. Here we use a # :class:`matplotlib.colors.BoundaryNorm` to get the data into classes # and use this to colorize the plot, but also to obtain the class # labels from an array of classes. data = np.random.randn(6, 6) y = ["Prod. {}".format(i) for i in range(10, 70, 10)] x = ["Cycle {}".format(i) for i in range(1, 7)] qrates = np.array(list("ABCDEFG")) norm = matplotlib.colors.BoundaryNorm(np.linspace(-3.5, 3.5, 8), 7) fmt = matplotlib.ticker.FuncFormatter(lambda x, pos: qrates[::-1] [norm(x)]) im, _ = heatmap(data, y, x, ax=ax3, cmap=plt.get_cmap("PiYG", 7), norm=norm, cbar_kw=dict(ticks=np.arange(-3, 4), format=fmt), cbarlabel="Quality Rating") annotate_heatmap(im, valfmt=fmt, size=9, fontweight="bold", threshold=-1, textcolors=["red", "black"]) # We can nicely plot a correlation matrix. Since this is bound by -1 and 1, # we use those as vmin and vmax. We may also remove leading zeros and hide # the diagonal elements (which are all 1) by using a # :class:`matplotlib.ticker.FuncFormatter`. corr_matrix = np.corrcoef(np.random.rand(6, 5)) im, _ = heatmap(corr_matrix, vegetables, vegetables, ax=ax4, cmap="PuOr", vmin=-1, vmax=1, cbarlabel="correlation coeff.") def func(x, pos): return "{:.2f}".format(x).replace("0.", ".").replace("1.00", "") annotate_heatmap(im, valfmt=matplotlib.ticker.FuncFormatter(func), size=7) plt.tight_layout() plt.show() You can change the color of bars in a barplot using color argument. RGB is a way of making colors. You have to to provide an amount of red, green, blue, and the transparency value to the color argument and it returns a color.# libraries import numpy as np import matplotlib.pyplot as plt # create a dataset height = [3, 12, 5, 18, 45] bars = ('A', 'B', 'C', 'D', 'E') x_pos = np.arange(len(bars)) # Create bars plt.bar(x_pos, height, color=(0.2, 0.4, 0.6, 0.6)) # Create names on the x-axis plt.xticks(x_pos, bars) # Show graph plt.show()Different color for each barIf you want to give different colors to each bar, just provide a list of color names to the color argument:# libraries import numpy as np import matplotlib.pyplot as plt # create a dataset height = [3, 12, 5, 18, 45] bars = ('A', 'B', 'C', 'D', 'E') x_pos = np.arange(len(bars)) # Create bars with different colors plt.bar(x_pos, height, color=['black', 'red', 'green', 'blue', 'cyan']) # Create names on the x-axis plt.xticks(x_pos, bars) # Show graph plt.show()The edgecolor argument allows you to color the borders of barplots.# libraries import numpy as np import matplotlib.pyplot as plt # create a dataset height = [3, 12, 5, 18, 45] bars = ('A', 'B', 'C', 'D', 'E') x_pos = np.arange(len(bars)) # Create bars with blue edge color plt.bar(x_pos, height, color=(0.1, 0.1, 0.1, 0.1), edgecolor='blue') # Create names on the x-axis plt.xticks(x_pos, bars) # Show graph plt.show()

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