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How to add a single new contour to a contour plot in Lattice
Load the latticeExtra library. Then: Part1<-contourplot( Male ~ Year * Age, data=this.ds, region=T, col.regions=rev(heat.colors(200)), cuts=50, main="", sep="") Part2<-contourplot( Male ~ Year * Age, data=this.ds, region=F, labels=F, lwd=2, at=c(0, 0.01, 1)) Plot.Final<-Part1+Part2 That should combine the graphs as you wish. If needed you may need to set xlim, ylim and labels so that everything looks OK.

Categories : R

Matplotlib: Scatter Plot to Foreground on top of a Contour Plot
You can manually choose in which order the different plots are to be displayed with the zorder parameter of e.g. the scatter method. To demonstrate, see the code below, where the scatter plot in the left subplot has zorder=1 and in the right subplot it has zorder=-1. The object with the highest zorder is placed on top. This means that the scatter will be placed on top of the contour in the first subplot, while it is placed underneath in the second subplot. import numpy as np import matplotlib.cm as cm import matplotlib.mlab as mlab import matplotlib.pyplot as plt delta = 0.025 x = np.arange(-3.0, 3.0, delta) y = np.arange(-2.0, 2.0, delta) X, Y = np.meshgrid(x, y) Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1) Z = 10.0 * (Z2 - Z1)

Categories : Python

Using contour to plot function
Are x and y properly defined as 2x2 matrices? If so then the "power" operator needs to be done on a component-wise basis (.^3 instead of ^3). This works: [x,y] = meshgrid(-2:.2:2,-2:.2:2); contour(3*y+y.^3-x.^3-5)

Categories : Matlab

Need Help in Contour Plot in Matlab
There are a few things to note: 1.) As Jacob Robbins pointed out correctly in his comment, you should avoid using names from Matlab functions as variable names (in your case min and max). One very easy way to do this, is to use only upper case letters for variable names. 2.) You are correct in saying that your fis only one output (though one output in this case is not a single number, but a vector). That is, because you don't assign any indexing to it within the loop. 3.) Yes, both contour and surfc need at least 2x2 - because they plot information on a grid, which is itself at least 2x2 in nature. 4.) In your particular case, two loops may not be necessary. You seem to only be manipulating the x-vector and your grid is regular. Hence you might want to try this loop: for I=1:le

Categories : Algorithm

Long error in contour plot python
The error states that TypeError: Input z must be a 2D array. if you look at the sizes of the input objects: print EF.shape, EB.shape, a.shape (51,) (51,) (51,) you'll see that these are not 2D arrays. Did you intend to use X and Y instead? When I make the change to a = ((1+.5*(np.exp(1.7*X)+np.exp(1.7*Y)+np.exp(1.7*(X+Y))))/(1+np.exp(1.7*X)+np.exp(1.7*Y)+np.exp(1.7*(X+Y)))) c = plt.contour(EF,EB,a,30) The output is It looks like you may need to adjust your parameter space since all the interesting stuff is around (0,0).

Categories : Python

Matplotlib - creating a filled 2d contour plot
As David said, use contourf: import numpy as np import pylab as pl x,y = np.mgrid[:1:1E-3,:1:1E-3] xs = ((x-0.3)**2.) ys = ((y-0.5)**2.) z = np.exp(-1*(xs/0.5+ys/0.3)) pl.contourf(x,y,z,20)

Categories : Python

Python/Matplotlib - Contour Plot with Bilinear Interpolation
This one seems to work. import matplotlib import numpy as np import matplotlib.cm as cm import matplotlib.pyplot as plt from scipy.interpolate import interp2d # http://en.wikipedia.org/wiki/File:Bilininterp.png xi = np.array([0.0, 1.0]) yi = np.array([0.0, 1.0]) zi = np.array([[0.0, 1.0], [1.0, 0.5]]) # Another example xi = np.array([0.0, 0.25, 1.0]) yi = np.array([0.0, 0.75, 1.0]) zi = np.array([[0.0, 0.5, 1.0], [0.5, 0.7, 0.5], [1.0, 1.0, 1.0]]) # I want 20 "levels" to be shown contour_breaks = 20 ticks = np.linspace(zi.min(), zi.max(), contour_breaks, endpoint=True) # Attempt 4 (interp2d does to correct bilinear interpolation) fig = plt.figure() axes = fig.add_subplot(111, aspect='equal') f = interp2d(xi, yi, zi, kind='linear') xi2 = np.linspace(0., 1., 100) yi2 = np.linspace(0., 1

Categories : Python

Smooth contour plot in matplotlib from 3 lists of different size
What you want seems to be a contour plot with a colorbar. You can do something like: X, Y = np.meshgrid(x, y, copy=False) Z = function(X, Y) # I don't know how you are getting the z values from... import matplotlib.pyplot as plt plt.contour(X, Y, Z) # non-filled contour or plt.contourf(X, Y, Z) # filled contour And to create the colorbar: plt.colorbar() check the documentation for more details and examples.

Categories : Python

How to Smooth a Plot in Matplotlib Without Losing Contour Lines?
Smoothing data -> losing data. My first reaction is: why do you want to display smoothed data? I've rarely ever seen data presentations in which data smoothing was actually helpful for the task of comprehending the data's implications. In fact, it's something Tufte has often criticized (that's not a reason to avoid doing it of course, but perhaps for asking yourself to come up with more justification than normal). If the plot needs to look pretty for some non-data-related reason, that's totally OK, but if you're trying to make it more pleasing to the eye when the task is to understand something about the nature of the contours, you're way better off just presenting the raw data as it is. If you have the different contours stored as separate sets of data (e.g. if you just steal the diff

Categories : Python

Adding an annotation box to a matplotlib contour/heat map plot
Annotation box to contour map: Done like this: import matplotlib.pyplot as plt import numpy as np from matplotlib import cm from numpy.random import randn from mpl_toolkits.axes_grid1.axes_divider import HBoxDivider import mpl_toolkits.axes_grid1.axes_size as Size def make_heights_equal(fig, rect, ax1, ax2, ax3, pad): # pad in inches h1, v1 = Size.AxesX(ax1), Size.AxesY(ax1) h2, v2 = Size.AxesX(ax2, 0.1), Size.AxesY(ax2) h3, v3 = Size.AxesX(ax3), Size.AxesY(ax3) pad_v = Size.Scaled(1) pad_h = Size.Fixed(pad) my_divider = HBoxDivider(fig, rect, horizontal=[h1, pad_h, h2, pad_h, h3], vertical=[v1, pad_v, v2, pad_v, v3]) ax1.set_axes_locator(my_divider.new_locator(0)) ax2.set_axes_locator

Categories : Python

How to plot contour of a covariance matrix of a gaussian distribution?
I finally did what i wanted to do by using a third party function called plot_gaussian_ellipsoid from the Matlab Central FileExchange. It plots the contour of the covariance matrix.

Categories : Matlab

matplotlib contour plot with lognorm - colorbar levels
From here I found an approach that seems to fit your question: from matplotlib.ticker import LogFormatter l_f = LogFormatter(10, labelOnlyBase=False) cbar = plt.colorbar(CF, ticks=lvls, format=l_f) which will give: note that the spacing between the ticks are indeed in log scale...

Categories : Python

How to show numeric values on a matlab contour plot
I have solved this issue. I use num2str and apply it on the text command and it has worked. here is what i did fv is the fitness values in my example strValues = strtrim(cellstr(num2str([fv],'(%d)'))); text(co(:,1), co(:,2),strValues,'VerticalAlignment','top'); the co are the points of the individuals(Pop) in my example.

Categories : Matlab

Matplotlib: Data cubic interpolation (or FIT) for Contour plot
You can adapt @Joe Kington's suggestion and use scipy.ndimage.zoom which for your case of a cubic interpolation fits perfectly: import matplotlib.pyplot as plt import numpy as np from scipy.ndimage import zoom from mpl_toolkits.mplot3d import axes3d # Receive standard Matplotlib data for 3d plot X, Y, Z = axes3d.get_test_data(1) # '1' is a step requested data #Calculate smooth data pw = 10 #power of the smooth Xsm = zoom(X, pw) Ysm = zoom(Y, pw) Zsm = zoom(Z, pw) # Create blank plot fig = plt.figure() #Create subplots ax1 = fig.add_subplot(211) ax2 = fig.add_subplot(212) # Plotting ax1.contour(X, Y, Z) ax2.contour(Xsm, Ysm, Zsm) plt.show() Which gives:

Categories : Python

Setting axis values of a 2D contour plot without using xticks
You can get rid of the error by taking out the extra parenthesis in the call to contour: CS=contour(x, y, jres_spec,arange(min_val,max_val,(max_val-min_val)/steps)) If that doesn't give you the plot you want, try xlim and ylim to set the axis limits directly.

Categories : Python

R: how to set the size of a contour plot with user defined aspect ratio?
Try this x <- 10*1:nrow(volcano) y <- 10*1:ncol(volcano) filled.contour(x, y, volcano,asp=1, frame.plot=F, plot.axes = { axis(1, pretty(x,min=0), line=-4) axis(2, seq(0, 600, by = 100)) })

Categories : R

weird contour plot with polar projections using matplotlib and basemap
Your Basemap object (m) also serves as the mpl axes. When plotting, you should use that instead of using plt.. So: m.contourf(x,y,TS2, fbot_levels, origin='lower') Stretching the levels between 0.5 and 0.9 highlights the different contours further.

Categories : Python

matplotlib contour plot: proportional colorbar levels in logarithmic scale
I propose to generate a pseudo colorbar as follows (see comments for explanations): import matplotlib.pyplot as plt import numpy as np from matplotlib.colors import LogNorm import matplotlib.gridspec as gridspec delta = 0.025 x = y = np.arange(0, 3.01, delta) X, Y = np.meshgrid(x, y) Z1 = plt.mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = plt.mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1) Z = 1e6 * (Z1 * Z2) fig=plt.figure() # # define 2 subplots, using gridspec to control the # width ratios: # # note: you have to import matplotlib.gridspec for this # gs = gridspec.GridSpec(1, 2,width_ratios=[15,1]) # the 1st subplot ax1 = plt.subplot(gs[0]) lvls = np.logspace(0,4,20) CF = ax1.contourf(X,Y,Z, norm = LogNorm(), levels = lvls

Categories : Python

how to draw a filled.contour plot with a data.frame of 3 variables in R (without regular grid)?
Thanks !!! It works !! From the time I was looking for... Here's what I did : library(akima) my.heat.colors <- function(x) { rev(heat.colors(x, alpha=1)) } my.matrix <- interp(X,Y,Z) ind.mat.na <- which(is.na(c(my.matrix$z))) my.matrix$z[ind.mat.na] <- 0 filled.contour(my.matrix, nlevels=10, color=my.heat.colors) And now I will plot contours on this. Thank you again !

Categories : R

Python: find contour lines from matplotlib.pyplot.contour()
You can get the vertices back by looping over collections and paths and using the iter_segments() method of matplotlib.path.Path. Here's a function that returns the vertices as a set of nested lists of contour lines, contour sections and arrays of x,y vertices: import numpy as np def get_contour_verts(cn): contours = [] # for each contour line for cc in cn.collections: paths = [] # for each separate section of the contour line for pp in cc.get_paths(): xy = [] # for each segment of that section for vv in pp.iter_segments(): xy.append(vv[0]) paths.append(np.vstack(xy)) contours.append(paths) return contours Edit: It's also possible to compute the contours without plotting

Categories : Python

Using matplotlib.animate to animate a contour plot in python
This is the line: cont, = ax.contourf([], [], [], 500) change to: x = linspace(0, 200, Nx) y = linspace(0, 100, Ny) x, y = meshgrid(x, y) z = n[i,:,0,:].T cont, = ax.contourf(x, y, z, 500) You need to intilize with sized arrays.

Categories : Python

drawing plot lines on QGraphicsScene
I'd say QPainter::drawPolyline() is a good option (or QPainterPath::addPolygon). You can use QPolygonF to contain your points. Then you just pass this to the QPainter's drawPolyline function. QPolygonF polyline; polyline.append(QPointF(x, y)); // add your points painter->drawPolyline(polyline); or QPainterPath painterPath; painterPath.addPolygon(polyline);

Categories : Qt

Drawing x-y plot with rhombus width and height controlled by xError and yError in R
You can use the my.symbols and ms.polygon functions in the TeachingDemos package to draw the rhombuses: library(TeachingDemos) plot(c(-5,10), c(-5,5), xlab = expression(Age), ylab = expression(value), type="n") my.symbols( Age, value, ms.polygon, n=4, xsize=2*Age_error, ysize=2*value_error, linesfun=polygon, col='grey' ) Leave out linesfun and col if you don't want the rhombuses filled.

Categories : R

Inacurate tracking when drawing calcOpticalFlow's outputed feature vector
In my opinion you can't use camera.set(CV_CAP_PROP_POS_FRAMES, currentFrame) on a webcam, but I 'm not positive about that. Instead I suggest you to save the previous frame in your prevFrame variable. As an example I can suggest you this working code, I only change inside the while loop and I add comment before all my adds : while(true) { if (destroyBox) { cv::destroyAllWindows(); break; } camera >> cameraFrame; if (cameraFrame.empty()) { std::cerr << "ERROR: Could not grab a camera frame." << std::endl; exit(1); } // new lines if(prevFrame.empty()){ prevFrame = cameraFrame; continue; } // end new lines //camera.set(CV_CAP_PROP_POS_FRAMES, currentFrame); /

Categories : Opencv

plot numeric vector with names as x ticks
You can use function axis() to add labels. Argument xaxt="n" inside plot() will make plot without x axis labels (numbers). plot(quantity,xaxt="n") axis(1,at=1:3,labels=names(quantity))

Categories : R

matplotlib bitmap plot with vector text
It should be as simple as passing in rasterized=True to the plot command. E.g. import matplotlib.pyplot as plt plt.plot(range(10), rasterized=True) plt.savefig('test.pdf') For me, this results in a pdf with a rasterized line (the resolution is controlled by the dpi you specified with savefig -- by default, it's 100) and vector text.

Categories : Python

how to make qplot produce a line plot with one vector of data
When I run plot(1:100), I get a points plot with x = seq_along(y), y = 1:100 to get the same plot using qplot, all you need to run is plot(1:100) qplot(y = 1:100) Within qplot there is if (missing(x)) { aesthetics$x <- bquote(seq_along(.(y)), aesthetics) } geom[geom == "auto"] <- "point which deals with this. qplot(1:100) will be parsed as qplot(x = 1:100) (using positional matching), and is dealt with by if (missing(y)) { geom[geom == "auto"] <- "histogram" if (is.null(ylab)) ylab <- "count" }

Categories : R

Is there an equivalent for data frames to the following code for vectors: unsampled.vector <- original.vector[-sampled.vector,]
You should probably save the value of the sample, then you can use negative indexing just as you would in a vector: sample_df <- mydf[s <- sample(nrow(mydf),10),] remainder_df <- mydf[-s,] Or more comprehensibly s <- sample(nrow(mydf),10) sample_df <- mydf[s,] remainder_df <- mydf[-s,]

Categories : R

Monogame not drawing vertex buffered cubes, only drawing GraphicsDevice.Clear colour
Thanks for all the help guys. I fixed the issue by changing graphicsDevice.DrawPrimitives(PrimitiveType.TriangleList, 0, 12); to graphicsDevice.DrawUserPrimitives(PrimitiveType.TriangleList, newVertices, 0, 12);

Categories : C#

Drawing an outer shadow when drawing an image
Here we go Yup I still dig the Nexus S First of all, please stop masking bitmaps that way, you can accomplish this without allocating another Bitmap, checkout this blog post about how to draw rounded (and actually any shape) images. Second using that Drawable you probably can figure out how to add your shadow, just make sure it does not get clipped, on 18+ you could use ViewOverlays for that, also keep in mind that there are several unsupported drawing operations for hardware accelerated layers, that includes setShadowLayer and BlurMaskFilter, if performance is not an issue for you, you can disable it as always: if (SDK_INT >= HONEYCOMB) { view.setLayerType(View.LAYER_TYPE_SOFTWARE, null); } And use setShadowLayer as you were trying already: somePaint.setShadowLayer(shadowSize

Categories : Android

OpenGL drawing in QDeclarativeItem messes up other QML drawing
The problem was caused from loading our texture data to the default texture object, which was also used by QML framework. Solution was to generate and bind unique textures in our own texture handling. For a OpenGL beginner like me this was a great lesson about texture handling. To handle other OpenGL state changes, it was sufficient to add glPushAttrib(GL_ALL_ATTRIB_BITS) and glPopAttrib() around our drawing.

Categories : Qt

It is possible to have all the axes displayed in the ilnumerics surface plot without affecting the plot size?
The extend occupied by the plot cube data groups is controlled by the ILPlotCube.DataScreenRect property. It defines the data area of the plot cube rectangle only - ignoring the space used by labels and axes. The DataScreenRect is automatically adjusted by default - depending on the sizes of axes (fonts, text heights), ticks, and tick labels configuration. By defining the DataScreenRect area yourself, you risk that some of these elements will move outside the visible area. Therefore, to enable optimal visibility for all elements, you may adjust the properties for label positions, and ticks as well. DataScreenRect in the online manual: http://ilnumerics.net/advanced-configurations.html DataScreenRect in the class reference: http://ilnumerics.net/apidoc/html/P_ILNumerics_Drawing_Plott

Categories : Misc

core plot scatter plot x y axis label not being displayed correctly
Change any references to _hostView.hostedGraph.graph to _hostView.hostedGraph. The graph property is inherited from CPTLayer. It is used by other parts of the graph to maintain a pointer to the graph, but not by the graph itself.

Categories : IOS

How do I plot multiple data subset forecast predictions onto a single plot
This is answered in another post Is there an easy way to revert a forecast back into a time series for plotting? This was initially posted as two unique questions, but they have the same answer. The core question being addressed is "how to restore the original time stamps to the forecast data". What I have learned with trial and error is "configure, then never loose the time series attribute" by applying these steps: 1: Make a time series Use the ts() command and create a time series. 2: Subset a time series Use 'window()' to create a subset of the time series in 'for()' loop. Use 'start()' and 'end()' on the data to show the time axis positions. 3: Forecast a time series Use 'forecast()' or 'predict()' which operate on time series. 4: Plot a time series When you plot a time series, the

Categories : R

Core plot- prevent zooming/scaling of plot to show full axes range
Is more a hint than an answer.. but, as I already said in comments: you can try to remove "scaleToFitPlots" and set xRange and yRange directly; or.. call -scaleToFitPlots: and then set the xRange afterwards

Categories : Iphone

Error while storing ggplots in list. Impossible to plot multiple ggplot, but possible to plot them seperately
Maybe you are looking for facet_wrap as Roland suggested. dat <- yourdata Get the mean and plot using facet_wrap moyparam<-ddply(dat, .(Date), function(x) data.frame(Mesure=mean(x$Mesure))) moyparam$Annee <- 1900 + as.POSIXlt(moyparam$Date)$year ggplot(moyparam, aes(Date, Mesure)) + geom_point() + theme_bw() + facet_wrap(~Annee, scales="free")

Categories : R

Iteration: sum of variable and vector front, export in another vector, erase vector front
Let's make this a bit simpler by taking out all the domain-specific stuff, and just discuss the basic question: [How do I] put the front value of vectorA in a local variable to add it to SUM, and then erase this front value? Here is a simple approach: vector <double> vectorA; double SUM = 0.0; // ... while (!vectorA.empty()) { const double curVal = vectorA.front(); // this strictly isn't necesarry. the compiler might optimize this away SUM += curVal; vectorA.erase (vectorA.begin()); } Now let's incorporate u: vector <double> vectorA; double SUM = 0.0; const double u = /* ??? */; // ... while (!vectorA.empty()) { const int curVal = vectorA.front(); // this strictly isn't necesarry. the compiler might optimize this away if (curVal > SUM) { SU

Categories : C++

core-plot scatter plot not showing with only one data point
The -scaleToFitPlots: method doesn't have enough information from only one data point to calculate "reasonable" axis ranges. In that case, set the xRange and yRange yourself based on the data you do have.

Categories : IOS

Add axis label to plot in matplotlib, by passing them as arguments to plot()
As @nordev already explained, you cannot pass through plot() the axis label, but inside your function you can get the active figure and then set the axis labels like the example below: import matplotlib.pyplot as plt def plot_something(x, y, **kwargs): title = kwargs.pop( 'title' ) xlabel = kwargs.pop( 'xlabel' ) ylabel = kwargs.pop( 'ylabel' ) plt.figure() plt.plot(x, y, **kwargs) fig = plt.gcf() for axis in fig.axes: axis.set_title( title ) axis.xaxis.set_label( xlabel ) axis.yaxis.set_label( ylabel ) return axis plot_conf = {'title': 'Blabla', 'xlabel':'Time (s)', 'ylabel': 'Speed (m/s)'} x = [1.,2.,3.] y = [1.,4.,9.] axis = plot_something(x=x,y=y, **plot_conf)

Categories : Python

HighCharts range area plot not working when plot is inverted
Torstein at HighCharts has implemented a fix to this bug that is in his GitHub repo: https://github.com/highslide-software/highcharts.com/commit/905535d2c56d61d034eed84eccf50e3bb44e1911 And he's posted an example here: see http://jsfiddle.net/highcharts/Tt485/2/ I tried his fix and it worked perfectly. He's planning a maintenance release soon to post the fix.

Categories : Highcharts



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