interpolation

One attempted approach was to use TexturePaint and g.fillRect() to paint the image. This however requires you to create a new TexturePaint and Rectangle2D object each time you paint an image, which isn't ideal - and doesn't help anyway. When I use g.drawImage(BufferedImage,...) , the rotated images appear to be blurred/soft. I'm familiar with RenderingHints and double-buffering (which is what I'm doing, I think), I just find it difficult to believe that you can't easily and efficiently rotate an image in Java that produces sharp results. Code for using TexturePaint looks something like this.

I'm trying to do a contour plot using matplotlib of a file with the following format: x1 y1 z1 x2 y2 z2 etc I can load it with numpy.loadtxt to get the vectors. So far, no trouble. I read this to learn how to plot, and can reproduce it by copy paste, so i'm sure nothin is wrong with my installation: http://matplotlib.org/examples/pylab_examples/griddata_demo.html I understand I have to input x and y as vector and z as an array ,which can be done with griddata. This is also what i find on this site. The documentation says: zi = griddata(x,y,z,xi,yi) fits a surface of the form z = f*(*x, y) to

I need to take the output of a matplotlib plot and turn it into an SVG path that I can use on a laser cutter. import matplotlib.pyplot as plt import numpy as np x = np.arange(0,100,0.00001) y = x*np.sin(2*pi*x) plt.plot(y) plt.show() For example, below you see a waveform. I would like to be able to output or save this waveform as an SVG path that I can later work with in a program such as Adobe Illustrator. I am aware of an SVG library called "Cairo" that matplotlib can use ( matplotlib.use('Cairo') ), however it's not clear to me that this will give me access to the SVG path that I need, even

I have been struggling to inteprolate the data for "empty" pixels in my 2D matrix. Basically, I understand (but not deeply) interpolation techniques such as Inverse Distance Weighting, Kriging, Bicubic etc. I dont know the starting point exactly (either in the statement of the problem or Python case). The problem definition: I have MxN matrix (regular grid) in which each pixel represents certain measurement value ( figure below and data used in this figure is here ). I wanted to interpolate the data for "question mark space" (white space which also consists of the same sized but empty pixels)