polar-coordinates

How do I combine gridded polar and Cartesian data on a plot? It is important to note that axes origins and scales have to match. In my application, I want to combine weather radar data ( polar ) with elevation data (Cartesian). This is the starting point : Thinking about this for a while, the answer is you need to translate you radial data into Cartesian space: import copy # fake....err, simulated... data # elevation X, Y = np.meshgrid(np.linspace(-50, 50, 1024), np.linspace(-50, 50, 1024)) elv = np.sin(np.pi * X / 50) * np.cos(2*np.pi * Y / 50) # radar R, theta = np.meshgrid(np.linspace(0, 35

I have a problem changing my axis labels in Matplotlib. I want to change the radial axis options in my Polar Plot. Basically, I'm computing the distortion of a cylinder, which is nothing but how much the radius deviates from the original (perfectly circular) cylinder. Some of the distortion values are negative, while some are positive due to tensile and compressive forces. I'm looking for a way to represent this in cylindrical coordinates graphically, so I thought that a polar plot was my best bet. Excel gives me a 'radar chart' option which is flexible enough to let me specify minimum and

I'm trying to convert an image with many circles with the same center, from Cartesian to Polar (so that the new image will be the circles but lines instead of the circles, see the image below), and that's working out just fine using the following code: [r, c] = size(img); r=floor(r/2); c=floor(c/2); [X, Y] = meshgrid(-c:c-1,-r:r-1); [theta, rho] = cart2pol(X, Y); subplot(221), imshow(img), axis on; hold on; subplot(221), plot(xCenter,yCenter, 'r+'); subplot(222), warp(theta, rho, zeros(size(theta)), img); view(2), axis square; The problem is, I don't understand why does it even work?

I have a polar plot where theta varies from 0 to pi/2, so the whole plot lies in the first quater, like this: %pylab inline X=linspace(0,pi/2) polar(X,cos(6*X)**2) (source: schurov.com ) Is it possible by means of pyplot or matplotlib to clip the polar plot so that only first quater is shown (and therefore no space is wasted)? I want a picture like this (but properly scaled): (source: schurov.com ) I'd like to do it by means of pyplot because I have several images like this and want to arrange them into a big figure (with subplot). Is it possible? I recommend not using the polar plot but

I have a circular space where angles 0 and 360 are equivalent. I want to plot rectangles in this space such that rectangles can cross this value. However, I am having trouble with ggplot2. base <- ggplot() + scale_x_continuous(breaks = seq(45, 360, 45), limits = c(0, 360)) + scale_y_continuous(breaks = seq(0, 1, 0.2), limits = c(0, 1)) + coord_polar(theta = "x", start = 1.5 * pi, direction = -1) 1. Attempt to plot with values exceeding xlim: base + geom_rect(aes(xmin = 340, xmax = 380, ymin = 0.4, ymax = 0.6), color = "darkblue", fill = "steelblue") #> Warning message: #> Removed 1 rows

The question R interpolated polar contour plot shows an excellent way to produce interpolated polar plots in R. I include the very slightly modified version I'm using: PolarImageInterpolate <- function( ### Plotting data (in cartesian) - will be converted to polar space. x, y, z, ### Plot component flags contours=TRUE, # Add contours to the plotted surface legend=TRUE, # Plot a surface data legend? axes=TRUE, # Plot axes? points=TRUE, # Plot individual data points extrapolate=FALSE, # Should we extrapolate outside data points? ### Data splitting params for color scale and contours col_breaks

I am trying to create a simple stereographic sun path diagram similar to these: http://wiki.naturalfrequency.com/wiki/Sun-Path_Diagram I am able to rotate a polar plot and set the scale to 90. How do I go about reversing the y-axis? Currently the axis goes from 0>90, how do I reverse the axis to 90>0 to represent the azimuth? I have tried: ax.invert_yaxis() ax.yaxis_inverted() Further, how would I go about creating a stereographic projection as opposed to a equidistant? My code: import matplotlib.pylab as plt testFig = plt.figure(1, figsize=(8,8)) rect = [0.1,0.1,0.8,0.8] testAx = testFig.add

my previous question ( Integral of Intensity function in python ) you can see the diffraction model in image below: I want to calculate integral of intensity in each pixel (square), so I can't use R and Theta as variable. How can I do this in X-Y coordinate. Our function: instead of sin(theta) we can use: sintheta= (np.sqrt((x)**2 + (y)**2)/(np.sqrt((x)**2 + (y)**2 + d**2))) Other constants: lamb=550*10**(-9) k=2.0*np.pi/lamb a=5.5*2.54*10**(-2) d=2.8 when you plot function, the result is something like this:(The image above is a view from top) the method in previous topic: calculate integrate

From matplotlib examples : import numpy as np import seaborn as sbs import matplotlib.pyplot as plt r = np.arange(0, 3.0, 0.01) theta = 2 * np.pi * r ax = plt.subplot(111, polar=True) ax.plot(theta, r, color='r', linewidth=3) ax.set_rmax(2.0) ax.grid(True) ax.set_title("A line plot on a polar axis", va='bottom') plt.show() How to move the radial tick labels (0.5, 1.0, 1.5, 2.0) to a different angle, say 120 deg? With version 1.4 or later, you can use "set_rlabel_position". e.g. to place the radial ticks a long a line at, say, 135 degrees: ax.set_rlabel_position(135) The relevant documentation