Databases
StackOverflow2013
Postsdbo
POPython/Scipy Interpolation (map_coordinates)
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POPython/Scipy Interpolation (map_coordinates)
    primarykey
    data
    text
    <p>I'm trying to do some interpolation with scipy. I've gone through many examples, but I'm not finding exactly what I want.</p> <p>Let's say I have some data where the row and column variable can vary from 0 to 1. The delta changes between each row and column is not always the same (see below).</p> <pre><code> | 0.00 0.25 0.80 1.00 ------|---------------------------- 0.00 | 1.40 6.50 1.50 1.80 0.60 | 8.90 7.30 1.10 1.09 1.00 | 4.50 9.20 1.80 1.20 </code></pre> <p>Now I want to be able to take a set of x,y points and determine the interpolated values. I know I can do this with map_coordinates. I'm wondering if there is any easy/clever way to make an x,y value to the appropriate index in the data array.</p> <p>For example, if I input x,y = 0.60, 0.25, then I should get back the correct index to be interpolated. In this case, that would be 1.0, 1.0 since 0.60, 0.25 would map exactly to the second row and second column. x=0.3 would map to 0.5 since it is halfway between 0.00 and 0.60.</p> <p>I know how to get the result I want, but I feel certain that there is a very quick/clear one or two-liner (or function that already exists) that can do this to make my code more clear. Basically it needs to piecewise interpolate between some array.</p> <p>Here is an example (based heavily on the code from <a href="https://stackoverflow.com/questions/3057015/scipy-interpolation-on-a-numpy-array">Scipy interpolation on a numpy array</a>) - I put TODO where this new function would go:</p> <pre><code>from scipy.ndimage import map_coordinates from numpy import arange import numpy as np # 0.000, 0.175, 0.817, 1.000 z = array([ [ 3.6, 6.5, 9.1, 11.5], # 0.0000 [ 3.9, -7.3, 10.0, 13.1], # 0.2620 [ 1.9, 8.3, -15.0, -12.1], # 0.6121 [-4.5, 9.2, 12.2, 14.8] ]) # 1.0000 ny, nx = z.shape xmin, xmax = 0., 1. ymin, ymax = 0., 1. xrange = array([0.000, 0.175, 0.817, 1.000 ]) yrange = array([0.0000, 0.2620, 0.6121, 1.0000]) # Points we want to interpolate at x1, y1 = 0.20, 0.45 x2, y2 = 0.30, 0.85 x3, y3 = 0.95, 1.00 # To make our lives easier down the road, let's # turn these into arrays of x &amp; y coords xi = np.array([x1, x2, x3], dtype=np.float) yi = np.array([y1, y2, y3], dtype=np.float) # Now, we'll set points outside the boundaries to lie along an edge xi[xi &gt; xmax] = xmax xi[xi &lt; xmin] = xmin yi[yi &gt; ymax] = ymax yi[yi &lt; ymin] = ymin # We need to convert these to (float) indicies # (xi should range from 0 to (nx - 1), etc) xi = (nx - 1) * (xi - xmin) / (xmax - xmin) yi = (ny - 1) * (yi - ymin) / (ymax - ymin) # TODO: Instead, xi and yi need to be mapped as described. This can only work with # even spacing...something like: #xi = SomeInterpFunction(xi, xrange) #yi = SomeInterpFunction(yi, yrange) # Now we actually interpolate # map_coordinates does cubic interpolation by default, # use "order=1" to preform bilinear interpolation instead... print xi print yi z1, z2, z3 = map_coordinates(z, [yi, xi], order=1) # Display the results for X, Y, Z in zip((x1, x2, x3), (y1, y2, y3), (z1, z2, z3)): print X, ',', Y, '--&gt;', Z </code></pre>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. USCommunity
    1. USScott B
    plurals
    1. PL
      singulars
      1. LTLinked
    2. PL
      singulars
      1. LTLinked
    1. PL
      singulars
      1. LTLinked
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POPython/Scipy Interpolation (map_coordinates)
      1. USunutbu
      1. VTFavorite
    2. VO
      singulars
      1. POPython/Scipy Interpolation (map_coordinates)
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POPython/Scipy Interpolation (map_coordinates)
      1. This table or related slice is empty.
      1. VTUpMod
    1. This table or related slice is empty.
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload