title: Scipy griddata interpolating only from boundary information
body: <p>I'm using griddata from Scipy in Python 2.7 to interpolate from some coarse sampling data to make a contour plot.  In short, I have a pond with a certain outline and depth/pH/temperature measurements throughout the pond.  At the boundaries, I set the depth = 0 and pH/temperature to the same as the nearest neighbor sample point inside of the pond.</p>
  
  <p>However, after running the script and messing around with the input data, it has become apparent that griddata is simply taking the data from the exterior of the area that I'm trying to interpolate in and simply deriving an interpolant from that.  I can enter into whatever data I want in the interior, and it will not matter at all to the result.</p>
  
  <p>I've created the following, simplified example that appears to display the same behavior.  In it, I specify a 5x5 grid of manufactured data, which is all zero except for the dead center, which is large.  I then try to interpolate data on a grid that is 4 times as dense, thinking that I should see some sort of a spike in the middle.  Instead, all values come out as the same thing: zero.  This code is given below:</p>
  
  <pre><code>import numpy as np
  from scipy.interpolate import griddata as grid_interp
  import matplotlib.pyplot as plt
  
  ########################################################################
  
  # create input grid
  input_grid = np.zeros([25,2])
  k=0
  for i in range(5):
      for j in range(5):
          input_grid[k,0] = i
          input_grid[k,1] = j
          k = k + 1
  
  # put a value in the center of the grid
  input_values = np.zeros([25,1])
  input_values[12] = 1000000.0
  
  # create grid to interpolate onto
  target_grid = np.ones([100,100,2])
  for i in range(100):
      for j in range(100):
          target_grid[i,j,0] = i/100*5
          target_grid[i,j,1] = i/100*5
  
  # perform interpolation
  data_out = grid_interp(input_grid,input_values,target_grid[:,:,:],method='cubic',fill_value=-99)
  
  # format for contourf
  plot_array = np.zeros([100,100])
  plot_array[:,:] = data_out[:,:,0]
  
  # plot
  plt.contourf(target_grid[:,:,0],target_grid[:,:,1],plot_array)
  </code></pre>
  
  <p>So...at this point, I'm not sure what I'm missing.  Any help would be appreciated.</p>