If I’m understanding your question correctly, your input “observation” data is regularly gridded? If so, scipy.ndimage.map_coordinates does exactly what you want. It’s a bit hard to understand at first pass, but essentially, you just feed it a sequence of coordinates that you want to interpolate the values of the grid at in pixel/voxel/n-dimensional-index coordinates. As … Read more
.plot_surface() takes 2D arrays as inputs, not 1D DataFrame columns. This has been explained quite well here, along with the below code that illustrates how one could arrive at the required format using DataFrame input. Reproduced below with minor modifications like additional comments. Alternatively, however, there is .plot_trisurf() which uses 1D inputs. I’ve added an … Read more
Note that this answer is outdated as of 2018; scipy has deprecated imread, and you should switch to imageio.imread. See this transition doc about differences between the two. The code below should work with no changes if you just import the new library in place of the old, but I haven’t tested it. The simplest … Read more
It’s easier than you think: >>> import numpy >>> A = numpy.array(((1,2),(3,4))) >>> idx = (0,0) >>> A[idx] 1
shorter, faster and clearer answer, avoiding meshgrid: import numpy as np def func(x, y): return np.sin(y * x) xaxis = np.linspace(0, 4, 10) yaxis = np.linspace(-1, 1, 20) result = func(xaxis[:,None], yaxis[None,:]) This will be faster in memory if you get something like x^2+y as function, since than x^2 is done on a 1D array … Read more
We need to use list of indices that are to be kept in sorted order instead of feeding the kth param as a scalar. Thus, to maintain the sorted nature across the first 5 elements, instead of np.argpartition(a,5)[:5], simply do – np.argpartition(a,range(5))[:5] Here’s a sample run to make things clear – In [84]: a = … Read more
You can use the numpy.timedelta64 object to perform time delta calculations on a numpy.datetime64 object, see Datetime and Timedelta Arithmetic. Since a year can be either 365 or 366 days, it is not possible to substract a year, but you could substract 365 days instead: import numpy as np np.datetime64(‘2014-12-31′) – np.timedelta64(365,’D’) results in: numpy.datetime64(‘2013-12-31’)
eigh guarantees you that the eigenvalues are sorted and uses a faster algorithm that takes advantage of the fact that the matrix is symmetric. If you know that your matrix is symmetric, use this function. Attention, eigh doesn’t check if your matrix is indeed symmetric, it by default just takes the lower triangular part of … Read more
scipy.misc.imread() will return a Numpy array, which is handy for lots of things.
I know it is too late for this answer, but I am excited learning NumPy. You can vectorize the function on your own with numpy.where. def func(x): import numpy as np x = np.where(x<0, 0., x*10) return x Examples Using a scalar as data input: x = 10 y = func(10) y = array(100.0) using … Read more