我有代表大气层的 3d 数据。现在我想将此数据插入到一个公共(public) Z 坐标(我的意思应该从函数的文档中清楚)。下面的代码工作正常,但我想知道是否有提高性能的方法......
def interpLevel(grid,value,data,interp='linear'):
"""
Interpolate 3d data to a common z coordinate.
Can be used to calculate the wind/pv/whatsoever values for a common
potential temperature / pressure level.
grid : numpy.ndarray
The grid. For example the potential temperature values for the whole 3d
grid.
value : float
The common value in the grid, to which the data shall be interpolated.
For example, 350.0
data : numpy.ndarray
The data which shall be interpolated. For example, the PV values for
the whole 3d grid.
kind : str
This indicates which kind of interpolation will be done. It is directly
passed on to scipy.interpolate.interp1d().
returs : numpy.ndarray
A 2d array containing the *data* values at *value*.
"""
ret = np.zeros_like(data[0,:,:])
# we need to copy the grid to a new one, because otherwise the flipping
# done below will be messed up
gr = np.zeros_like(grid)
da = np.zeros_like(data)
for latIdx in xrange(grid.shape[1]):
for lonIdx in xrange(grid.shape[2]):
# check if we need to flip the column
if grid[0,latIdx,lonIdx] > grid[-1,latIdx,lonIdx]:
gr[:,latIdx,lonIdx] = grid[::-1,latIdx,lonIdx]
da[:,latIdx,lonIdx] = data[::-1,latIdx,lonIdx]
else:
gr[:,latIdx,lonIdx] = grid[:,latIdx,lonIdx]
da[:,latIdx,lonIdx] = data[:,latIdx,lonIdx]
f = interpolate.interp1d(gr[:,latIdx,lonIdx], \
da[:,latIdx,lonIdx], \
kind=interp)
ret[latIdx,lonIdx] = f(value)
return ret
最佳答案
好吧,这可能会稍微提速,因为它使用的内存更少。
ret = np.zeros_like(data[0,:,:])
for latIdx in xrange(grid.shape[1]):
for lonIdx in xrange(grid.shape[2]):
# check if we need to flip the column
if grid[0,latIdx,lonIdx] > grid[-1,latIdx,lonIdx]:
ind = -1
else:
ind = 1
f = interpolate.interp1d(grid[::ind,latIdx,lonIdx], \
data[::ind,latIdx,lonIdx], \
kind=interp)
ret[latIdx,lonIdx] = f(value)
return ret
我所做的就是真正摆脱 gr 和 da。
除此之外,您是否使用大量不同的值调用此函数(即值不同但其他参数相同)?如果是这样,您可能希望使该函数能够处理多个值(添加另一个维度 ret 换句话说,它与值的长度一样长)。这样您就可以更好地利用您创建的插值函数。
最后的建议是尝试a profiler .它可以让您看到什么花费的时间最多。
关于python - 使用 SciPy 对 3d 数据进行插值时如何提高性能,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/2312665/