Python 3.x Dask map_块-索引器:元组索引超出范围
我想对Dask执行以下操作:Python 3.x Dask map_块-索引器:元组索引超出范围,python-3.x,dask,dask-delayed,Python 3.x,Dask,Dask Delayed,我想对Dask执行以下操作: 从HDF5文件加载矩阵 并行化每个条目的计算 这是我的密码: def blocked_func(x): return np.random.random() with h5py.File(file_path) as f: d = f['/data'] arr = da.from_array(d, chunks=(chunks_row, chunks_col)) arr2 = arr.map_blocks(blocked_func,
def blocked_func(x):
return np.random.random()
with h5py.File(file_path) as f:
d = f['/data']
arr = da.from_array(d, chunks=(chunks_row, chunks_col))
arr2 = arr.map_blocks(blocked_func, dtype='float32').compute()
但代码会引发以下错误:
File ".../remote_fr_thinkpad/test_big_data.py", line 43, in <module>
arr2 = arr.map_blocks(blocked_func, dtype='float32').compute()
File ".../anaconda3/lib/python3.7/site-packages/dask/base.py", line 156, in compute
(result,) = compute(self, traverse=False, **kwargs)
File ".../anaconda3/lib/python3.7/site-packages/dask/base.py", line 399, in compute
return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
File ".../anaconda3/lib/python3.7/site-packages/dask/base.py", line 399, in <listcomp>
return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
File ".../anaconda3/lib/python3.7/site-packages/dask/array/core.py", line 779, in finalize
return concatenate3(results)
File ".../anaconda3/lib/python3.7/site-packages/dask/array/core.py", line 3497, in concatenate3
chunks = chunks_from_arrays(arrays)
File ".../anaconda3/lib/python3.7/site-packages/dask/array/core.py", line 3327, in chunks_from_arrays
result.append(tuple([shape(deepfirst(a))[dim] for a in arrays]))
File ".../anaconda3/lib/python3.7/site-packages/dask/array/core.py", line 3327, in <listcomp>
result.append(tuple([shape(deepfirst(a))[dim] for a in arrays]))
IndexError: tuple index out of range
文件“../remote\u fr\u thinkpad/test\u big\u data.py”,第43行,在
arr2=arr.map_块(blocked_func,dtype='float32').compute()
文件“../anaconda3/lib/python3.7/site packages/dask/base.py”,第156行,在compute中
(结果,)=compute(自我,遍历=False,**kwargs)
文件“../anaconda3/lib/python3.7/site packages/dask/base.py”,第399行,在compute中
返回重新打包([f(r,*a)用于r,(f,a)压缩(结果,邮政编码)])
文件“../anaconda3/lib/python3.7/site packages/dask/base.py”,第399行,在
返回重新打包([f(r,*a)用于r,(f,a)压缩(结果,邮政编码)])
文件“../anaconda3/lib/python3.7/site packages/dask/array/core.py”,第779行,最终确定
返回3(结果)
文件“../anaconda3/lib/python3.7/site packages/dask/array/core.py”,第3497行,连接3
chunks=来自数组的chunks\u(数组)
文件“../anaconda3/lib/python3.7/site packages/dask/array/core.py”,第3327行,从_数组中分块_
追加(tuple([shape(deepfirst(a))[dim]表示数组中的a]))
文件“../anaconda3/lib/python3.7/site packages/dask/array/core.py”,第3327行,在
追加(tuple([shape(deepfirst(a))[dim]表示数组中的a]))
索引器错误:元组索引超出范围
我在谷歌上搜索了一下,还尝试了达斯克的gu_func,但也出现了同样的错误
谢谢您的帮助。
map\u block
希望blocked\u func
返回与其输入相同形状的数组(chunks\u row,chunks\u col)
,而实际上它只返回一个浮点
两种方法都可以
1) 保持形状的函数,例如:
def blocked_func(x):
return x*2
或
2) 告诉map_blocks
输出的形状将不同:
arr2 = arr.map_blocks(blocked_func, chunks=(1,1), dtype='float32').compute()
但将输入数组的维数保留在blocked_func
中,例如:
def blocked_func(x):
return np.random.random()[None,None]
# or like this
# return np.array([1,1])