130 lines
4.2 KiB
Python
130 lines
4.2 KiB
Python
""" npz/hdf5 file based storage;
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this modules adds the possibility to dump and load objects in files and
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a more convenient was of accessing the data via the .attributedict thanks
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to the DataStorage class """
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import numpy as np
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import os
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import h5py
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import collections
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import logging as log
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log.basicConfig(level=log.INFO)
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def unwrapArray(a,recursive=True,readH5pyDataset=True):
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""" This function takes an object (like a dictionary) and recursivively
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unwraps it solving many issues like the fact that many objects are
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packaged as 0d array
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This funciton has also some specific hack for handling h5py limit to
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handle for example the None object or the numpy unicode ...
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"""
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# is h5py dataset convert to array
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if isinstance(a,h5py.Dataset) and readH5pyDataset: a = a[...]
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if isinstance(a,h5py.Dataset) and a.shape == (): a = a[...]
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if isinstance(a,np.ndarray) and a.ndim == 0 : a = a.item()
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if isinstance(a,np.ndarray) and a.dtype.char == "S": a = a.astype(str)
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if recursive:
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if "items" in dir(a): # dict, h5py groups, npz file
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a = dict(a); # convert to dict, otherwise can't asssign values
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for key,value in a.items(): a[key] = unwrapArray(value)
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elif isinstance(a,list):
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for index in range(len(a)): a[index] = unwrapArray(a[i])
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else:
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pass
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if isinstance(a,dict): a = DataStorage(a)
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# restore None that cannot be saved in h5py
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if isinstance(a,str) and a == "NONE_PYTHON_OBJECT": a = None
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# h5py can't save numpy unicode
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if isinstance(a,np.ndarray) and a.dtype.char == "S": a = a.astype(str)
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return a
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def dictToH5Group(d,group):
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""" helper function that transform (recursive) a dictionary into an
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hdf group by creating subgroups """
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for key,value in d.items():
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if isinstance(value,dict):
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group.create_group(key)
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dictToH5Group(value,group[key])
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else:
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# h5py can't handle numpy unicode arrays
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if isinstance(value,np.ndarray) and value.dtype.char == "U":
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value = np.asarray([vv.encode('ascii') for vv in value])
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# h5py can't save None
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if value is None: value="NONE_PYTHON_OBJECT"
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try:
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group[key] = value
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except TypeError:
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log.error("Can't save %s"%(key))
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def dictToH5(h5,d):
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""" Save a dictionary into an hdf5 file
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h5py is not capable of handling dictionaries natively"""
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h5 = h5py.File(h5,mode="w")
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# group = h5.create_group("/")
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dictToH5Group(d,h5["/"])
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h5.close()
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def h5ToDict(h5,readH5pyDataset=True):
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""" Read a hdf5 file into a dictionary """
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with h5py.File(h5,"r") as h:
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ret = unwrapArray(h,recursive=True,readH5pyDataset=readH5pyDataset)
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return ret
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def npzToDict(npzFile):
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with np.load(npzFile) as npz: d = dict(npz)
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d = unwrapArray(d,recursive=True)
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return d
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def dictToNpz(npzFile,d): np.savez(npzFile,**d)
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def read(fname):
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extension = os.path.splitext(fname)[1]
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log.info("Reading storage file %s"%fname)
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if extension == ".npz":
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return npzToDict(fname)
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elif extension == ".h5":
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return h5ToDict(fname)
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else:
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raise ValueError("Extension must be h5 or npz, it was %s"%extension)
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def save(fname,d):
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extension = os.path.splitext(fname)[1]
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log.info("Saving storage file %s"%fname)
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if extension == ".npz":
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return dictToNpz(fname,d)
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elif extension == ".h5":
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return dictToH5(fname,d)
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else:
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raise ValueError("Extension must be h5 or npz")
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class DataStorage(dict):
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""" Storage for 1d integrated info """
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def __init__(self,fileOrDict,default_name='pyfai_1d',default_ext='npz'):
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if isinstance(fileOrDict,dict):
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self.filename = None
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d = fileOrDict
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else:
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assert isinstance(fileOrDict,str)
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if os.path.isdir(fileOrDict):
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fileOrDict = fileOrDict + "/" + default_name + "." + default_ext
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self.filename = fileOrDict
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d = read(fileOrDict)
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# allow accessing with .data, .delays, etc.
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for k,v in d.items(): setattr(self,k,v)
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# allow accessing as proper dict
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self.update( **dict(d) )
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def __setitem__(self, key, value):
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setattr(self,key,value)
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super().__setitem__(key, value)
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def __delitem__(self, key):
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delattr(self,key)
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super().__delitem__(key)
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def save(self,fname=None):
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if fname is None: fname = self.filename
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assert fname is not None
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save(fname,dict(self))
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