Reputation: 531
I'm trying to overwrite a numpy array that's a small part of a pretty complicated h5 file.
I'm extracting an array, changing some values, then want to re-insert the array into the h5 file.
I have no problem extracting the array that's nested.
f1 = h5py.File(file_name,'r')
X1 = f1['meas/frame1/data'].value
f1.close()
My attempted code looks something like this with no success:
f1 = h5py.File(file_name,'r+')
dset = f1.create_dataset('meas/frame1/data', data=X1)
f1.close()
As a sanity check, I executed this in Matlab using the following code, and it worked with no problems.
h5write(file1, '/meas/frame1/data', X1);
Does anyone have any suggestions on how to do this successfully?
Upvotes: 53
Views: 56562
Reputation: 85
Different scenarios:
with h5py.File(file_name,'r+') as ds:
ds['meas/frame1/data'][5] = val # change index 5 to scalar "val"
ds['meas/frame1/data'][3:7] = vals # change values of indices 3--6 to "vals"
with h5py.File(file_name,'r+') as ds:
ds['meas/frame1/data'][...] = X1 # change array values to those of "X1"
with h5py.File(file_name,'r+') as ds:
del ds['meas/frame1/data'] # delete old, differently sized dataset
ds.create_dataset('meas/frame1/data',data=X1) # implant new-shaped dataset "X1"
Since the File object is a context manager, using with statements is a nice way to package your code, and automatically close out of your dataset once you're done altering it. (You don't want to be in read/write mode if you only need to read off data!)
Upvotes: 4
Reputation: 46550
You want to assign values, not create a dataset:
f1 = h5py.File(file_name, 'r+') # open the file
data = f1['meas/frame1/data'] # load the data
data[...] = X1 # assign new values to data
f1.close() # close the file
To confirm the changes were properly made and saved:
f1 = h5py.File(file_name, 'r')
np.allclose(f1['meas/frame1/data'].value, X1)
#True
Upvotes: 55
Reputation: 3190
askewchan's answer describes the way to do it (you cannot create a dataset under a name that already exists, but you can of course modify the dataset's data). Note, however, that the dataset must have the same shape as the data (X1
) you are writing to it. If you want to replace the dataset with some other dataset of different shape, you first have to delete it:
del f1['meas/frame1/data']
dset = f1.create_dataset('meas/frame1/data', data=X1)
Upvotes: 48