Note
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HDF5 cache¶
In this example, we will see how to use HDF5Cache
.
from __future__ import division, unicode_literals
from numpy import array
from gemseo.api import configure_logger
from gemseo.caches.hdf5_cache import HDF5Cache
configure_logger()
Out:
<RootLogger root (INFO)>
Import¶
Let’s first import the array
and the HDF5Cache
classes.
Create¶
A instance of HDF5Cache
can be instantiated with the following
statement. The user has to provide the file path of the HDF5 file, as well
as the node name, which usually is a discipline name.
cache = HDF5Cache("my_cache.hdf5", "node1")
It is possible to see the principal attributes of the cache by printing it, either using a print statement or using the logguer:
print(cache)
Out:
Name: node1
Type: HDF5Cache
Tolerance: 0.0
Input names: None
Output names: None
Length: 0
HDF file path my_cache.hdf5
HDF node path node1
Cache¶
In this example, we manually add data in the cache from the data dictionary
to illsutrate its use. Yet, it has to be noted that a cache can be attached
to an MDODiscipline
instance, and the user does not have to feed the
cache manually.
Here, we provide to the cache the data dictionary, and we set x as input
and y as output.
data = {"x": array([1.0]), "y": array([2.0])}
cache.cache_outputs(data, ["x"], data, ["y"])
data = {"x": array([2.0]), "y": array([3.0])}
cache.cache_outputs(data, ["x"], data, ["y"])
print(cache)
Out:
Name: node1
Type: HDF5Cache
Tolerance: 0.0
Input names: ['x']
Output names: ['y']
Length: 2
HDF file path my_cache.hdf5
HDF node path node1
Get all data¶
We can now print some information from the cache, such as its length. We can also display all the cached data so far.
print(cache.get_length())
print(cache.get_all_data())
Out:
2
{1: {'inputs': {'x': array([1.])}, 'outputs': {'y': array([2.])}, 'jacobian': None}, 2: {'inputs': {'x': array([2.])}, 'outputs': {'y': array([3.])}, 'jacobian': None}}
Get last cached data¶
It is also possible to display the last entry cached, for the inputs and the outputs.
print(cache.get_last_cached_inputs())
print(cache.get_last_cached_outputs())
Out:
{'x': array([2.])}
{'y': array([3.])}
Clear the cache¶
It is also possible to clear the cache, which removes all the data which has been stored so far in the HDF5 file.
cache.clear()
print(cache)
Out:
Name: node1
Type: HDF5Cache
Tolerance: 0.0
Input names: None
Output names: None
Length: 0
HDF file path my_cache.hdf5
HDF node path node1
Total running time of the script: ( 0 minutes 0.041 seconds)