def hdfcaching():
"""Auto-cache/save results to HDF."""
import os
import tables as pt
from cgp.utils.hdfcache import Hdfcache
filename = "/home/jonvi/hdfcache.h5"
hdfcache = Hdfcache(filename)
pipeline = [hdfcache.cache(i) for i in gt2par, par2ph, ph2agg]
with hdfcache:
for i in genotypes:
for func in pipeline:
i = func(i)
with pt.openFile(filename) as f:
gt = f.root.gt2par.input[:]
agg = f.root.ph2agg.output[:]
summarize(gt, agg)
os.system("h5ls -r " + filename)
"""
Cache computations to HDF file for simple genotype-phenotype example.
Here, the line "ph = hdfcache.cache(ph)" is equivalent to the decorator syntax:
.. code-block:: none
@hdfcache.cache
def ph(...):
...
However, cgp.examples.simple.ph is left undecorated so we can illustrate
different tools for caching and parallelization.
"""
import os
from tempfile import gettempdir
from cgp.utils.hdfcache import Hdfcache
from cgp.examples.simple import * # @UnusedWildImport pylint: disable=W0614
if __name__ == "__main__":
hdfcache = Hdfcache(os.path.join(gettempdir(), "cgpdemo.h5"))
ph = hdfcache.cache(ph)
result = np.concatenate([ph(gt) for gt in gts]).view(np.recarray)
visualize(result)
