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.. jupyter-execute::
:hide-code:
import set_working_directory
.. _write_json:
Writing JSON Serialised Objects
-------------------------------
Using JSON, we can serialise ``cogent3`` objects to a file for easy storage and retrieval.
Create an example object to serialise
"""""""""""""""""""""""""""""""""""""
Let's create a ``LikelihoodFunction`` object to use in this example. It is generated from fitting the General Nucleotide (GN) model to an alignment of BRCA1 in primates.
.. jupyter-execute::
:hide-code:
from tempfile import TemporaryDirectory
tmpdir = TemporaryDirectory(dir=".")
path_to_dir = tmpdir.name
.. jupyter-execute::
:raises:
from cogent3 import get_app
# Load the alignment
load_aligned_app = get_app("load_aligned", moltype="dna", format="fasta")
aln = load_aligned_app("data/primate_brca1.fasta")
# Fit the GN model
gn_model_app = get_app("model", "GN", tree="data/primate_brca1.tree")
model_result = gn_model_app(aln)
model_result.lf
``write_json`` - writing JSON-serialised object to file
""""""""""""""""""""""""""""""""""""""""""""""""""""""""
Using the ``write_json`` app, we can write out the likelihood function as a JSON-serialised object, making it easy to retrieve the model parameters for future reference if required.
We need to provide the ``write_json`` app with a data store to which it will write. Optionally when we apply the app we can specify an identifier for the data, which will name the file.
.. jupyter-execute::
:raises:
from cogent3 import get_app, open_data_store
# Initialise the write_json app with a data store
out_dstore = open_data_store(path_to_dir, mode="w", suffix="json")
write_json_app = get_app("write_json", data_store=out_dstore)
write_json_app(model_result.lf, identifier="gn_params.json")
.. note:: Learn how to load a JSON serialised object in the :ref:`loading JSON serialised objects <load_json>` section!
.. tip:: When running this code on your machine, remember to replace ``path_to_dir`` with an actual directory path.
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