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.. jupyter-execute::
:hide-code:
import set_working_directory
Writing tabular data
--------------------
With the ``write_tabular`` app, ``cogent3`` "TabularTypes" (``Table``, ``DictArray``, ``DistanceMatrix``) are supported for writing to disk.
Let's generate a ``cogent3`` ``Table`` to use in the examples below. One way to do that is by applying the ``tabulate_stats`` app to a model result.
.. jupyter-execute::
:raises:
from cogent3 import get_app
# load alignment
load_aligned_app = get_app("load_aligned", moltype="dna")
aln = load_aligned_app("data/primate_brca1.fasta")
# fit GN model
gn_model_app = get_app("model", "GN", tree="data/primate_brca1.tree")
model_result = gn_model_app(aln)
# tabulate the model result
tabulator = get_app("tabulate_stats")
model_result_tab = tabulator(model_result)
motif_params = model_result_tab["motif params"]
print(type(motif_params))
motif_params
Writing a CSV file
^^^^^^^^^^^^^^^^^^
To write in CSV format, we create the ``write_tabular`` app with ``format="csv"``.
.. jupyter-execute::
:hide-code:
from tempfile import TemporaryDirectory
tmpdir = TemporaryDirectory(dir=".")
path_to_dir = tmpdir.name
.. jupyter-execute::
:raises:
from cogent3 import get_app, open_data_store
out_dstore = open_data_store(path_to_dir, mode="w", suffix="csv")
write_tabular_app = get_app("write_tabular", data_store=out_dstore, format="csv")
write_tabular_app(motif_params, identifier="gn_model_results.csv")
Writing a TSV file
^^^^^^^^^^^^^^^^^^
To write in TSV format, we create the ``write_tabular`` app with ``format="tsv"``.
.. jupyter-execute::
:hide-code:
from tempfile import TemporaryDirectory
tmpdir = TemporaryDirectory(dir=".")
path_to_dir = tmpdir.name
.. jupyter-execute::
:raises:
from cogent3 import get_app, open_data_store
out_dstore = open_data_store(path_to_dir, mode="w", suffix="tsv")
write_tabular_app = get_app("write_tabular", data_store=out_dstore, format="tsv")
write_tabular_app(motif_params, identifier="gn_model_results.tsv")
Using ``write_tabular`` in a composed process
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Instead of applying the apps sequentially as above, we can add apps into a composed process, and apply the process to a data store. In this example, we define a process that calculates an unaligned distance measure between sequences, writing these estimated distances to a tsv file.
.. jupyter-execute::
:hide-code:
from tempfile import TemporaryDirectory
tmpdir = TemporaryDirectory(dir=".")
path_to_dir = tmpdir.name
.. jupyter-execute::
:raises:
from cogent3 import get_app, open_data_store
loader = get_app("load_unaligned", moltype="dna")
jdist = get_app("jaccard_dist")
out_dstore = open_data_store(path_to_dir, mode="w", suffix="tsv")
writer = get_app("write_tabular", data_store=out_dstore, format="tsv")
process = loader + jdist + writer
in_dstore = open_data_store("data", suffix="fasta", mode="r", limit=2)
result = process.apply_to(in_dstore)
result.describe
.. tip:: When running this code on your machine, remember to replace ``path_to_dir`` with an actual directory path.
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