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"""
.. _ref_use_local_data_example:

Bring a field's data locally to improve performance
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Reducing the number of calls to the server is key to improving
performance. Using the ``as_local_field`` option brings the data
from the server to your local machine where you can work on it.
When finished, you send the updated data back to the server
in one transaction.

"""

# Import necessary modules
from ansys.dpf import core as dpf
from ansys.dpf.core import examples, operators as ops

###############################################################################
# Create a model object to establish a connection with an
# example result file and then extract:
model = dpf.Model(examples.download_multi_stage_cyclic_result())
print(model)
mesh = model.metadata.meshed_region

###############################################################################
# Create the workflow
# ~~~~~~~~~~~~~~~~~~~~

###############################################################################
# Compute the stress principal invariants:
stress_op = ops.result.stress(data_sources=model.metadata.data_sources)
stress_op.inputs.requested_location.connect(dpf.locations.nodal)
stress_op.inputs.mesh_scoping.connect(mesh.nodes.scoping)

principal_op = ops.invariant.principal_invariants_fc(stress_op)
principal_stress_1 = principal_op.outputs.fields_eig_1()[0]
principal_stress_2 = principal_op.outputs.fields_eig_2()[0]
principal_stress_3 = principal_op.outputs.fields_eig_3()[0]

###############################################################################
# Manipulate data locally
# ~~~~~~~~~~~~~~~~~~~~~~~


###############################################################################
# This example goes over the fields, keeping the largest invariant value
# by node if the averaged value of invariants is large enough.
# Exploring data allows you to customize it to meet your needs.

node_scoping_ids = principal_stress_1.scoping.ids
threshold = 300000.0

field_to_keep = dpf.fields_factory.create_scalar_field(
    len(node_scoping_ids), location=dpf.locations.nodal
)

with field_to_keep.as_local_field() as f:
    with principal_stress_1.as_local_field() as s1:
        with principal_stress_2.as_local_field() as s2:
            with principal_stress_3.as_local_field() as s3:
                for i, id in enumerate(node_scoping_ids):
                    d1 = abs(s1.get_entity_data_by_id(id))
                    d2 = abs(s2.get_entity_data_by_id(id))
                    d3 = abs(s3.get_entity_data_by_id(id))
                    if (d1 + d2 + d3) / 3.0 > threshold:
                        d = max(d1, d2, d3)
                        f.append(d, id)

###############################################################################
# Plot result field
# ~~~~~~~~~~~~~~~~~


###############################################################################
# Plot the result field on the skin mesh:
mesh.plot(field_to_keep)

###############################################################################
# Plot initial invariants
# ~~~~~~~~~~~~~~~~~~~~~~~


###############################################################################
# Plot the initial invariants:

mesh.plot(principal_stress_1)
mesh.plot(principal_stress_2)
mesh.plot(principal_stress_3)