"""Simulation results data encapsulation, for PyBERT.
Original Author: David Banas <capn.freako@gmail.com>
Original Date: 9 May 2017
This Python script provides a data structure for encapsulating the
simulation results data of a PyBERT instance. It was first
created, as a way to facilitate easier pickling, so that a particular
result could be saved and later restored, as a reference waveform.
Copyright (c) 2017 by David Banas; All rights reserved World wide.
"""
import pickle
from pathlib import Path
from typing import Union
from chaco.api import ArrayPlotData
RESULTS_FILEDIALOG_WILDCARD = "*.pybert_data"
"""This sets the supported file types in the GUI's save-as or loading dialog."""
[docs]
class PyBertData:
"""PyBERT simulation results data encapsulation class.
This class is used to encapsulate that subset of the results data
for a PyBERT instance, which is to be saved when the user clicks the
"Save Results" button.
"""
_item_names = [
"chnl_h",
"tx_out_h",
"ctle_out_h",
"dfe_out_h",
"chnl_s",
"tx_s",
"ctle_s",
"dfe_s",
"tx_out_s",
"ctle_out_s",
"dfe_out_s",
"chnl_p",
"tx_out_p",
"ctle_out_p",
"dfe_out_p",
"chnl_H",
"tx_H",
"ctle_H",
"dfe_H",
"tx_out_H",
"ctle_out_H",
"dfe_out_H",
"tx_out",
]
def __init__(self, the_PyBERT, date_created: str, version: str):
"""Copy just that subset of the supplied PyBERT instance's 'plotdata'
attribute, which should be saved during pickling."""
plotdata = the_PyBERT.plotdata
the_data = ArrayPlotData()
for item_name in self._item_names:
the_data.set_data(item_name, plotdata.get_data(item_name))
self.the_data = the_data
# Generic Information
self.date_created = date_created
self.version = version
[docs]
def save(self, filepath: Path):
"""Save all of the plot data out to a file.
Args:
filepath: The full filepath including the extension to save too.
"""
with open(filepath, "wb") as the_file:
pickle.dump(self, the_file)
# pylint: disable=too-many-branches
[docs]
@staticmethod
def load_from_file(filepath: Union[str, Path], pybert):
"""Recall all the results from a file and load them as reference plots.
Confirms that the file actually exists and attempts to load back the
graphs as reference plots in pybert.
Args:
filepath: The full filepath including the extension to save too.
pybert: instance of the main app
"""
filepath = Path(filepath) # incase a string was passed convert to a path.
if not filepath.exists():
raise FileNotFoundError(f"{filepath} does not exist.")
# Right now the loads deserialize back into a `PyBertData` class.
with open(filepath, "rb") as the_file:
user_results = pickle.load(the_file)
if not isinstance(user_results, PyBertData):
raise ValueError("The data structure read in is NOT of type: ArrayPlotData!")
# Load the reference plots.
for prop, value in user_results.the_data.arrays.items():
pybert.plotdata.set_data(prop + "_ref", value)
# Add reference plots, if necessary.
# - time domain
for container, suffix, has_both in [
(pybert.plots_h.component_grid.flat, "h", False),
(pybert.plots_s.component_grid.flat, "s", True),
(pybert.plots_p.component_grid.flat, "p", False),
]:
if "Reference" not in container[0].plots:
(ix, prefix) = (0, "chnl")
item_name = prefix + "_" + suffix + "_ref"
container[ix].plot(("t_ns_chnl", item_name), type="line", color="darkcyan", name="Inc_ref")
for ix, prefix in [(1, "tx"), (2, "ctle"), (3, "dfe")]:
item_name = prefix + "_out_" + suffix + "_ref"
container[ix].plot(("t_ns_chnl", item_name), type="line", color="darkmagenta", name="Cum_ref")
if has_both:
for ix, prefix in [(1, "tx"), (2, "ctle"), (3, "dfe")]:
item_name = prefix + "_" + suffix + "_ref"
container[ix].plot(("t_ns_chnl", item_name), type="line", color="darkcyan", name="Inc_ref")
# - frequency domain
for container, suffix, has_both in [(pybert.plots_H.component_grid.flat, "H", True)]:
if "Reference" not in container[0].plots:
(ix, prefix) = (0, "chnl")
item_name = prefix + "_" + suffix + "_ref"
container[ix].plot(
("f_GHz", item_name), type="line", color="darkcyan", name="Inc_ref", index_scale="log"
)
for ix, prefix in [(1, "tx"), (2, "ctle"), (3, "dfe")]:
item_name = prefix + "_out_" + suffix + "_ref"
container[ix].plot(
("f_GHz", item_name),
type="line",
color="darkmagenta",
name="Cum_ref",
index_scale="log",
)
if has_both:
for ix, prefix in [(1, "tx"), (2, "ctle"), (3, "dfe")]:
item_name = prefix + "_" + suffix + "_ref"
container[ix].plot(
("f_GHz", item_name),
type="line",
color="darkcyan",
name="Inc_ref",
index_scale="log",
)