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"""Runs RAT from the MATLAB API."""
import json
import tempfile
import warnings
from pathlib import Path
import numpy as np
from ..events import EventTypes, PlotEventData, ProgressEventData, notify
from ..outputs import Results
from ..project import Project
from ..wrappers import MatlabWrapper
RUNNER = """function executeRAT()
cur_dir = pwd;
cd('{rat_path}');
addPaths;
cd(cur_dir);
project = jsonToProject('{project}');
controls = jsonToControls('{control}');
customControls = customControl();
customControls.update(controls);
customControls.filePath = '{ipc_path}';
for i=1:project.customFile.rowCount
addpath(project.customFile.varTable{{i, 5}});
end
eventManager.register(eventTypes.Message, @(x) logger('{msg_log_path}', x));
eventManager.register(eventTypes.Progress, @(x) logger('{progress_log_path}', x));
eventManager.register(eventTypes.Plot, @(x) logger('{plot_log_path}', x));
global RAT_PROGRESS_UPDATE_FREQ RAT_PROGRESS_UPDATE_COUNT
RAT_PROGRESS_UPDATE_FREQ = {progress_event_freq};
RAT_PROGRESS_UPDATE_COUNT = -1;
[project, results] = RAT(project, customControls);
projectToJson(project, '{project}');
resultsToJson(results, '{result}');
eventManager.clear();
close all
end
"""
CONTROL = """classdef customControl < controlsClass
properties(Hidden = true)
filePath = ''
end
methods
function update(obj, controls)
propNames = properties(controls);
for i = 1:length(propNames)
obj.(propNames{i}) = controls.(propNames{i});
end
end
function path = getIPCFilePath(obj)
path = obj.filePath;
end
end
end
"""
LOGGER = """function logger(logPath, data)
if isstruct(data)
entry = plotDataToJson(data);
elseif iscell(data)
global RAT_PROGRESS_UPDATE_FREQ RAT_PROGRESS_UPDATE_COUNT;
RAT_PROGRESS_UPDATE_COUNT = RAT_PROGRESS_UPDATE_COUNT + 1;
if rem(RAT_PROGRESS_UPDATE_COUNT, RAT_PROGRESS_UPDATE_FREQ) ~= 0
return
end
entry = [data{1}, ',', num2str(data{2})];
else
entry = strip(data, 'right');
end
fid = fopen(logPath, "a");
cleanup = onCleanup(@() fclose(fid));
fprintf(fid, "%s\\n", entry);
end
function encoded = plotDataToJson(data)
% Encodes the results into a json file...
tmpResults = struct();
for fn = fieldnames(data)'
tmpResults.(fn{1}) = data.(fn{1});
end
tmpResults.reflectivity = correctCellArray(tmpResults.reflectivity);
tmpResults.shiftedData = correctCellArray(tmpResults.shiftedData);
tmpResults.sldProfiles = makeCellJson(tmpResults.sldProfiles);
tmpResults.resampledLayers = makeCellJson(tmpResults.resampledLayers);
encoded = jsonencode(tmpResults,ConvertInfAndNaN=false);
encoded = strrep(encoded, ']"', ']');
encoded = strrep(encoded, '"[', '[');
end
function outputArray = makeCellJson(cellArray)
% The jsonencode function flattens 2d cell arrays this is a workaround to
% avoid flattening by converting to a string array with is not flattened.
[row, col] = size(cellArray, [1, 2]);
outputArray = strings([row, col]);
for i=1:row
for j=1:col
entry = cellArray{i, j};
if size(entry, 1) == 1
entry = {entry};
end
if col == 1
entry = {entry};
end
outputArray(i, j) = jsonencode(entry);
end
end
if row == 1
outputArray = {outputArray};
end
end
function cellArray = correctCellArray(cellArray)
% Corrects array with single row so its written as 2D array in json
[row, col] = size(cellArray, [1, 2]);
for i=1:row
for j=1:col
if size(cellArray{i, j}, 1) == 1
cellArray{i, j} = {cellArray{i, j}};
end
end
end
end
"""
def run_matlab_directly(
project, controls, matlab_rat_path, ipc_path="", stdout=None, stderr=None, progress_event_freq=10
):
"""Run User provided MATLAB RAT for the given project and controls inputs.
Parameters
----------
project : RAT.Project or dict
The project model (or equivalent json dict), which defines the physical system under study.
controls : RAT.Controls or dict
The controls model (or equivalent json dict), which defines algorithmic properties.
matlab_rat_path : str
The path to MATLAB RAT folder.
ipc_path : str, optional
IPC path for MATLAB to use.
stdout : io.TextIOBase, optional
Text stream for MATLAB console output.
stderr : io.TextIOBase, optional
Text stream for MATLAB console error output.
progress_event_freq : int, default: 10
Update frequency of the progress event.
"""
if MatlabWrapper.loader is None:
raise ImportError(MatlabWrapper.loader_error_message) from None
engine = MatlabWrapper.loader.result()
with tempfile.TemporaryDirectory() as tmp:
project_file = Path(tmp, "project.json")
control_file = Path(tmp, "controls.json")
result_file = Path(tmp, "results.json")
runner_file = Path(tmp, "executeRAT.m")
custom_controls_file = Path(tmp, "customControl.m")
msg_log_file = Path(tmp, "runner_msg_log.txt")
progress_log_file = Path(tmp, "runner_progress_log.txt")
plot_log_file = Path(tmp, "runner_plot_log.txt")
Path(tmp, "logger.m").write_text(LOGGER)
with open(custom_controls_file, "w") as f:
f.write(CONTROL)
with open(runner_file, "w") as f:
f.write(
RUNNER.format(
project=project_file,
control=control_file,
result=result_file,
rat_path=matlab_rat_path,
ipc_path=ipc_path,
msg_log_path=msg_log_file,
progress_log_path=progress_log_file,
plot_log_path=plot_log_file,
progress_event_freq=progress_event_freq,
)
)
controls.save(control_file) if not isinstance(controls, dict) else control_file.write_text(json.dumps(controls))
with warnings.catch_warnings(): # Avoid warning about relative paths
warnings.simplefilter("ignore")
project.save(project_file) if not isinstance(project, dict) else project_file.write_text(
json.dumps(project)
)
engine.addpath(tmp, nargout=0)
future = engine.executeRAT(nargout=0, stdout=stdout, stderr=stderr, background=True)
msg_cur_line = 0
plot_cur_line = 0
progress_cur_line = 0
while not future.done():
if msg_log_file.exists():
with open(msg_log_file, encoding="utf-8") as handle:
handle.seek(msg_cur_line)
text = handle.read()
msg_cur_line = handle.tell()
if text:
notify(EventTypes.Message, text)
if progress_log_file.exists():
with open(progress_log_file, encoding="utf-8") as handle:
handle.seek(progress_cur_line)
lines = handle.readlines()
progress_cur_line = handle.tell()
if lines:
msg, percent = lines[-1].strip().rsplit(",", 1)
progress_data = ProgressEventData()
progress_data.message = msg
progress_data.percent = float(percent)
notify(EventTypes.Progress, progress_data)
if plot_log_file.exists():
with open(plot_log_file, encoding="utf-8") as handle:
handle.seek(plot_cur_line)
lines = handle.readlines()
plot_cur_line = handle.tell()
if lines:
plot_data = PlotEventData()
plot_json = json.loads(lines[-1])
plot_data.modelType = plot_json["modelType"]
plot_data.reflectivity = [np.array(ref) for ref in plot_json["reflectivity"]]
plot_data.shiftedData = [np.array(sd) for sd in plot_json["shiftedData"]]
plot_data.sldProfiles = [
[np.array(prof) for prof in profiles] for profiles in plot_json["sldProfiles"]
]
plot_data.resampledLayers = [
[np.array(lay) for lay in layers] for layers in plot_json["resampledLayers"]
]
plot_data.dataPresent = plot_json["dataPresent"]
plot_data.subRoughs = plot_json["subRoughs"]
plot_data.resample = plot_json["resample"]
plot_data.contrastNames = plot_json["contrastNames"]
notify(EventTypes.Plot, plot_data)
engine.rmpath(tmp, nargout=0)
if future.result() is not None:
raise RuntimeError(future.result())
project = Project.load(project_file)
results = Results.load(result_file)
return project, results
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