Refactor report generation to handle per-instrument residual correlation and improve error logging (3a9af7ac) · Commits · Gaetano Scandariato / PyAETNA

PyAETNA/planet_phys.py

+8 −1

Changes for PyAETNA/planet_phys.py: 8 added lines, 1 removed line.
Original line number	Diff line number	Diff line
		@@ -2064,11 +2064,18 @@ def _render_corner_groups(pdf, corner_groups, plModel, num_chains, log_func, der
		valid_params.append(p)
		else:
		# It's fixed, add to notes
		# Handle case where arr might be a scalar (float) instead of array
		if hasattr(arr, 'flatten'):
		val = arr.flatten()[0] if np.size(arr) > 0 else 0.0
		else:
		val = float(arr) if np.size(arr) > 0 else 0.0
		fixed_notes.append(f"{p} = {val:.4g}")

		# Filter samples to only include valid parameters (with variation)
		valid_samples_dict = {p: samples_dict[p] for p in valid_params if p in samples_dict}

		fig = plot_corner(
		group['samples'], group['params'],
		valid_samples_dict, valid_params,
		truths=group['truths'],
		title=group['title'],
		plModel=plModel,

PyAETNA/reporting/pdf_report.py

+24 −19

Changes for PyAETNA/reporting/pdf_report.py: 24 added lines, 19 removed lines.
Original line number	Diff line number	Diff line
		@@ -647,25 +647,6 @@ def generate_report(pickle_path, output_pdf, log_file=None, config_file=None):
		pdf.savefig(fig)
		plt.close(fig)

		# ── 1b. Per-instrument residual correlation (all visits combined, colored by visit) ─
		# After showing individual per-visit correlation plots, add one page showing
		# all visits for this instrument with colors distinguishing each visit.
		inst_mask_full = instrument_full == inst_id
		if _do_per_visit and np.sum(inst_mask_full) >= 10:
		inst_visits = [v for v in visits_to_plot
		if np.any((visit_arr == v) & (instrument_arr == inst_id))]
		# Only show this combined plot if the instrument has multiple visits with data
		if len(inst_visits) > 1:
		if hasattr(plData, 'dBasis') and len(plData.dBasis) > 0:
		_log(f" - Per-instrument residual correlation (all {len(inst_visits)} visits): {inst_name}")
		fig = plot_residuals_vs_dbasis(plData, residuals_full_unsorted, plModel=plModel,
		visit_to_plot=None,
		instrument_to_plot=inst_id,
		title=f'Residuals vs. dBasis Variables (All Visits) - {inst_name}')
		if fig is not None:
		pdf.savefig(fig)
		plt.close(fig)

		# ── 2. Per-instrument best-fit model (all visits combined) ───
		try:
		_log(f" - Per-instrument best-fit {data_type_label}: {inst_name}")
		@@ -678,6 +659,9 @@ def generate_report(pickle_path, output_pdf, log_file=None, config_file=None):
		plt.close(fig)
		except Exception as e:
		_log(f"WARNING: failed to generate per-instrument plot for {inst_name}: {e}")
		import traceback
		for line in traceback.format_exc().split('\n'):
		_log(f" {line}")
		fig = plot_models(plData, plModel, best_params, param_config,
		samples_dict=samples,
		instrument_to_plot=inst_id, show_gp=True, log_func=_log,
		@@ -706,6 +690,27 @@ def generate_report(pickle_path, output_pdf, log_file=None, config_file=None):
		pdf.savefig(fig)
		plt.close(fig)

		# ── 1b. Per-instrument residual correlation (all visits combined, colored by visit) ─
		# After showing individual per-visit correlation plots, add one page showing
		# all visits for this instrument with colors distinguishing each visit.
		inst_mask_full = instrument_full == inst_id
		print(_do_per_visit)
		print(np.sum(inst_mask_full))
		if _do_per_visit and np.sum(inst_mask_full) >= 10:
		inst_visits = [v for v in visits_to_plot
		if np.any((visit_arr == v) & (instrument_arr == inst_id))]
		# Only show this combined plot if the instrument has multiple visits with data
		if len(inst_visits) > 1:
		if hasattr(plData, 'dBasis') and len(plData.dBasis) > 0:
		_log(f" - Per-instrument residual correlation (all {len(inst_visits)} visits): {inst_name}")
		fig = plot_residuals_vs_dbasis(plData, residuals_full_unsorted, plModel=plModel,
		visit_to_plot=None,
		instrument_to_plot=inst_id,
		title=f'Residuals vs. dBasis Variables (All Visits) - {inst_name}')
		if fig is not None:
		pdf.savefig(fig)
		plt.close(fig)

		# Noise budget summary: per-instrument (and per-visit when jitter scope is per_visit).
		# Shows median σ_orig, median jitter contribution, and residuals RMS side by side
		# so the reader can see at a glance how much of the noise floor comes from the

PyAETNA/reporting/periodogram_plots.py

+1 −0

Changes for PyAETNA/reporting/periodogram_plots.py: 1 added line, 0 removed lines.
Original line number	Diff line number	Diff line
		@@ -25,6 +25,7 @@ def _log(msg, level='INFO'):
		logger._log(msg, level=level)

		from .plot_model_helpers import _compute_planet_model_for_plotting
		from .corner_plot import _get_distinct_colors


		def plot_residuals_histogram(residuals, dy, title='Residuals Distribution', figsize=(8, 5)):