From 1bf003eb0bd0bbbfa1c43d75a0b2752871071506 Mon Sep 17 00:00:00 2001
From: Tobias Meisel <tobias.meisel@ufz.de>
Date: Wed, 27 Mar 2024 14:57:15 +0100
Subject: [PATCH] [logparser] Documentation - changed headings and line breaks
---
.../howto_logparser/plot_logparser_analyses.py | 14 ++++++--------
ogstools/logparser/common_ogs_analyses.py | 10 ++++++----
2 files changed, 12 insertions(+), 12 deletions(-)
diff --git a/docs/examples/howto_logparser/plot_logparser_analyses.py b/docs/examples/howto_logparser/plot_logparser_analyses.py
index 66dc4ef10..339320751 100644
--- a/docs/examples/howto_logparser/plot_logparser_analyses.py
+++ b/docs/examples/howto_logparser/plot_logparser_analyses.py
@@ -40,8 +40,8 @@ df_records = pd.DataFrame(records)
df_log = fill_ogs_context(df_records)
# %%
-# Iterations per time step
-# ------------------------
+# Analysis of iterations per time step
+# ------------------------------------
# Please see explanation in logparser
# :ref:`sphx_glr_auto_examples_howto_logparser_plot_logparser_intro.py`.
# (Section: Use predefined analyses)
@@ -52,8 +52,8 @@ df_ts_it # noqa: B018
# %%
-# Performance in separate parts by time step
-# ---------------------------------------------
+# Analysis of computational efficiency by time step
+# -------------------------------------------------
# The resulting table presents the performance metrics for separate parts of the simulation,
# organized by time step. Is uses :py:mod:`ogstools.logparser.analysis_time_step`.
# Each row corresponds to a specific time step, displaying metrics such
@@ -66,8 +66,6 @@ df_ts = df_ts.loc[0]
# - see advanced
df_ts # noqa: B018
# %%
-# Performance of in separate parts by time step - plot
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# We select only some metrics (3) and use pandas plot function.
df_ts[["assembly_time", "dirichlet_time", "linear_solver_time"]].plot(
logy=True, grid=True
@@ -85,8 +83,8 @@ analysis_convergence_newton_iteration(df_log)
# %%
-# Staggered
-# ---------
+# Staggered - Analysis of convergence criteria - Newton iterations
+# ----------------------------------------------------------------
# The resulting table provides convergence criteria for staggered coupled processes,
# Each row represents convergence metrics such as `global component norm |x|`, `change of global component norm |dx|` (change between 2 iteration of non linear solver)
# and `relative change of global component |dx|/|x|` at different time steps and coupling
diff --git a/ogstools/logparser/common_ogs_analyses.py b/ogstools/logparser/common_ogs_analyses.py
index 1ae1bd007..7737884b5 100644
--- a/ogstools/logparser/common_ogs_analyses.py
+++ b/ogstools/logparser/common_ogs_analyses.py
@@ -206,11 +206,13 @@ def fill_ogs_context(df_raw_log: pd.DataFrame) -> pd.DataFrame:
Pandas documentation : https://pandas.pydata.org/pandas-docs/stable/user_guide/
Notes:
- Some logs do not contain information about time_step and iteration. The information must be collected by context (by surrounding log lines from same mpi_process)
- Logs are grouped by mpi_process to get only surrounding log lines from same mpi_process
+ Some logs do not contain information about time_step and iteration. The
+ information must be collected by context (by surrounding log lines from same mpi_process).
+ Logs are grouped by mpi_process to get only surrounding log lines from same mpi_process.
There are log lines that give the current time step (when time step starts).
- It can be assumed that in all following lines belong to this time steps, until next collected value of time step
- Some columns that contain actual integer values are converted to float
+ It can be assumed that in all following lines belong to this time steps, until next
+ collected value of time step.
+ Some columns that contain actual integer values are converted to float.
See https://pandas.pydata.org/pandas-docs/stable/user_guide/integer_na.html
ToDo list of columns with integer values are known from regular expression
--
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