From bf4d03f3693aa90c99e9048cde7a417bd056fb77 Mon Sep 17 00:00:00 2001
From: Florez Ospina Juan Felipe <juan.florez-ospina@psi.ch>
Date: Thu, 2 Nov 2023 15:49:35 +0100
Subject: [PATCH] Added output_files' folder, environment.yml file, and jupyter
 notebook demo on how to create and visualize hdf5 files.

---
 demo_create_and_visualize_hdf5_file.ipynb | 113 ++++++++++++++++++++++
 environment.yml                           |  13 +++
 2 files changed, 126 insertions(+)
 create mode 100644 demo_create_and_visualize_hdf5_file.ipynb
 create mode 100644 environment.yml

diff --git a/demo_create_and_visualize_hdf5_file.ipynb b/demo_create_and_visualize_hdf5_file.ipynb
new file mode 100644
index 0000000..0ce8a0f
--- /dev/null
+++ b/demo_create_and_visualize_hdf5_file.ipynb
@@ -0,0 +1,113 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import hdf5_lib as h5lib\n",
+    "import os\n",
+    "\n",
+    "# define input file directory\n",
+    "\n",
+    "input_file_path = './input_files\\\\BeamTimeMetaData.h5'\n",
+    "output_dir_path = './output_files'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Read the above specified input_file_path as a dataframe. \n",
+    "\n",
+    "Since we know this file was created from a Thorsten Table's format, we can use h5lib.read_mtable_as_dataframe() to read it.\n",
+    "\n",
+    "Then, we rename the name column as filename, as this is the column's name use to idenfify files in subsequent functions.\n",
+    "Also, we add to the dataframe a few categorical columns to be used as grouping variables when creating the hdf5 file's group hierarchy. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read BeamTimeMetaData.h5, containing Thorsten's Matlab Table\n",
+    "input_data_df = h5lib.read_mtable_as_dataframe(input_file_path)\n",
+    "\n",
+    "# Preprocess Thorsten's input_data dataframe so that i can be used to create a newer .h5 file\n",
+    "# under certain grouping specificiations.\n",
+    "input_data_df = input_data_df.rename(columns = {'name':'filename'})\n",
+    "input_data_df = h5lib.augment_with_filenumber(input_data_df)\n",
+    "input_data_df = h5lib.augment_with_filetype(input_data_df)\n",
+    "input_data_df = h5lib.split_sample_col_into_sample_and_data_quality_cols(input_data_df)\n",
+    "input_data_df['lastModifiedDatestr'] = input_data_df['lastModifiedDatestr'].astype('datetime64[s]')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define grouping functions to be passed into create_hdf5_file function. These can also be set\n",
+    "# as strings refering to categorical columns in input_data_df.\n",
+    "\n",
+    "test_grouping_funcs = True\n",
+    "if test_grouping_funcs:\n",
+    "    group_by_sample = lambda x : h5lib.group_by_df_column(x,'sample')\n",
+    "    group_by_type = lambda x : h5lib.group_by_df_column(x,'filetype')\n",
+    "    group_by_filenumber = lambda x : h5lib.group_by_df_column(x,'filenumber')\n",
+    "else:\n",
+    "    group_by_sample = 'sample'\n",
+    "    group_by_type = 'filetype'\n",
+    "    group_by_filenumber = 'filenumber'\n",
+    "\n",
+    "output_filename = 'test.h5'\n",
+    "\n",
+    "h5lib.create_hdf5_file(os.path.join(output_dir_path,output_filename),\n",
+    "                       input_data_df, 'top-down', \n",
+    "                       group_by_funcs = [group_by_sample, group_by_type, group_by_filenumber]\n",
+    "                       )\n",
+    "\n",
+    "annotation_dict = {'Campaign name': 'SLS-Campaign-2023',\n",
+    "                    'Users':'Thorsten, Luca, Zoe',\n",
+    "                    'Startdate': str(input_data_df['lastModifiedDatestr'].min()),\n",
+    "                    'Enddate': str(input_data_df['lastModifiedDatestr'].max())\n",
+    "                    }\n",
+    "h5lib.annotate_root_dir('test.h5',annotation_dict)\n",
+    "\n",
+    "h5lib.display_group_hierarchy_on_a_treemap('test.h5')\n",
+    "\n",
+    "print(':)')\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "test_atmos_chem_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/environment.yml b/environment.yml
new file mode 100644
index 0000000..c9009cc
--- /dev/null
+++ b/environment.yml
@@ -0,0 +1,13 @@
+name: test_atmos_chem_env
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.11
+  - jupyter
+  - numpy
+  - pandas
+  - matplotlib
+  - plotly=5.18
+  - h5py=3.10
+  - pybis=1.35