From 66c6e6c931500b84fe26496e0021f1ea5fb356b0 Mon Sep 17 00:00:00 2001
From: edufour <edouard.dufour@micro-ondes.ch>
Date: Thu, 29 Feb 2024 21:27:11 +0100
Subject: [PATCH] First processing steps

---
 data/__init__.py           |   3 +
 data/data_loading.py       |  54 ++++++++++++++
 data/data_processing.ipynb | 140 ++++++++++++++++++++-----------------
 data/data_processing.py    |  88 +++++++++++++++++++++++
 utils/df_utils.py          |   8 +++
 5 files changed, 228 insertions(+), 65 deletions(-)
 create mode 100644 data/__init__.py
 create mode 100644 data/data_loading.py
 create mode 100644 data/data_processing.py
 create mode 100644 utils/df_utils.py

diff --git a/data/__init__.py b/data/__init__.py
new file mode 100644
index 0000000..172004b
--- /dev/null
+++ b/data/__init__.py
@@ -0,0 +1,3 @@
+import pandas as pd
+from data_loading import *
+from data_processing import *
\ No newline at end of file
diff --git a/data/data_loading.py b/data/data_loading.py
new file mode 100644
index 0000000..2eefd2e
--- /dev/null
+++ b/data/data_loading.py
@@ -0,0 +1,54 @@
+import pandas as pd
+from utils.df_utils import *
+
+
+def load_raw_metadata() -> pd.DataFrame:
+    """
+    Load metadata.csv
+    :return:
+    """
+    with open("../data_raw/metadata.csv") as f:
+        return pd.read_csv(f, index_col="file")
+
+
+def load_raw_measure(filename: str) -> pd.DataFrame:
+    """
+    Load a given measure session
+    :param filename:
+    :return:
+    """
+    with open(f"../data_raw/{filename}") as f:
+        df_experiment = pd.DataFrame([x.split() for x in f.readlines()])
+        df_experiment.columns = df_experiment.iloc[0]
+        df_experiment = df_experiment[1:][["#Wave", "#Intensity"]].astype(float)
+    return df_experiment
+
+
+def get_raw_measure_with_metadata(file: pd.Series) -> tuple[pd.DataFrame, list[pd.DataFrame]]:
+    """
+    Load a given measure, slice it and give the corresponding metadata
+    :param file:
+    :return: dataframe containing the metadata with one row per sliced measure
+    :return: list of sliced measure dataframes
+    """
+    df_experiment = load_raw_measure(file.name)
+    sliced_experiments = slice_df(df_experiment, df_experiment[df_experiment["#Wave"].diff() > 0].index)
+    sliced_experiments = [exp.set_index("#Wave") for exp in sliced_experiments]
+    file = pd.DataFrame(file).transpose()
+    metadata = pd.DataFrame(file.loc[file.index.repeat(len(sliced_experiments))])
+    return metadata, sliced_experiments
+
+
+def load_data() -> tuple[pd.DataFrame, list[pd.DataFrame]]:
+    """
+    Load all the available data, slice it into individual measures and give the corresponding metadata
+    :return: dataframe containing the metadata with one row per sliced measure
+    :return: list of sliced measure dataframes
+    """
+    metadata, sliced_experiments = pd.DataFrame(), []
+    raw_metadata = load_raw_metadata()
+    for _, row in raw_metadata.iterrows():
+        temp_metadata, temp_sliced_experiments = get_raw_measure_with_metadata(row)
+        metadata = pd.concat([metadata, temp_metadata])
+        sliced_experiments.extend(temp_sliced_experiments)
+    return metadata, sliced_experiments
diff --git a/data/data_processing.ipynb b/data/data_processing.ipynb
index 6671bb9..e6f9d75 100644
--- a/data/data_processing.ipynb
+++ b/data/data_processing.ipynb
@@ -7,40 +7,31 @@
    "metadata": {
     "collapsed": true,
     "ExecuteTime": {
-     "end_time": "2024-02-26T18:00:51.600227Z",
-     "start_time": "2024-02-26T18:00:50.046904700Z"
+     "end_time": "2024-02-29T20:15:41.237366300Z",
+     "start_time": "2024-02-29T20:15:39.704235Z"
     }
    },
    "outputs": [],
    "source": [
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
+    "%matplotlib inline\n",
+    "from data import load_data, adjust_baseline, savitzky_golay\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "import random"
    ]
   },
   {
    "cell_type": "code",
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "                                                   strain  replica   phase  \\\nfile                                                                         \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...   A390      1.0  liquid   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...   A390      3.0  liquid   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...   A390      3.0  liquid   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...   A390      2.0   solid   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...   A390      2.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...   CHA0      3.0  liquid   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...   CHA0      3.0  liquid   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...   CHA0      1.0   solid   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...   CHA0      1.0   solid   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...   CHA0      NaN     NaN   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...   F113      NaN   liqui   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...   F113      NaN   liqui   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \n\n                                                    objective substrate  \\\nfile                                                                      \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...         50       alu   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...         50       alu   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \n\n                                                    laser_power[%]  grating  \\\nfile                                                                          \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...             100     1800   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...             100     1800   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \n\n                                                    exposition[sec]  \\\nfile                                                                  \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...               20   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...               20   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...               20   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...               20   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...               20   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \n\n                                                    confocalhigh  \\\nfile                                                               \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...          True   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...          True   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...          True   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...          True   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...          True   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \n\n                                                    accumulations  \nfile                                                               \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...              2  \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...              2  \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...              2  \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...              2  \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...              2  \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  ",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>strain</th>\n      <th>replica</th>\n      <th>phase</th>\n      <th>objective</th>\n      <th>substrate</th>\n      <th>laser_power[%]</th>\n      <th>grating</th>\n      <th>exposition[sec]</th>\n      <th>confocalhigh</th>\n      <th>accumulations</th>\n    </tr>\n    <tr>\n      <th>file</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>A390SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraliquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraliquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>A390</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round211 (2).txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round211.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0Liquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round (2).txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>CHA0</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2 (2).txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu(1).txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectra_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop1 (2).txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop1.txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid_50x_dried3_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop.txt</th>\n      <td>F113</td>\n      <td>NaN</td>\n      <td>liqui</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>NaN</td>\n      <td>liqui</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2 (2).txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "with open(\"../data_raw/metadata.csv\") as f:\n",
-    "    df_all_experiments = pd.read_csv(f, index_col=\"file\")\n",
-    "df_all_experiments"
+    "df_metadata, sliced_experiments = load_data()"
    ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-26T18:00:51.632216300Z",
-     "start_time": "2024-02-26T18:00:51.602923Z"
+     "end_time": "2024-02-29T20:15:42.730489300Z",
+     "start_time": "2024-02-29T20:15:41.246497600Z"
     }
    },
    "id": "8ad20a80c1220f67",
@@ -49,65 +40,83 @@
   {
    "cell_type": "code",
    "outputs": [
-    {
-     "data": {
-      "text/plain": "0                #X      #Y        #Wave    #Intensity\n1      14537.392021 -1316.1  1927.490234  34298.539063\n2      14537.392021 -1316.1  1925.943359  34948.273438\n3      14537.392021 -1316.1  1924.396484  34378.742188\n4      14537.392021 -1316.1  1922.849609  34778.796875\n5      14537.392021 -1316.1  1921.300781  34488.968750\n...             ...     ...          ...           ...\n30326  14577.392021 -1284.1   188.570313   9527.851563\n30327  14577.392021 -1284.1   186.636719   9477.843750\n30328  14577.392021 -1284.1   184.701172   9612.567383\n30329  14577.392021 -1284.1   182.765625   9742.063477\n30330  14577.392021 -1284.1   180.828125   9698.495117\n\n[30330 rows x 4 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>#X</th>\n      <th>#Y</th>\n      <th>#Wave</th>\n      <th>#Intensity</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1927.490234</td>\n      <td>34298.539063</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1925.943359</td>\n      <td>34948.273438</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1924.396484</td>\n      <td>34378.742188</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1922.849609</td>\n      <td>34778.796875</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1921.300781</td>\n      <td>34488.968750</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>30326</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>188.570313</td>\n      <td>9527.851563</td>\n    </tr>\n    <tr>\n      <th>30327</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>186.636719</td>\n      <td>9477.843750</td>\n    </tr>\n    <tr>\n      <th>30328</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>184.701172</td>\n      <td>9612.567383</td>\n    </tr>\n    <tr>\n      <th>30329</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>182.765625</td>\n      <td>9742.063477</td>\n    </tr>\n    <tr>\n      <th>30330</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>180.828125</td>\n      <td>9698.495117</td>\n    </tr>\n  </tbody>\n</table>\n<p>30330 rows × 4 columns</p>\n</div>"
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "with open(f\"../data_raw/{df_all_experiments.index[0]}\") as f:\n",
-    "    df_experiment = pd.DataFrame([x.split() for x in f.readlines()])\n",
-    "    df_experiment.columns = df_experiment.iloc[0]\n",
-    "    df_experiment = df_experiment[1:].astype(float)\n",
-    "df_experiment"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-26T18:05:49.594975900Z",
-     "start_time": "2024-02-26T18:05:49.527469Z"
-    }
-   },
-   "id": "4d6ba1f5360b6333",
-   "execution_count": 12
-  },
-  {
-   "cell_type": "code",
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "<Axes: >"
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
     {
      "data": {
       "text/plain": "<Figure size 640x480 with 1 Axes>",
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df_experiment[[\"#Wave\", \"#Intensity\"]].plot()"
+    "_ = sliced_experiments[random.randint(0, len(sliced_experiments))].plot()"
    ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-26T18:05:51.419517500Z",
-     "start_time": "2024-02-26T18:05:51.187293Z"
+     "end_time": "2024-02-29T20:15:42.907972600Z",
+     "start_time": "2024-02-29T20:15:42.732100500Z"
     }
    },
    "id": "1a9d17e12743f2bc",
-   "execution_count": 13
+   "execution_count": 3
+  },
+  {
+   "cell_type": "code",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "baselined_experiments = []\n",
+    "for exp in sliced_experiments:\n",
+    "    baselined_experiments.append(adjust_baseline(exp, scale = True))\n",
+    "    plt.plot(baselined_experiments[-1])"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-29T20:15:47.336829400Z",
+     "start_time": "2024-02-29T20:15:44.049249400Z"
+    }
+   },
+   "id": "31e370899b32dc7d",
+   "execution_count": 4
+  },
+  {
+   "cell_type": "code",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "smoothed_experiments = []\n",
+    "for exp in baselined_experiments:\n",
+    "    smoothed_experiments.append(savitzky_golay(exp.to_numpy(), 15, 7)[::-1])\n",
+    "    plt.plot(smoothed_experiments[-1])"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-29T20:20:27.093993600Z",
+     "start_time": "2024-02-29T20:20:25.247088400Z"
+    }
+   },
+   "id": "1104a63f751b0a33",
+   "execution_count": 17
   },
   {
    "cell_type": "code",
@@ -116,11 +125,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-26T18:00:52.236580Z",
-     "start_time": "2024-02-26T18:00:52.218164200Z"
+     "end_time": "2024-02-29T19:59:21.375365200Z",
+     "start_time": "2024-02-29T19:59:21.370298800Z"
     }
    },
-   "id": "ce858af586a1dce1"
+   "id": "6ca28a456c031f81",
+   "execution_count": 5
   }
  ],
  "metadata": {
diff --git a/data/data_processing.py b/data/data_processing.py
new file mode 100644
index 0000000..6f9c1b9
--- /dev/null
+++ b/data/data_processing.py
@@ -0,0 +1,88 @@
+from pybaselines import Baseline
+import numpy as np
+from math import factorial
+
+
+def calculate_baseline(measure):
+    baseline_fitter = Baseline(x_data=measure.index)
+    bkg_2, params_2 = baseline_fitter.iasls(measure["#Intensity"], lam=10, p=1e-2)
+    return bkg_2
+
+
+def adjust_baseline(measure, scale = False):
+    baseline = calculate_baseline(measure)
+    measure["#Intensity"] -= baseline
+    if scale:
+        measure["#Intensity"] /= baseline.max() - baseline.min()
+    return measure
+
+
+def savitzky_golay(y, window_size, order, deriv=0, rate=1):
+    r"""Smooth (and optionally differentiate) data with a Savitzky-Golay filter.
+    The Savitzky-Golay filter removes high frequency noise from data.
+    It has the advantage of preserving the original shape and
+    features of the signal better than other types of filtering
+    approaches, such as moving averages techniques.
+    Parameters
+    ----------
+    y : array_like, shape (N,)
+        the values of the time history of the signal.
+    window_size : int
+        the length of the window. Must be an odd integer number.
+    order : int
+        the order of the polynomial used in the filtering.
+        Must be less then `window_size` - 1.
+    deriv: int
+        the order of the derivative to compute (default = 0 means only smoothing)
+    Returns
+    -------
+    ys : ndarray, shape (N)
+        the smoothed signal (or it's n-th derivative).
+    Notes
+    -----
+    The Savitzky-Golay is a type of low-pass filter, particularly
+    suited for smoothing noisy data. The main idea behind this
+    approach is to make for each point a least-square fit with a
+    polynomial of high order over a odd-sized window centered at
+    the point.
+    Examples
+    --------
+    t = np.linspace(-4, 4, 500)
+    y = np.exp( -t**2 ) + np.random.normal(0, 0.05, t.shape)
+    ysg = savitzky_golay(y, window_size=31, order=4)
+    import matplotlib.pyplot as plt
+    plt.plot(t, y, label='Noisy signal')
+    plt.plot(t, np.exp(-t**2), 'k', lw=1.5, label='Original signal')
+    plt.plot(t, ysg, 'r', label='Filtered signal')
+    plt.legend()
+    plt.show()
+    References
+    ----------
+    .. [1] A. Savitzky, M. J. E. Golay, Smoothing and Differentiation of
+       Data by Simplified Least Squares Procedures. Analytical
+       Chemistry, 1964, 36 (8), pp 1627-1639.
+    .. [2] Numerical Recipes 3rd Edition: The Art of Scientific Computing
+       W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery
+       Cambridge University Press ISBN-13: 9780521880688
+    """
+
+    try:
+        window_size = np.abs(int(window_size))
+        order = np.abs(int(order))
+    except ValueError:
+        raise ValueError("window_size and order have to be of type int")
+    if window_size % 2 != 1 or window_size < 1:
+        raise TypeError("window_size size must be a positive odd number")
+    if window_size < order + 2:
+        raise TypeError("window_size is too small for the polynomials order")
+    order_range = range(order+1)
+    half_window = (window_size -1) // 2
+    # precompute coefficients
+    b = np.mat([[k**i for i in order_range] for k in range(-half_window, half_window+1)])
+    m = np.linalg.pinv(b).A[deriv] * rate**deriv * factorial(deriv)
+    # pad the signal at the extremes with
+    # values taken from the signal itself
+    firstvals = y[0] - np.abs( y[1:half_window+1][::-1] - y[0] )
+    lastvals = y[-1] + np.abs(y[-half_window-1:-1][::-1] - y[-1])
+    y = np.concatenate((firstvals, y, lastvals))
+    return np.convolve(m[::-1], y.T[0], mode='valid')
diff --git a/utils/df_utils.py b/utils/df_utils.py
new file mode 100644
index 0000000..a025d02
--- /dev/null
+++ b/utils/df_utils.py
@@ -0,0 +1,8 @@
+import pandas as pd
+
+def slice_df(df, slice_positions):
+    sliced_dfs = [df[:slice_positions[0]-1].copy(deep=True)]
+    for i in range(len(slice_positions)-1):
+        sliced_dfs.append(df[slice_positions[i]-1:slice_positions[i+1]-1].copy(deep=True))
+    sliced_dfs.append(df[slice_positions[-1]-1:].copy(deep=True))
+    return sliced_dfs
\ No newline at end of file