Add Examples: Peak Finding, Impedance

CHANGELOG.md

@@ -7,12 +7,24 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 ### Fixed
 - 
 
+### Changed
+- 
+
+### Added
+- 
+
+## [0.4.5] - 2021-05-07
+
+### Fixed
+- 
+
 ### Changed
 - [#40](https://github.com/bcliang/gamry-parser/pull/40) Change: GamryParser to_timestamp param #40
-- [#41](https://github.com/bcliang/gamry-parser/pull/40) Use tox as test runner
+- [#41](https://github.com/bcliang/gamry-parser/pull/41) Use tox as test runner
 
 ### Added
 - [#42](https://github.com/bcliang/gamry-parser/pull/42) Update read_header function to support EFM140 data Files
+- [#43](https://github.com/bcliang/gamry-parser/pull/43) Add Examples: Peak Finding, Impedance
 
 ## [0.4.4] - 2021-02-28
 

demo/notebook_cyclicvoltammetry.ipynb

@@ -30,10 +30,14 @@
         "import matplotlib.pyplot as plt\n",
         "\n",
         "try:\n",
-        "  import gamry_parser as parser\n",
+        "    import gamry_parser\n",
         "except:\n",
-        "  !pip install -q --upgrade gamry-parser\n",
-        "  import gamry_parser as parser\n",
+        "    subprocess.run(\n",
+        "        [\"pip\", \"install\", \"gamry-parser\"], \n",
+        "        encoding=\"utf-8\", \n",
+        "        shell=False)\n",
+        "finally:\n",
+        "    import gamry_parser\n",
         "\n",
         "p = parser.CyclicVoltammetry()\n",
         "  \n",

demo/notebook_cyclicvoltammetry_peakdetect.ipynb

@@ -0,0 +1,253 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Gamry-Parser CyclicVoltammetry Peak Detection Example",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "YyeVlSYkhahF",
+        "cellView": "form"
+      },
+      "source": [
+        "#@title Imports, initial setup (Ctrl+F9 to run all)\n",
+        "import os\n",
+        "import re\n",
+        "import pandas as pd\n",
+        "import matplotlib.pyplot as plt\n",
+        "from scipy.signal import find_peaks\n",
+        "import copy\n",
+        "\n",
+        "try:\n",
+        "    import gamry_parser\n",
+        "except:\n",
+        "    subprocess.run(\n",
+        "        [\"pip\", \"install\", \"gamry-parser\"], \n",
+        "        encoding=\"utf-8\", \n",
+        "        shell=False)\n",
+        "finally:\n",
+        "    import gamry_parser\n",
+        "\n",
+        "gp = gamry_parser.CyclicVoltammetry()\n",
+        "\n",
+        "print('Done.')"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ZGoqracvk9q2",
+        "cellView": "form"
+      },
+      "source": [
+        "\"\"\"\n",
+        "### SCRIPT CONFIGURATION SETTINGS ###\n",
+        "\"\"\"\n",
+        "#@markdown **Experimental Setup**\n",
+        "\n",
+        "#@markdown Where should the notebook search for DTA files? Examples (using google colab):\n",
+        "#@markdown - Mounted google drive folder: `/content/drive/`\n",
+        "#@markdown - If uploading files manually, : `/content/`).\n",
+        "\n",
+        "data_path = \"/content/\" #@param {type:\"string\"}\n",
+        "\n",
+        "#@markdown Filter which files we want to analyze\n",
+        "file_pattern = \"Search-For-Text\" #@param {type:\"string\"}\n",
+        "\n",
+        "#@markdown Extract trace labels from file name (e.g. `[17:].lower()` => drop the first 17 characters from the filename and convert to lowercase). The trace labels are used for category labeling (and plot legends)\n",
+        "file_label_xform = \"[51:]\" #@param {type:\"string\"}\n",
+        "\n",
+        "# create a \"results\" dataframe to contain the values we care about\n",
+        "data_df = pandas.DataFrame()\n",
+        "settings_df = pandas.DataFrame()\n",
+        "peaks_df = pandas.DataFrame()\n",
+        "\n",
+        "# identify files to process\n",
+        "files = [f for f in os.listdir(data_path) if \n",
+        "    os.path.splitext(f)[1].lower() == \".dta\" and\n",
+        "    len(re.findall(file_pattern.upper(), f.upper())) > 0\n",
+        "    ]\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "cellView": "form",
+        "id": "8MFNF2Qz6lef"
+      },
+      "source": [
+        "#@markdown **Process Data and Detect Peaks**\n",
+        "\n",
+        "#@markdown Which CV curves (cycle number) should be sampled? (`0` would select the first CV curve from each file)\n",
+        "curves_to_sample = \"0\" #@param {type:\"string\"}\n",
+        "curves_to_sample = [int(item.strip()) for item in curves_to_sample.split(\",\")]\n",
+        "\n",
+        "#@markdown Peak Detection: specify the peak detection parameters\n",
+        "peak_width_mV = 75 #@param {type:\"integer\"}\n",
+        "peak_height_nA =  25 #@param {type:\"integer\"}\n",
+        "peak_thresh_max_mV = 800 #@param {type:\"integer\"}\n",
+        "peak_thresh_min_mV = -100 #@param  {type:\"integer\"}\n",
+        "\n",
+        "# this method finds the row that has an index value closest to the desired time elapsed\n",
+        "def duration_lookup(df, elapsed):\n",
+        "    return df.index.get_loc(elapsed, method='nearest')\n",
+        "\n",
+        "# iterate through each DTA file\n",
+        "for index, file in enumerate(files):\n",
+        "    print(\"Checking File {}\".format(file))\n",
+        "\n",
+        "    label, ext = os.path.splitext(file)\n",
+        "    my_label = \"-\".join(eval(\"label{}\".format(file_label_xform)).strip().split())\n",
+        "\n",
+        "    # load the dta file using gamry parser\n",
+        "    gp.load(filename=os.path.join(data_path, file))\n",
+        "\n",
+        "    is_cv = gp.get_header().get(\"TAG\") == \"CV\"\n",
+        "    if not is_cv:\n",
+        "        # if the DTA file is a different experiment type, skip it and move to the next file.\n",
+        "        print(\"File `{}` is not a CV experiment. Skipping\".format(file))\n",
+        "        del files[index]  # remove invalid file from list\n",
+        "        continue\n",
+        "    \n",
+        "    # for each CV file, let's extract the relevant information\n",
+        "    cv = gamry_parser.CyclicVoltammetry(filename=os.path.join(data_path, file))\n",
+        "    cv.load()\n",
+        "    for curve_num in curves_to_sample:\n",
+        "        print(\"\\tProcessing Curve #{}\".format(curve_num))\n",
+        "        v1, v2 = cv.get_v_range()\n",
+        "        settings = pandas.DataFrame({\n",
+        "            \"label\": my_label,\n",
+        "            \"curves\": cv.get_curve_count(),\n",
+        "            \"v1_mV\": v1*1000,\n",
+        "            \"v2_mV\": v2*1000,\n",
+        "            \"rate_mV\": cv.get_scan_rate(),\n",
+        "        }, index=[0])\n",
+        "        settings_df = settings_df.append(settings)\n",
+        "\n",
+        "        data = copy.deepcopy(cv.get_curve_data(curve=curve_num))\n",
+        "        data.Im = data.Im*1e9\n",
+        "        data.Vf = data.Vf*1e3\n",
+        "        data[\"label\"] = my_label #\"{:03d}-{}\".format(index, curve_num)\n",
+        "\n",
+        "        data_df = data_df.append(data)\n",
+        "\n",
+        "        # find peaks in the data\n",
+        "        dV = cv.get_scan_rate()  # in mV\n",
+        "        peak_width = int(peak_width_mV/dV)\n",
+        "        peaks_pos, props_pos = find_peaks(\n",
+        "            data.Im, \n",
+        "            width=peak_width, \n",
+        "            distance=2*peak_width, \n",
+        "            height=peak_height_nA\n",
+        "        )\n",
+        "        peaks_neg, props_neg = find_peaks(\n",
+        "            -data.Im, \n",
+        "            width=peak_width, \n",
+        "            distance=2*peak_width, \n",
+        "            height=peak_height_nA\n",
+        "        )\n",
+        "        peaks = list(peaks_pos) + list(peaks_neg)\n",
+        "        # remove peaks that are out of min/max range\n",
+        "        peaks = [peak \n",
+        "                 for peak in peaks \n",
+        "                 if data.Vf.iloc[peak] >= peak_thresh_min_mV and data.Vf.iloc[peak] <= peak_thresh_max_mV]\n",
+        "\n",
+        "        # add detected peaks to aggregated peak dataframe\n",
+        "        peaks = data.iloc[peaks].sort_values(by=\"Vf\")\n",
+        "        peaks[\"index\"] = peaks.index\n",
+        "        peaks.reset_index(level=0, inplace=True)\n",
+        "        peaks_df = peaks_df.append(peaks)\n",
+        "        peaks_df = peaks_df[[\"label\", \"index\", \"Vf\", \"Im\"]]\n",
+        "        # print(\"\\tdetected peaks (mV)\", [int(peak) for peak in data.iloc[peaks].Vf.sort_values().tolist()])\n",
+        "\n",
+        "print(\"\\nFile Metadata\")\n",
+        "print(settings_df.to_string(index=False))\n",
+        "\n",
+        "print(\"\\nPeaks Detected\")\n",
+        "print(peaks_df.to_string(index=False))"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Ulne80RrpBrW",
+        "cellView": "form"
+      },
+      "source": [
+        "#@markdown **I-V plot**: Overlay the loaded CyclicVoltammetry Curves\n",
+        "\n",
+        "from plotly.subplots import make_subplots\n",
+        "import plotly.graph_objects as go\n",
+        "from plotly.colors import DEFAULT_PLOTLY_COLORS\n",
+        "\n",
+        "fig = make_subplots(rows=1, cols=1, shared_xaxes=True, vertical_spacing=0.02)\n",
+        "\n",
+        "for (index, exp_id) in enumerate(data_df.label.unique()):\n",
+        "    data = data_df.loc[data_df.label == exp_id]\n",
+        "    newTrace = go.Scatter(\n",
+        "        x=data.Vf,\n",
+        "        y=data.Im,\n",
+        "        mode='lines',\n",
+        "        name=exp_id,\n",
+        "        legendgroup=files[index],\n",
+        "        line=dict(color=DEFAULT_PLOTLY_COLORS[index]),\n",
+        "    )\n",
+        "    fig.add_trace(newTrace, row=1, col=1)\n",
+        "    peak = peaks_df.loc[peaks_df.label == exp_id]\n",
+        "    newTrace = go.Scatter(\n",
+        "        x=peak.Vf, y=peak.Im, \n",
+        "        mode=\"markers\", \n",
+        "        showlegend=False, \n",
+        "        marker=dict(size=12,\n",
+        "                    color=DEFAULT_PLOTLY_COLORS[index],\n",
+        "        )\n",
+        "    )\n",
+        "    fig.add_trace(newTrace, row=1, col=1)\n",
+        "\n",
+        "layout = {\n",
+        "    'title': {'text': 'Cyclic Voltammetry Overlay',\n",
+        "              'yanchor': 'top',\n",
+        "              'y': 0.95,\n",
+        "              'x': 0.5 },\n",
+        "    'xaxis': {\n",
+        "        'anchor': 'x',\n",
+        "        'title': 'voltage, mV'\n",
+        "    },\n",
+        "    'yaxis': {\n",
+        "        'title': 'current, nA',\n",
+        "        'type': 'linear'\n",
+        "        ''\n",
+        "    },\n",
+        "    'width': 1200,\n",
+        "    'height': 500,\n",
+        "    'margin': dict(l=30, r=20, t=60, b=20),\n",
+        "}\n",
+        "fig.update_layout(layout)\n",
+        "\n",
+        "config={\n",
+        "    'displaylogo': False,\n",
+        "    'modeBarButtonsToRemove': ['select2d', 'lasso2d', 'hoverClosestCartesian', 'toggleSpikelines','hoverCompareCartesian']\n",
+        "}\n",
+        "fig.show(config=config)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

demo/notebook_gamry_parser.ipynb

@@ -30,10 +30,14 @@
         "import matplotlib.pyplot as plt\n",
         "\n",
         "try:\n",
-        "  import gamry_parser as parser\n",
+        "    import gamry_parser\n",
         "except:\n",
-        "  !pip install -q --upgrade gamry-parser\n",
-        "  import gamry_parser as parser\n",
+        "    subprocess.run(\n",
+        "        [\"pip\", \"install\", \"gamry-parser\"], \n",
+        "        encoding=\"utf-8\", \n",
+        "        shell=False)\n",
+        "finally:\n",
+        "    import gamry_parser\n",
         "\n",
         "p = parser.GamryParser()\n",
         "  \n",
@@ -163,4 +167,4 @@
       "outputs": []
     }
   ]
-}
+}