{ "cells": [ { "cell_type": "markdown", "id": "cca688da-ecff-4c16-95c3-df7c3585f06f", "metadata": {}, "source": [ "# alphatims" ] }, { "cell_type": "raw", "id": "3d02fe77-26a8-45dc-9056-078449b074a7", "metadata": { "editable": true, "raw_mimetype": "text/html", "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "\n", " \"Launch\n", "\n", "

" ] }, { "cell_type": "markdown", "id": "36e0c3b8-9a13-4aa9-8284-b9b181a46da8", "metadata": {}, "source": [ "## Install alphatims" ] }, { "cell_type": "code", "execution_count": 1, "id": "ff13c59a-c8fa-4342-83bd-b83380e5a0d1", "metadata": {}, "outputs": [], "source": [ "!pip install alphatims --quiet" ] }, { "cell_type": "markdown", "id": "5c907cc2-c11c-499a-8659-a36b02c3ac1e", "metadata": {}, "source": [ "## Download test data" ] }, { "cell_type": "code", "execution_count": 2, "id": "1816af2a-32f1-4967-9f71-351dd72bcb8a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "File 20201207_tims03_Evo03_PS_SA_HeLa_200ng_EvoSep_prot_DDA_21min_8cm_S1-C10_1_22476.d.zip downloaded successfully!\n", "File extracted to ./!\n", "Zip file 20201207_tims03_Evo03_PS_SA_HeLa_200ng_EvoSep_prot_DDA_21min_8cm_S1-C10_1_22476.d.zip removed.\n" ] } ], "source": [ "import requests\n", "import zipfile\n", "import os\n", "\n", "# # Define the URL and file name\n", "url = 'https://github.com/MannLabs/alphatims/releases/download/0.1.210317/20201207_tims03_Evo03_PS_SA_HeLa_200ng_EvoSep_prot_DDA_21min_8cm_S1-C10_1_22476.d.zip'\n", "file_name = '20201207_tims03_Evo03_PS_SA_HeLa_200ng_EvoSep_prot_DDA_21min_8cm_S1-C10_1_22476.d.zip'\n", "extract_dir = './' # Directory to extract the contents\n", "\n", "# # Download the file\n", "response = requests.get(url)\n", "with open(file_name, 'wb') as file:\n", " file.write(response.content)\n", "\n", "print(f'File {file_name} downloaded successfully!')\n", "\n", "# Unzip the file\n", "with zipfile.ZipFile(file_name, 'r') as zip_ref:\n", " zip_ref.extractall(extract_dir)\n", "\n", "print(f'File extracted to {extract_dir}!')\n", "\n", "# Optionally, remove the zip file after extraction\n", "os.remove(file_name)\n", "print(f'Zip file {file_name} removed.')" ] }, { "cell_type": "markdown", "id": "5d600e03-aa37-49ed-9b77-2372f0d8b177", "metadata": {}, "source": [ "## Load `.d` File and Extra a section of it as a `pd.DataFrame`" ] }, { "cell_type": "code", "execution_count": 9, "id": "b292914a-87aa-452b-b2c9-c982da0ce8c6", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:237: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.Id[0] = 0\n", "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:238: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.Time[0] = 0\n", "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:239: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.MaxIntensity[0] = 0\n", "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:240: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.SummedIntensities[0] = 0\n", "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:241: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.NumPeaks[0] = 0\n", "/home/joshua/mambaforge/envs/pyopenms-viz/lib/python3.12/site-packages/alphatims/bruker.py:242: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n", "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n", "A typical example is when you are setting values in a column of a DataFrame, like:\n", "\n", "df[\"col\"][row_indexer] = value\n", "\n", "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", "\n", " frames.MsMsType[0] = 0\n", "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 11886/11886 [00:01<00:00, 9692.55it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Time taken to run the code: 2.02 seconds\n" ] }, { "data": { "text/html": [ "
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raw_indicesframe_indicesscan_indicesprecursor_indicespush_indicestof_indicesrt_valuesrt_values_minmobility_valuesquad_low_mz_valuesquad_high_mz_valuesmz_valuesintensity_valuescorrected_intensity_values
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.............................................
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17041 rows × 14 columns

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" ], "text/plain": [ " raw_indices frame_indices scan_indices precursor_indices \\\n", "0 0 1 52 0 \n", "1 1 1 63 0 \n", "2 2 1 69 0 \n", "3 3 1 77 0 \n", "4 4 1 78 0 \n", "... ... ... ... ... \n", "17036 17036 1 919 0 \n", "17037 17037 1 919 0 \n", "17038 17038 1 919 0 \n", "17039 17039 1 923 0 \n", "17040 17040 1 923 0 \n", "\n", " push_indices tof_indices rt_values rt_values_min mobility_values \\\n", "0 980 255431 0.564402 0.009407 1.580692 \n", "1 991 308595 0.564402 0.009407 1.568660 \n", "2 997 160184 0.564402 0.009407 1.562095 \n", "3 1005 375561 0.564402 0.009407 1.553337 \n", "4 1006 248580 0.564402 0.009407 1.552242 \n", "... ... ... ... ... ... \n", "17036 1847 74875 0.564402 0.009407 0.609185 \n", "17037 1847 112482 0.564402 0.009407 0.609185 \n", "17038 1847 143231 0.564402 0.009407 0.609185 \n", "17039 1851 160022 0.564402 0.009407 0.604592 \n", "17040 1851 167506 0.564402 0.009407 0.604592 \n", "\n", " quad_low_mz_values quad_high_mz_values mz_values intensity_values \\\n", "0 -1.0 -1.0 913.250345 10 \n", "1 -1.0 -1.0 1185.318098 86 \n", "2 -1.0 -1.0 514.400704 159 \n", "3 -1.0 -1.0 1578.430403 53 \n", "4 -1.0 -1.0 880.766749 47 \n", "... ... ... ... ... \n", "17036 -1.0 -1.0 253.681834 81 \n", "17037 -1.0 -1.0 357.374903 253 \n", "17038 -1.0 -1.0 455.328372 130 \n", "17039 -1.0 -1.0 513.819175 154 \n", "17040 -1.0 -1.0 541.027761 174 \n", "\n", " corrected_intensity_values \n", "0 10 \n", "1 86 \n", "2 159 \n", "3 53 \n", "4 47 \n", "... ... \n", "17036 81 \n", "17037 253 \n", "17038 130 \n", "17039 154 \n", "17040 174 \n", "\n", "[17041 rows x 14 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import alphatims.bruker\n", "\n", "bruker_dia_d_folder_name = \"./20201207_tims03_Evo03_PS_SA_HeLa_200ng_EvoSep_prot_DDA_21min_8cm_S1-C10_1_22476.d\"\n", "dda_data = alphatims.bruker.TimsTOF(bruker_dia_d_folder_name)\n", "\n", "# Slice the resulting object to return a pandas dataframe\n", "# for full details see https://github.com/MannLabs/alphatims/blob/master/nbs/tutorial.ipynb\n", "dda_data[1] # returns the first spectrum" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 5 }