From 70bb747233c0873299b1b0618ebe34af4b142c6d Mon Sep 17 00:00:00 2001 From: Luis Perez Date: Fri, 21 Aug 2020 19:28:10 -0700 Subject: [PATCH] Major refactoring of base code. All contents replaced for files generated by cookiecutter template. All previous files deleted and replaced by an automatically-generated cookiecutter template. Unit tests verified and working. Fixed an error on unit tests. Reorganized main function so it's only necessary to call it as "flowsym" or "from flowsym import ..." --- .github/ISSUE_TEMPLATE.md | 15 + .gitignore | 105 +++ .idea/.gitignore | 8 + .ipynb_checkpoints/facsim-checkpoint.py | 318 -------- .../requirements-checkpoint.txt | 4 - .travis.yml | 29 + AUTHORS.rst | 13 + CONTRIBUTING.rst | 128 +++ HISTORY.rst | 8 + LICENSE | 22 + MANIFEST.in | 11 + Makefile | 85 ++ README.md | 2 - README.rst | 41 + docs/Makefile | 20 + docs/authors.rst | 1 + docs/conf.py | 162 ++++ docs/contributing.rst | 1 + docs/history.rst | 1 + docs/index.rst | 20 + docs/installation.rst | 51 ++ docs/make.bat | 36 + docs/readme.rst | 1 + docs/usage.rst | 7 + flowsym.py | 744 ------------------ flowsym/__init__.py | 5 + flowsym/cli.py | 16 + {data => flowsym/data}/FPbase_Spectra.csv | 0 .../data}/FPbase_Spectra_updated.csv | 0 {data => flowsym/data}/sample_output.fcs | Bin flowsym/flowsym.py | 1 + requirements.txt | 18 +- requirements_dev.txt | 12 + setup.cfg | 26 + setup.py | 53 ++ test_flowsym.py | 76 -- tests/__init__.py | 1 + tests/data/FPbase_Spectra.csv | 552 +++++++++++++ tests/data/FPbase_Spectra_updated.csv | 552 +++++++++++++ tests/data/sample_output.fcs | Bin 0 -> 24688 bytes tests/test_flowsym.py | 37 + tox.ini | 27 + 42 files changed, 2058 insertions(+), 1151 deletions(-) create mode 100644 .github/ISSUE_TEMPLATE.md create mode 100644 .gitignore create mode 100644 .idea/.gitignore delete mode 100644 .ipynb_checkpoints/facsim-checkpoint.py delete mode 100644 .ipynb_checkpoints/requirements-checkpoint.txt create mode 100644 .travis.yml create mode 100644 AUTHORS.rst create mode 100644 CONTRIBUTING.rst create mode 100644 HISTORY.rst create mode 100644 LICENSE create mode 100644 MANIFEST.in create mode 100644 Makefile delete mode 100644 README.md create mode 100644 README.rst create mode 100644 docs/Makefile create mode 100644 docs/authors.rst create mode 100644 docs/conf.py create mode 100644 docs/contributing.rst create mode 100644 docs/history.rst create mode 100644 docs/index.rst create mode 100644 docs/installation.rst create mode 100644 docs/make.bat create mode 100644 docs/readme.rst create mode 100644 docs/usage.rst delete mode 100644 flowsym.py create mode 100644 flowsym/__init__.py create mode 100644 flowsym/cli.py rename {data => flowsym/data}/FPbase_Spectra.csv (100%) rename {data => flowsym/data}/FPbase_Spectra_updated.csv (100%) rename {data => flowsym/data}/sample_output.fcs (100%) create mode 100644 flowsym/flowsym.py create mode 100644 requirements_dev.txt create mode 100644 setup.cfg create mode 100644 setup.py delete mode 100644 test_flowsym.py create mode 100644 tests/__init__.py create mode 100644 tests/data/FPbase_Spectra.csv create mode 100644 tests/data/FPbase_Spectra_updated.csv create mode 100644 tests/data/sample_output.fcs create mode 100644 tests/test_flowsym.py create mode 100644 tox.ini diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md new file mode 100644 index 0000000..1eb072b --- /dev/null +++ b/.github/ISSUE_TEMPLATE.md @@ -0,0 +1,15 @@ +* flowsym version: +* Python version: +* Operating System: + +### Description + +Describe what you were trying to get done. +Tell us what happened, what went wrong, and what you expected to happen. + +### What I Did + +``` +Paste the command(s) you ran and the output. +If there was a crash, please include the traceback here. +``` diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..43091aa --- /dev/null +++ b/.gitignore @@ -0,0 +1,105 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +env/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# pyenv +.python-version + +# celery beat schedule file +celerybeat-schedule + +# SageMath parsed files +*.sage.py + +# dotenv +.env + +# virtualenv +.venv +venv/ +ENV/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ + +# IDE settings +.vscode/ \ No newline at end of file diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..73f69e0 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml +# Editor-based HTTP Client requests +/httpRequests/ diff --git a/.ipynb_checkpoints/facsim-checkpoint.py b/.ipynb_checkpoints/facsim-checkpoint.py deleted file mode 100644 index 704c247..0000000 --- a/.ipynb_checkpoints/facsim-checkpoint.py +++ /dev/null @@ -1,318 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Created on Mon Jan 20 09:57:16 2020 - -:author: Michael -:author: Luis -""" - -# Check to see if fcsy is installed on machine -import importlib.util - -package_name = 'fcsy' -spec = importlib.util.find_spec(package_name) -if spec is None: - print( - f"{package_name} is not installed, please install {package_name} to write fcs files in the \'measure\' function!") - -import numpy as np -import pandas as pd -import time -from fcsy.fcs import write_fcs - -# from __init__ import spectrum_data - -# Temp - init file in same directory screws up pytest run -spectrum_data = pd.read_csv( - 'data/FPbase_Spectra_updated.csv').fillna(value=0) - - -def create_controls(size, colors=['Blue', 'Cyan', 'Green', 'Yellow', 'Orange', 'Red', 'Far_red', 'NIR', 'IR']): - """ - This is a function that takes a DataFrame size (i.e. number of controls) and - a list of colors the user wants to run controls for. - :param size: - :param colors: - :return: - """ - - # Check to make sure the inputs were of correct type - if type(size) != int: - raise TypeError("size cannot be of type: " + str(type(size))) - elif type(colors) != list: - raise TypeError("Ex cannot be of type: " + str(type(colors))) - - # Controls data - accept whatever colors the user provides - controls_dict = {} - for i in colors: - controls_dict[i] = {'Wavelength': [], 'Excitation Efficiency': [], 'Emission Efficiency': []} - - # Make excitation and emission data easier to read in to dictionary - wavelengths = spectrum_data['Wavelength'] - - green_ex_efficiency = spectrum_data['Fluorescein (FITC) EX'] - red_ex_efficiency = spectrum_data['Kaede (Red) EX'] - blue_ex_efficiency = spectrum_data['Pacific Blue EX'] - far_red_ex_efficiency = spectrum_data['APC (allophycocyanin) AB'] - NIR_ex_efficiency = spectrum_data['PerCP-Cy5.5 AB'] - IR_ex_efficiency = spectrum_data['APC/Cy7 EX'] - cyan_ex_efficiency = spectrum_data['CFP EX'] - yellow_ex_efficiency = spectrum_data['EYFP EX'] - orange_ex_efficiency = spectrum_data['mOrange EX'] - - # Excitation and emission data for each color control - pre-defined information - excitation_dict = {'green': [list(wavelengths), list(green_ex_efficiency)], - 'red': [list(wavelengths), list(red_ex_efficiency)], - 'blue': [list(wavelengths), list(blue_ex_efficiency)], - 'far_red': [list(wavelengths), list(far_red_ex_efficiency)], - 'nir': [list(wavelengths), list(NIR_ex_efficiency)], - 'ir': [list(wavelengths), list(IR_ex_efficiency)], - 'cyan': [list(wavelengths), list(cyan_ex_efficiency)], - 'yellow': [list(wavelengths), list(yellow_ex_efficiency)], - 'orange': [list(wavelengths), list(orange_ex_efficiency)]} - - # Make excitation and emission data easier to read in to dictionary - green_em_efficiency = spectrum_data['Fluorescein (FITC) EM'] - red_em_efficiency = spectrum_data['Kaede (Red) EM'] - blue_em_efficiency = spectrum_data['Pacific Blue EM'] - far_red_em_efficiency = spectrum_data['APC (allophycocyanin) EM'] - NIR_em_efficiency = spectrum_data['PerCP-Cy5.5 EM'] - IR_em_efficiency = spectrum_data['APC/Cy7 EM'] - cyan_em_efficiency = spectrum_data['CFP EM'] - yellow_em_efficiency = spectrum_data['EYFP EM'] - orange_em_efficiency = spectrum_data['mOrange EM'] - - # Excitation and emission data for each color control - pre-defined information - emission_dict = {'green': [list(wavelengths), list(green_em_efficiency)], - 'red': [list(wavelengths), list(red_em_efficiency)], - 'blue': [list(wavelengths), list(blue_em_efficiency)], - 'far_red': [list(wavelengths), list(far_red_em_efficiency)], - 'nir': [list(wavelengths), list(NIR_em_efficiency)], - 'ir': [list(wavelengths), list(IR_em_efficiency)], - 'cyan': [list(wavelengths), list(cyan_em_efficiency)], - 'yellow': [list(wavelengths), list(yellow_em_efficiency)], - 'orange': [list(wavelengths), list(orange_em_efficiency)]} - - # Match colors that the user wants to excitation and emission data - for key, value in controls_dict.items(): - key = key.lower() # Doesn't matter if user entered capital letters or not - if key in excitation_dict: - value['Wavelength'] = [excitation_dict[key][0]] - value['Excitation Efficiency'] = [excitation_dict[key][1]] - value['Emission Efficiency'] = [emission_dict[key][1]] - - else: - raise NameError(str(key) + ' is not an available control, try: ' + - str(list(excitation_dict.keys()))) - - # Create a new dictionary that will keep the associated colors with dataframe objects - results_dict = {} - for key, value in controls_dict.items(): - results_dict[key] = pd.DataFrame(value) - - # Finally, create a list that will hold all DFs while preserving color order - final_control_results = [] - for i in colors: - final_control_results.append(pd.concat([results_dict[i]] * size, ignore_index=True)) - - # Return tuple of the list for easy access of colors - return tuple(final_control_results) - - -def create_sample(size, colors=['Blue', 'Cyan', 'Green', 'Yellow', 'Orange', 'Red', 'Far_red', 'NIR', 'IR'], - weights=[]): - """ - This is a function that takes a defined dataframe length for number of samples (int) - and excitation and emission wavelengths (list,list). Assumes equal probability of each - color unless specified by the user - :param size: - :param colors: - :param weights: - :return: - """ - - - # Check to make sure the inputs were of correct type - if type(size) != int: - raise TypeError("size cannot be of type: " + str(type(size))) - elif type(colors) != list: - raise TypeError("Ex cannot be of type: " + str(type(colors))) - - # Make excitation and emission data easier to read in to dictionary - wavelengths = spectrum_data['Wavelength'] - - green_ex_efficiency = spectrum_data['Fluorescein (FITC) EX'] - red_ex_efficiency = spectrum_data['Kaede (Red) EX'] - blue_ex_efficiency = spectrum_data['Pacific Blue EX'] - far_red_ex_efficiency = spectrum_data['APC (allophycocyanin) AB'] - NIR_ex_efficiency = spectrum_data['PerCP-Cy5.5 AB'] - IR_ex_efficiency = spectrum_data['APC/Cy7 EX'] - cyan_ex_efficiency = spectrum_data['CFP EX'] - yellow_ex_efficiency = spectrum_data['EYFP EX'] - orange_ex_efficiency = spectrum_data['mOrange EX'] - - # Excitation and emission data for each color control - pre-defined information - excitation_dict = {'green': [list(wavelengths), list(green_ex_efficiency)], - 'red': [list(wavelengths), list(red_ex_efficiency)], - 'blue': [list(wavelengths), list(blue_ex_efficiency)], - 'far_red': [list(wavelengths), list(far_red_ex_efficiency)], - 'nir': [list(wavelengths), list(NIR_ex_efficiency)], - 'ir': [list(wavelengths), list(IR_ex_efficiency)], - 'cyan': [list(wavelengths), list(cyan_ex_efficiency)], - 'yellow': [list(wavelengths), list(yellow_ex_efficiency)], - 'orange': [list(wavelengths), list(orange_ex_efficiency)]} - - # Make excitation and emission data easier to read in to dictionary - green_em_efficiency = spectrum_data['Fluorescein (FITC) EM'] - red_em_efficiency = spectrum_data['Kaede (Red) EM'] - blue_em_efficiency = spectrum_data['Pacific Blue EM'] - far_red_em_efficiency = spectrum_data['APC (allophycocyanin) EM'] - NIR_em_efficiency = spectrum_data['PerCP-Cy5.5 EM'] - IR_em_efficiency = spectrum_data['APC/Cy7 EM'] - cyan_em_efficiency = spectrum_data['CFP EM'] - yellow_em_efficiency = spectrum_data['EYFP EM'] - orange_em_efficiency = spectrum_data['mOrange EM'] - - # Excitation and emission data for each color control - pre-defined information - emission_dict = {'green': [list(wavelengths), list(green_em_efficiency)], - 'red': [list(wavelengths), list(red_em_efficiency)], - 'blue': [list(wavelengths), list(blue_em_efficiency)], - 'far_red': [list(wavelengths), list(far_red_em_efficiency)], - 'nir': [list(wavelengths), list(NIR_em_efficiency)], - 'ir': [list(wavelengths), list(IR_em_efficiency)], - 'cyan': [list(wavelengths), list(cyan_em_efficiency)], - 'yellow': [list(wavelengths), list(yellow_em_efficiency)], - 'orange': [list(wavelengths), list(orange_em_efficiency)]} - - # Set dictionary to be made into dataframe - sample_dict = {'Wavelength': [], 'Excitation Efficiency': [], 'Emission Efficiency': []} - - # Make "size" number of cell entries - for i in range(size): - if len(weights) == 0: - color_to_pick = np.random.choice(colors).lower() - else: - color_to_pick = np.random.choice(colors, p=weights).lower() - - sample_dict['Wavelength'].append(excitation_dict[color_to_pick][0]) - sample_dict['Excitation Efficiency'].append(excitation_dict[color_to_pick][1]) - sample_dict['Emission Efficiency'].append(emission_dict[color_to_pick][1]) - - data = pd.DataFrame(sample_dict) - - # Create protein copy number - copies = np.round(np.random.normal(100, size=len(data), scale=20)) - data['Copy number'] = copies - - # Return just the sample dataframe - return data - - -# Bandwidth on lasers is +-5 nm. channels are [450+-25, 525+-25, 600+-30, 665+-15, 720+-30, 785+-30] for filter set 2 -def measure(dataframe, lasers=[405, 488, 561, 638], channels=[1, 2, 3, 4, 5, 6], - create_fcs=True, outfile_name='data/sample_output.fcs'): - """ - This is a function that will measure fluorescence intensity for any given sample - DataFrame and laser/channel parameters. Output will be an fcs file (default) that is - the same size as the sample you ran in the function. Alternatively, you can return - just a pandas DataFrame object by setting return_fcs=False. The user can set the output - file name manually to simulate creating multiple samples and measurements. - """ - # Bandwidth for each fluorescence channel - channels_information = {1: list(range(425, 475)), 2: list(range(500, 550)), 3: list(range(570, 630)), - 4: list(range(650, 680)), - 5: list(range(690, 750)), 6: list(range(755, 805))} - - # This is the list that will hold all of the intensity vectors for each cell - new_dataframe_list = [['FL' + str(i) for i in channels]] - - # where are our laser wavelengths in our input dataframe? - laser_indices = {} - - # For each laser, find the indices for their wavelengths and their gaussian efficiencies - for laser in lasers: - # This part makes a gaussian distribution of each laser+-5 - counts_dict = {} - myarray = np.array(np.round(np.random.normal(loc=laser, scale=2.0, size=10000))) - new_array = [x for x in myarray if laser + 5 >= x >= laser - 5] - - for i in new_array: - if i not in counts_dict.keys(): - counts_dict[i] = list(new_array).count(i) - - max_count = max(counts_dict.values()) - - for key, value in counts_dict.items(): - counts_dict[key] = value / max_count - - # Find the wavelength indices that our lasers hit - make a dictionary with indices as keys and laser - # efficiencies as values - for index2, wave in enumerate(dataframe['Wavelength'][0]): - if wave in counts_dict.keys(): - laser_indices[index2] = counts_dict[wave] - - # figure out unique emission profiles based on color so we know when to end the loop - copy = dataframe.copy() - copy['Emission Efficiency'] = copy['Emission Efficiency'].astype(str) - - # Create numpy arrays to randomly sample from based on the number of excited molecules - emission_reference = {} - - for index, row in dataframe.iterrows(): - if str(row['Emission Efficiency']) not in emission_reference.keys(): - waves_to_add = np.array([round(value * 100) * [row['Wavelength'][index]] for index, value in - enumerate(row['Emission Efficiency']) if value >= 0.01]) - emission_reference[str(row['Emission Efficiency'])] = np.array([y for x in waves_to_add for y in x]) - - if len(emission_reference.keys()) == len(copy['Emission Efficiency'].unique()): - break - - # for each cell that is being analyzed - for index, row in dataframe.iterrows(): - intensity_vector = [] - - # Calculate peak excitation efficiency for our cell given all lasers at once (collinear laser set up) - excitation_max = max([row['Excitation Efficiency'][key] * value for key, value in laser_indices.items()]) - num_excited_proteins = round(row['Copy number'] * excitation_max) - - # Sample emission at wavelengths corresponding to real emission efficiency from FPbase, size=number of - # excited proteins - real_emission_wavelengths = np.random.choice(emission_reference[str(row['Emission Efficiency'])], - size=num_excited_proteins) - - # amp = np.random.choice(list(range(1000,1700,40))) - # For each fluorescence channel, find the appropriate emission values - for channel in channels: - em_chan = channels_information[channel] - - # Find intensity in each channel - NOTE using intersection and set here speed up the code DRAMATICALLY - emission_intensity = len(set(real_emission_wavelengths).intersection(em_chan)) * ( - 1000 + np.random.normal(0, scale=50)) # Average amplification +- noise - - # add intensity in each channel to the vector - intensity_vector.append(float(emission_intensity)) - - new_dataframe_list.append(intensity_vector) - - column_names = new_dataframe_list.pop(0) - - # Create new dataframe and output - output = pd.DataFrame(new_dataframe_list, columns=column_names) - - if create_fcs: - write_fcs(output, outfile_name) - print("FCS file created with filename: " + str(outfile_name)) - - return output - - -# Run the code outside of defining functions -if __name__ == "__main__": - sample_size = 1000 - - sample = create_sample(sample_size) - - start = time.time() - measurements = measure(sample) - stop = time.time() - print("Time to run measure was " + str(round(stop - start, 3)) + " seconds") diff --git a/.ipynb_checkpoints/requirements-checkpoint.txt b/.ipynb_checkpoints/requirements-checkpoint.txt deleted file mode 100644 index 0cc0df2..0000000 --- a/.ipynb_checkpoints/requirements-checkpoint.txt +++ /dev/null @@ -1,4 +0,0 @@ -numpy~=1.18.1 -pandas~=0.24.2 -fcsy~=0.3.1 -pytest~=5.4.2 \ No newline at end of file diff --git a/.travis.yml b/.travis.yml new file mode 100644 index 0000000..21c3bb7 --- /dev/null +++ b/.travis.yml @@ -0,0 +1,29 @@ +# Config file for automatic testing at travis-ci.com + +language: python +python: + - 3.8 + - 3.7 + - 3.6 + - 3.5 + +# Command to install dependencies, e.g. pip install -r requirements.txt --use-mirrors +install: pip install -U tox-travis + +# Command to run tests, e.g. python setup.py test +script: tox + +# Assuming you have installed the travis-ci CLI tool, after you +# create the Github repo and add it to Travis, run the +# following command to finish PyPI deployment setup: +# $ travis encrypt --add deploy.password +deploy: + provider: pypi + distributions: sdist bdist_wheel + user: mshavlik; lperezmo + password: + secure: PLEASE_REPLACE_ME + on: + tags: true + repo: mshavlik; lperezmo/flowsym + python: 3.8 diff --git a/AUTHORS.rst b/AUTHORS.rst new file mode 100644 index 0000000..773b3c7 --- /dev/null +++ b/AUTHORS.rst @@ -0,0 +1,13 @@ +======= +Credits +======= + +Development Lead +---------------- + +* Michael M. Shavlik; Luis Perez Morales + +Contributors +------------ + +None yet. Why not be the first? diff --git a/CONTRIBUTING.rst b/CONTRIBUTING.rst new file mode 100644 index 0000000..446a742 --- /dev/null +++ b/CONTRIBUTING.rst @@ -0,0 +1,128 @@ +.. highlight:: shell + +============ +Contributing +============ + +Contributions are welcome, and they are greatly appreciated! Every little bit +helps, and credit will always be given. + +You can contribute in many ways: + +Types of Contributions +---------------------- + +Report Bugs +~~~~~~~~~~~ + +Report bugs at https://github.com/mshavlik; lperezmo/flowsym/issues. + +If you are reporting a bug, please include: + +* Your operating system name and version. +* Any details about your local setup that might be helpful in troubleshooting. +* Detailed steps to reproduce the bug. + +Fix Bugs +~~~~~~~~ + +Look through the GitHub issues for bugs. Anything tagged with "bug" and "help +wanted" is open to whoever wants to implement it. + +Implement Features +~~~~~~~~~~~~~~~~~~ + +Look through the GitHub issues for features. Anything tagged with "enhancement" +and "help wanted" is open to whoever wants to implement it. + +Write Documentation +~~~~~~~~~~~~~~~~~~~ + +flowsym could always use more documentation, whether as part of the +official flowsym docs, in docstrings, or even on the web in blog posts, +articles, and such. + +Submit Feedback +~~~~~~~~~~~~~~~ + +The best way to send feedback is to file an issue at https://github.com/mshavlik; lperezmo/flowsym/issues. + +If you are proposing a feature: + +* Explain in detail how it would work. +* Keep the scope as narrow as possible, to make it easier to implement. +* Remember that this is a volunteer-driven project, and that contributions + are welcome :) + +Get Started! +------------ + +Ready to contribute? Here's how to set up `flowsym` for local development. + +1. Fork the `flowsym` repo on GitHub. +2. Clone your fork locally:: + + $ git clone git@github.com:your_name_here/flowsym.git + +3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:: + + $ mkvirtualenv flowsym + $ cd flowsym/ + $ python setup.py develop + +4. Create a branch for local development:: + + $ git checkout -b name-of-your-bugfix-or-feature + + Now you can make your changes locally. + +5. When you're done making changes, check that your changes pass flake8 and the + tests, including testing other Python versions with tox:: + + $ flake8 flowsym tests + $ python setup.py test or pytest + $ tox + + To get flake8 and tox, just pip install them into your virtualenv. + +6. Commit your changes and push your branch to GitHub:: + + $ git add . + $ git commit -m "Your detailed description of your changes." + $ git push origin name-of-your-bugfix-or-feature + +7. Submit a pull request through the GitHub website. + +Pull Request Guidelines +----------------------- + +Before you submit a pull request, check that it meets these guidelines: + +1. The pull request should include tests. +2. If the pull request adds functionality, the docs should be updated. Put + your new functionality into a function with a docstring, and add the + feature to the list in README.rst. +3. The pull request should work for Python 3.5, 3.6, 3.7 and 3.8, and for PyPy. Check + https://travis-ci.com/mshavlik; lperezmo/flowsym/pull_requests + and make sure that the tests pass for all supported Python versions. + +Tips +---- + +To run a subset of tests:: + +$ pytest tests.test_flowsym + + +Deploying +--------- + +A reminder for the maintainers on how to deploy. +Make sure all your changes are committed (including an entry in HISTORY.rst). +Then run:: + +$ bump2version patch # possible: major / minor / patch +$ git push +$ git push --tags + +Travis will then deploy to PyPI if tests pass. diff --git a/HISTORY.rst b/HISTORY.rst new file mode 100644 index 0000000..a99a090 --- /dev/null +++ b/HISTORY.rst @@ -0,0 +1,8 @@ +======= +History +======= + +0.1.0 (2020-08-21) +------------------ + +* First release on PyPI. diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..e9fa158 --- /dev/null +++ b/LICENSE @@ -0,0 +1,22 @@ +MIT License + +Copyright (c) 2020, Michael M. Shavlik; Luis Perez Morales + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + diff --git a/MANIFEST.in b/MANIFEST.in new file mode 100644 index 0000000..965b2dd --- /dev/null +++ b/MANIFEST.in @@ -0,0 +1,11 @@ +include AUTHORS.rst +include CONTRIBUTING.rst +include HISTORY.rst +include LICENSE +include README.rst + +recursive-include tests * +recursive-exclude * __pycache__ +recursive-exclude * *.py[co] + +recursive-include docs *.rst conf.py Makefile make.bat *.jpg *.png *.gif diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..b171145 --- /dev/null +++ b/Makefile @@ -0,0 +1,85 @@ +.PHONY: clean clean-test clean-pyc clean-build docs help +.DEFAULT_GOAL := help + +define BROWSER_PYSCRIPT +import os, webbrowser, sys + +from urllib.request import pathname2url + +webbrowser.open("file://" + pathname2url(os.path.abspath(sys.argv[1]))) +endef +export BROWSER_PYSCRIPT + +define PRINT_HELP_PYSCRIPT +import re, sys + +for line in sys.stdin: + match = re.match(r'^([a-zA-Z_-]+):.*?## (.*)$$', line) + if match: + target, help = match.groups() + print("%-20s %s" % (target, help)) +endef +export PRINT_HELP_PYSCRIPT + +BROWSER := python -c "$$BROWSER_PYSCRIPT" + +help: + @python -c "$$PRINT_HELP_PYSCRIPT" < $(MAKEFILE_LIST) + +clean: clean-build clean-pyc clean-test ## remove all build, test, coverage and Python artifacts + +clean-build: ## remove build artifacts + rm -fr build/ + rm -fr dist/ + rm -fr .eggs/ + find . -name '*.egg-info' -exec rm -fr {} + + find . -name '*.egg' -exec rm -f {} + + +clean-pyc: ## remove Python file artifacts + find . -name '*.pyc' -exec rm -f {} + + find . -name '*.pyo' -exec rm -f {} + + find . -name '*~' -exec rm -f {} + + find . -name '__pycache__' -exec rm -fr {} + + +clean-test: ## remove test and coverage artifacts + rm -fr .tox/ + rm -f .coverage + rm -fr htmlcov/ + rm -fr .pytest_cache + +lint: ## check style with flake8 + flake8 flowsym tests + +test: ## run tests quickly with the default Python + pytest + +test-all: ## run tests on every Python version with tox + tox + +coverage: ## check code coverage quickly with the default Python + coverage run --source flowsym -m pytest + coverage report -m + coverage html + $(BROWSER) htmlcov/index.html + +docs: ## generate Sphinx HTML documentation, including API docs + rm -f docs/flowsym.rst + rm -f docs/modules.rst + sphinx-apidoc -o docs/ flowsym + $(MAKE) -C docs clean + $(MAKE) -C docs html + $(BROWSER) docs/_build/html/index.html + +servedocs: docs ## compile the docs watching for changes + watchmedo shell-command -p '*.rst' -c '$(MAKE) -C docs html' -R -D . + +release: dist ## package and upload a release + twine upload dist/* + +dist: clean ## builds source and wheel package + python setup.py sdist + python setup.py bdist_wheel + ls -l dist + +install: clean ## install the package to the active Python's site-packages + python setup.py install diff --git a/README.md b/README.md deleted file mode 100644 index 598fbd0..0000000 --- a/README.md +++ /dev/null @@ -1,2 +0,0 @@ -# Flowsym -Simulation software of Fluorescence Assisted Cell Sorting diff --git a/README.rst b/README.rst new file mode 100644 index 0000000..2e8803f --- /dev/null +++ b/README.rst @@ -0,0 +1,41 @@ +======= +flowsym +======= + + +.. image:: https://img.shields.io/pypi/v/flowsym.svg + :target: https://pypi.python.org/pypi/flowsym + +.. image:: https://img.shields.io/travis/mshavlik; lperezmo/flowsym.svg + :target: https://travis-ci.com/mshavlik; lperezmo/flowsym + +.. image:: https://readthedocs.org/projects/flowsym/badge/?version=latest + :target: https://flowsym.readthedocs.io/en/latest/?badge=latest + :alt: Documentation Status + + +.. image:: https://pyup.io/repos/github/mshavlik; lperezmo/flowsym/shield.svg + :target: https://pyup.io/repos/github/mshavlik; lperezmo/flowsym/ + :alt: Updates + + + +A Python API for simulating flow cytometry data + + +* Free software: MIT license +* Documentation: https://flowsym.readthedocs.io. + + +Features +-------- + +* TODO + +Credits +------- + +This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template. + +.. _Cookiecutter: https://github.com/audreyr/cookiecutter +.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..691aecd --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = python -msphinx +SPHINXPROJ = flowsym +SOURCEDIR = . +BUILDDIR = _build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/authors.rst b/docs/authors.rst new file mode 100644 index 0000000..e122f91 --- /dev/null +++ b/docs/authors.rst @@ -0,0 +1 @@ +.. include:: ../AUTHORS.rst diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..36b61cf --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,162 @@ +#!/usr/bin/env python +# +# flowsym documentation build configuration file, created by +# sphinx-quickstart on Fri Jun 9 13:47:02 2017. +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +# If extensions (or modules to document with autodoc) are in another +# directory, add these directories to sys.path here. If the directory is +# relative to the documentation root, use os.path.abspath to make it +# absolute, like shown here. +# +import os +import sys +sys.path.insert(0, os.path.abspath('..')) + +import flowsym + +# -- General configuration --------------------------------------------- + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones. +extensions = ['sphinx.ext.autodoc', 'sphinx.ext.viewcode'] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# +# source_suffix = ['.rst', '.md'] +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +project = 'flowsym' +copyright = "2020, Michael M. Shavlik; Luis Perez Morales" +author = "Michael M. Shavlik; Luis Perez Morales" + +# The version info for the project you're documenting, acts as replacement +# for |version| and |release|, also used in various other places throughout +# the built documents. +# +# The short X.Y version. +version = flowsym.__version__ +# The full version, including alpha/beta/rc tags. +release = flowsym.__version__ + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = None + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This patterns also effect to html_static_path and html_extra_path +exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'sphinx' + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = False + + +# -- Options for HTML output ------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'alabaster' + +# Theme options are theme-specific and customize the look and feel of a +# theme further. For a list of options available for each theme, see the +# documentation. +# +# html_theme_options = {} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + + +# -- Options for HTMLHelp output --------------------------------------- + +# Output file base name for HTML help builder. +htmlhelp_basename = 'flowsymdoc' + + +# -- Options for LaTeX output ------------------------------------------ + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, author, documentclass +# [howto, manual, or own class]). +latex_documents = [ + (master_doc, 'flowsym.tex', + 'flowsym Documentation', + 'Michael M. Shavlik; Luis Perez Morales', 'manual'), +] + + +# -- Options for manual page output ------------------------------------ + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + (master_doc, 'flowsym', + 'flowsym Documentation', + [author], 1) +] + + +# -- Options for Texinfo output ---------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + (master_doc, 'flowsym', + 'flowsym Documentation', + author, + 'flowsym', + 'One line description of project.', + 'Miscellaneous'), +] + + + diff --git a/docs/contributing.rst b/docs/contributing.rst new file mode 100644 index 0000000..e582053 --- /dev/null +++ b/docs/contributing.rst @@ -0,0 +1 @@ +.. include:: ../CONTRIBUTING.rst diff --git a/docs/history.rst b/docs/history.rst new file mode 100644 index 0000000..2506499 --- /dev/null +++ b/docs/history.rst @@ -0,0 +1 @@ +.. include:: ../HISTORY.rst diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..88cb0cf --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,20 @@ +Welcome to flowsym's documentation! +====================================== + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + readme + installation + usage + modules + contributing + authors + history + +Indices and tables +================== +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/installation.rst b/docs/installation.rst new file mode 100644 index 0000000..cb3225c --- /dev/null +++ b/docs/installation.rst @@ -0,0 +1,51 @@ +.. highlight:: shell + +============ +Installation +============ + + +Stable release +-------------- + +To install flowsym, run this command in your terminal: + +.. code-block:: console + + $ pip install flowsym + +This is the preferred method to install flowsym, as it will always install the most recent stable release. + +If you don't have `pip`_ installed, this `Python installation guide`_ can guide +you through the process. + +.. _pip: https://pip.pypa.io +.. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/ + + +From sources +------------ + +The sources for flowsym can be downloaded from the `Github repo`_. + +You can either clone the public repository: + +.. code-block:: console + + $ git clone git://github.com/mshavlik; lperezmo/flowsym + +Or download the `tarball`_: + +.. code-block:: console + + $ curl -OJL https://github.com/mshavlik; lperezmo/flowsym/tarball/master + +Once you have a copy of the source, you can install it with: + +.. code-block:: console + + $ python setup.py install + + +.. _Github repo: https://github.com/mshavlik; lperezmo/flowsym +.. _tarball: https://github.com/mshavlik; lperezmo/flowsym/tarball/master diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..ba4219a --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,36 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=python -msphinx +) +set SOURCEDIR=. +set BUILDDIR=_build +set SPHINXPROJ=flowsym + +if "%1" == "" goto help + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The Sphinx module was not found. Make sure you have Sphinx installed, + echo.then set the SPHINXBUILD environment variable to point to the full + echo.path of the 'sphinx-build' executable. Alternatively you may add the + echo.Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 +) + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% + +:end +popd diff --git a/docs/readme.rst b/docs/readme.rst new file mode 100644 index 0000000..72a3355 --- /dev/null +++ b/docs/readme.rst @@ -0,0 +1 @@ +.. include:: ../README.rst diff --git a/docs/usage.rst b/docs/usage.rst new file mode 100644 index 0000000..7e0239a --- /dev/null +++ b/docs/usage.rst @@ -0,0 +1,7 @@ +===== +Usage +===== + +To use flowsym in a project:: + + import flowsym diff --git a/flowsym.py b/flowsym.py deleted file mode 100644 index 89da4c4..0000000 --- a/flowsym.py +++ /dev/null @@ -1,744 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Created on Mon Jan 20 09:57:16 2020 - -:author: Michael -:author: Luis -""" - -# Check to see if fcsy and hdbscan are installed on machine -import importlib.util - -package_name = 'fcsy' -spec = importlib.util.find_spec(package_name) -if spec is None: - print( - f"{package_name} is not installed, please install {package_name} to write fcs files in the \'measure\' function!") - -package2_name = 'hdbscan' -spec2 = importlib.util.find_spec(package2_name) -if spec2 is None: - print( - f"{package2_name} is not installed, please install {package2_name} to cluster data in the \'cluster\' function!") - -package3_name = 'unidip' -spec3 = importlib.util.find_spec(package3_name) -if spec3 is None: - print( - f"{package3_name} is not installed, please install {package3_name} to perform a dip test in the \'dip_test\' " - f"function!") - -import numpy as np -import pandas as pd -import time -from fcsy.fcs import write_fcs -import hdbscan -import matplotlib.pyplot as plt -import seaborn as sns -from unidip import UniDip -from copy import deepcopy -from scipy.stats import ks_2samp -from sklearn.mixture import GaussianMixture - -# from __init__ import spectrum_data - -# Temp - init file in same directory screws up pytest run -spectrum_data = pd.read_csv( - 'data/FPbase_Spectra_updated.csv').fillna(value=0) - - -def create_controls(size, colors=('blue', 'cyan', 'green', 'yellow', 'orange', 'red', 'far_red', 'nir', 'ir')): - """ - This is a function that takes a DataFrame size (i.e. number of controls) and - a list of colors the user wants to run controls for. - - :type size: int - :param size: - :type colors: list - :param colors: 'blue', 'cyan', 'green', 'yellow', 'orange', 'red', 'far_red', 'NIR', 'IR' - :return: tuple with final control results - """ - - # Check to make sure the inputs were of correct type - if type(size) != int: - raise TypeError("size cannot be of type: " + str(type(size))) - elif type(colors) != list: - raise TypeError("Ex cannot be of type: " + str(type(colors))) - - # Controls data - accept whatever colors the user provides - controls_dict = {} - for i in colors: - controls_dict[i] = {'Wavelength': [], 'Excitation Efficiency': [], 'Emission Efficiency': []} - - # Make excitation and emission data easier to read in to dictionary - wavelengths = spectrum_data['Wavelength'] - - green_ex_efficiency = spectrum_data['Fluorescein (FITC) EX'] - red_ex_efficiency = spectrum_data['Kaede (Red) EX'] - blue_ex_efficiency = spectrum_data['Pacific Blue EX'] - far_red_ex_efficiency = spectrum_data['APC (allophycocyanin) AB'] - NIR_ex_efficiency = spectrum_data['PerCP-Cy5.5 AB'] - IR_ex_efficiency = spectrum_data['APC/Cy7 EX'] - cyan_ex_efficiency = spectrum_data['CFP EX'] - yellow_ex_efficiency = spectrum_data['EYFP EX'] - orange_ex_efficiency = spectrum_data['mOrange EX'] - - # Excitation and emission data for each color control - pre-defined information - excitation_dict = {'green': [list(wavelengths), list(green_ex_efficiency)], - 'red': [list(wavelengths), list(red_ex_efficiency)], - 'blue': [list(wavelengths), list(blue_ex_efficiency)], - 'far_red': [list(wavelengths), list(far_red_ex_efficiency)], - 'nir': [list(wavelengths), list(NIR_ex_efficiency)], - 'ir': [list(wavelengths), list(IR_ex_efficiency)], - 'cyan': [list(wavelengths), list(cyan_ex_efficiency)], - 'yellow': [list(wavelengths), list(yellow_ex_efficiency)], - 'orange': [list(wavelengths), list(orange_ex_efficiency)]} - - # Make excitation and emission data easier to read in to dictionary - green_em_efficiency = spectrum_data['Fluorescein (FITC) EM'] - red_em_efficiency = spectrum_data['Kaede (Red) EM'] - blue_em_efficiency = spectrum_data['Pacific Blue EM'] - far_red_em_efficiency = spectrum_data['APC (allophycocyanin) EM'] - nir_em_efficiency = spectrum_data['PerCP-Cy5.5 EM'] - ir_em_efficiency = spectrum_data['APC/Cy7 EM'] - cyan_em_efficiency = spectrum_data['CFP EM'] - yellow_em_efficiency = spectrum_data['EYFP EM'] - orange_em_efficiency = spectrum_data['mOrange EM'] - - # Excitation and emission data for each color control - pre-defined information - emission_dict = {'green': [list(wavelengths), list(green_em_efficiency)], - 'red': [list(wavelengths), list(red_em_efficiency)], - 'blue': [list(wavelengths), list(blue_em_efficiency)], - 'far_red': [list(wavelengths), list(far_red_em_efficiency)], - 'nir': [list(wavelengths), list(nir_em_efficiency)], - 'ir': [list(wavelengths), list(ir_em_efficiency)], - 'cyan': [list(wavelengths), list(cyan_em_efficiency)], - 'yellow': [list(wavelengths), list(yellow_em_efficiency)], - 'orange': [list(wavelengths), list(orange_em_efficiency)]} - - # Match colors that the user wants to excitation and emission data - for key, value in controls_dict.items(): - key = key.lower() # Doesn't matter if user entered capital letters or not - if key in excitation_dict: - value['Wavelength'] = [excitation_dict[key][0]] - value['Excitation Efficiency'] = [excitation_dict[key][1]] - value['Emission Efficiency'] = [emission_dict[key][1]] - - else: - raise NameError(str(key) + ' is not an available control, try: ' + - str(list(excitation_dict.keys()))) - - # Create a new dictionary that will keep the associated colors with dataframe objects - results_dict = {} - for key, value in controls_dict.items(): - results_dict[key] = pd.DataFrame(value) - - # Finally, create a list that will hold all DFs while preserving color order - final_control_results = [] - for i in colors: - final_control_results.append(pd.concat([results_dict[i]] * size, ignore_index=True)) - - for df in final_control_results: - df['Copy number'] = np.round(np.random.normal(100, size=size, scale=1)) - - # Return tuple of the list for easy access of colors - return tuple(final_control_results) - - -def create_sample(size, colors=['blue', 'cyan', 'green', 'yellow', 'orange', 'red', 'far_red', 'nir', 'ir'], - weights=[]): - """ - This is a function that takes a defined dataframe length for number of samples (int) - and excitation and emission wavelengths (list,list). Assumes equal probability of each - color unless specified by the user. - - :type colors list of strings - :param colors: ['blue', 'cyan', 'green', 'yellow', 'orange', 'red', 'far_red', 'NIR', 'IR'] - :type weights list - :param weights (e.g. [0]) - :type size int - :param size (e.g. 1000 points) - :return: pandas DataFrame - """ - - # Check to make sure the inputs were of correct type - if type(size) != int: - raise TypeError("size cannot be of type: " + str(type(size))) - elif type(colors) != list: - raise TypeError("Color list cannot be of type: " + str(type(colors))) - - # Make excitation and emission data easier to read in to dictionary - wavelengths = spectrum_data['Wavelength'] - - green_ex_efficiency = spectrum_data['Fluorescein (FITC) EX'] - red_ex_efficiency = spectrum_data['Kaede (Red) EX'] - blue_ex_efficiency = spectrum_data['Pacific Blue EX'] - far_red_ex_efficiency = spectrum_data['APC (allophycocyanin) AB'] - nir_ex_efficiency = spectrum_data['PerCP-Cy5.5 AB'] - ir_ex_efficiency = spectrum_data['APC/Cy7 EX'] - cyan_ex_efficiency = spectrum_data['CFP EX'] - yellow_ex_efficiency = spectrum_data['EYFP EX'] - orange_ex_efficiency = spectrum_data['mOrange EX'] - - # Excitation and emission data for each color control - pre-defined information - excitation_dict = {'green': [list(wavelengths), list(green_ex_efficiency)], - 'red': [list(wavelengths), list(red_ex_efficiency)], - 'blue': [list(wavelengths), list(blue_ex_efficiency)], - 'far_red': [list(wavelengths), list(far_red_ex_efficiency)], - 'nir': [list(wavelengths), list(nir_ex_efficiency)], - 'ir': [list(wavelengths), list(ir_ex_efficiency)], - 'cyan': [list(wavelengths), list(cyan_ex_efficiency)], - 'yellow': [list(wavelengths), list(yellow_ex_efficiency)], - 'orange': [list(wavelengths), list(orange_ex_efficiency)]} - - # Make excitation and emission data easier to read in to dictionary - green_em_efficiency = spectrum_data['Fluorescein (FITC) EM'] - red_em_efficiency = spectrum_data['Kaede (Red) EM'] - blue_em_efficiency = spectrum_data['Pacific Blue EM'] - far_red_em_efficiency = spectrum_data['APC (allophycocyanin) EM'] - nir_em_efficiency = spectrum_data['PerCP-Cy5.5 EM'] - ir_em_efficiency = spectrum_data['APC/Cy7 EM'] - cyan_em_efficiency = spectrum_data['CFP EM'] - yellow_em_efficiency = spectrum_data['EYFP EM'] - orange_em_efficiency = spectrum_data['mOrange EM'] - - # Excitation and emission data for each color control - pre-defined information - emission_dict = {'green': [list(wavelengths), list(green_em_efficiency)], - 'red': [list(wavelengths), list(red_em_efficiency)], - 'blue': [list(wavelengths), list(blue_em_efficiency)], - 'far_red': [list(wavelengths), list(far_red_em_efficiency)], - 'nir': [list(wavelengths), list(nir_em_efficiency)], - 'ir': [list(wavelengths), list(ir_em_efficiency)], - 'cyan': [list(wavelengths), list(cyan_em_efficiency)], - 'yellow': [list(wavelengths), list(yellow_em_efficiency)], - 'orange': [list(wavelengths), list(orange_em_efficiency)]} - - # Set dictionary to be made into DataFrame - sample_dict = {'Wavelength': [], 'Excitation Efficiency': [], 'Emission Efficiency': []} - - # Make "size" number of cell entries - for i in range(size): - if len(weights) == 0: - color_to_pick = np.random.choice(colors).lower() - else: - color_to_pick = np.random.choice(colors, p=weights).lower() - - sample_dict['Wavelength'].append(excitation_dict[color_to_pick][0]) - sample_dict['Excitation Efficiency'].append(excitation_dict[color_to_pick][1]) - sample_dict['Emission Efficiency'].append(emission_dict[color_to_pick][1]) - - data = pd.DataFrame(sample_dict) - - # Create protein copy number - copies = np.round(np.random.normal(100, size=len(data), scale=20)) - data['Copy number'] = copies - - # Return just the sample DataFrame - return data - - -# Bandwidth on lasers is +-5 nm. channels are [450+-25, 525+-25, 600+-30, 665+-15, 720+-30, 785+-30] for filter set 2 -def measure(dataframe, lasers=[405, 488, 561, 638], channels=[1, 2, 3, 4, 5, 6], - create_fcs=True, outfile_name='data/sample_output.fcs'): - """ - This is a function that will measure fluorescence intensity for any given sample - DataFrame and laser/channel parameters. Output will be an fcs file (default) that is - the same size as the sample you ran in the function. Alternatively, you can return - just a pandas DataFrame object by setting return_fcs=False. The user can set the output - file name manually to simulate creating multiple samples and measurements. - - :type lasers: list of int - :param dataframe: - :type dataframe: pandas.DataFrame - :param lasers: - :type channels list - :param channels: - :type create_fcs bool - :param create_fcs: - :param outfile_name: - :return: DataFrame and file - """ - # Bandwidth for each fluorescence channel - channels_information = {1: list(range(425, 475)), 2: list(range(500, 550)), 3: list(range(570, 630)), - 4: list(range(650, 680)), - 5: list(range(690, 750)), 6: list(range(755, 805))} - - # This is the list that will hold all of the intensity vectors for each cell - new_dataframe_list = [['FL' + str(i) for i in channels]] - - # where are our laser wavelengths in our input dataframe? - laser_indices = {} - - # For each laser, find the indices for their wavelengths and their gaussian efficiencies - for laser in lasers: - # This part makes a gaussian distribution of each laser+-5 - counts_dict = {} - gaussian_dist_of_laser = np.array(np.round(np.random.normal(loc=laser, scale=2.0, size=10000))) - new_array = [x for x in gaussian_dist_of_laser if laser + 5 >= x >= laser - 5] - - for i in new_array: - if i not in counts_dict.keys(): - counts_dict[i] = list(new_array).count(i) - - max_count = max(counts_dict.values()) - - for key, value in counts_dict.items(): - counts_dict[key] = value / max_count - - # Find the wavelength indices that our lasers hit - make a dictionary with indices as keys and laser - # efficiencies as values - for index2, wave in enumerate(dataframe['Wavelength'][0]): - if wave in counts_dict.keys(): - laser_indices[index2] = counts_dict[wave] - - # figure out unique emission profiles based on color so we know when to end the loop - copy = dataframe.copy() - copy['Emission Efficiency'] = copy['Emission Efficiency'].astype(str) - - # Create numpy arrays to randomly sample from based on the number of excited molecules - emission_reference = {} - - for index, row in dataframe.iterrows(): - if str(row['Emission Efficiency']) not in emission_reference.keys(): - waves_to_add = np.array([round(value * 100) * [row['Wavelength'][index]] for index, value in - enumerate(row['Emission Efficiency']) if value >= 0.01]) - emission_reference[str(row['Emission Efficiency'])] = np.array([y for x in waves_to_add for y in x]) - - if len(emission_reference.keys()) == len(copy['Emission Efficiency'].unique()): - break - - # for each cell that is being analyzed - for index, row in dataframe.iterrows(): - intensity_vector = [] - - # Calculate peak excitation efficiency for our cell given all lasers at once (collinear laser set up) - excitation_max = max([row['Excitation Efficiency'][key] * value for key, value in laser_indices.items()]) - num_excited_proteins = round(row['Copy number'] * excitation_max) - - # Sample emission at wavelengths corresponding to real emission efficiency from FPbase, size=number of - # excited proteins - real_emission_wavelengths = np.random.choice(emission_reference[str(row['Emission Efficiency'])], - size=num_excited_proteins) - - # amp = np.random.choice(list(range(1000,1700,40))) - # For each fluorescence channel, find the appropriate emission values - for channel in channels: - em_chan = channels_information[channel] - - # Find intensity in each channel - NOTE using intersection and set here speed up the code DRAMATICALLY - emission_intensity = len(set(real_emission_wavelengths).intersection(em_chan)) * ( - 1000 + np.random.normal(0, scale=50)) # Average amplification +- noise - - # add intensity in each channel to the vector - intensity_vector.append(float(emission_intensity)) - - new_dataframe_list.append(intensity_vector) - - column_names = new_dataframe_list.pop(0) - - # Create new DataFrame and output - output = pd.DataFrame(new_dataframe_list, columns=column_names) - - if create_fcs: - write_fcs(output, outfile_name) - print("FCS file created with filename: " + str(outfile_name)) - - return output - - -def cluster(measured_data, min_cluster_size=50, savefig=True): - """ - This is a function to cluster flow cytometry data that has been measured in fluorescence channels using - density-based spatial clustering of applications with noise (DBSCAN), which clusters based on density of points - in an unsupervised method. The number of clusters does not need to be explicitly stated by the users. The only - parameter that needs to be optimized is min_cluster_size, which is set to 50 here. But I recommend 1% of the len( - data) Resulting plots are a bar chart showing the number of cells in each cluster and a heatmap of the median - fluorescence intensity in each channel for each cluster. - - Note: clusters that are labeled '0' are cells that the DBSCAN could not cluster. - - Returns a tuple of two dictionaries. The first dictionary is the median fluorescence represented in the heatmap - while the second dictionary holds all the fluorescence vectors for each cluster. Both of these are needed - for a dip test and re-clustering. - - :rtype: tuple of dict - :type measured_data file - :param measured_data - :type min_cluster_size int - :param min_cluster_size - :type savefig bool - :param savefig - :return: - """ - - # Create the clustering object - cluster_obj = hdbscan.HDBSCAN(min_cluster_size=min_cluster_size) - - # Perform the clustering - cluster_obj.fit(measured_data) - - # Find the number of cells in each cluster - cluster_counts = {} - - # clusters are - for i in cluster_obj.labels_: - if i not in cluster_counts.keys(): - cluster_counts[str(i + 1)] = list(cluster_obj.labels_).count(i) - - X = [] - - # Make a 2d array of the vectors - for index, row in measured_data.iterrows(): - X.append([x for x in row]) - - # Make a dictionary for our clusters to hold their associated vectors - cluster_dict = {} - for cluster_num in cluster_obj.labels_: - if cluster_num not in cluster_dict.keys(): - cluster_dict[cluster_num] = [] - - # Add the vector in each cluster - for index, vector in enumerate(X): - cluster_dict[cluster_obj.labels_[index]].append(vector) - - final_dictionary = {} - - # Make a new dictionary which will have the median value for each channel in the vector for a heatmap downstream - for key, value in cluster_dict.items(): - median_values = [] - for i in range(len(value[0])): - median_values.append(np.median([row[i] for row in value])) - final_dictionary["Cluster " + str(key + 1)] = median_values - - df = pd.DataFrame(final_dictionary, index=list(measured_data.columns)) - - fig, ax = plt.subplots(1, 2, figsize=(10, 4)) - sns.heatmap(df.transpose(), cmap='copper') - - cluster_names = [] - count = [] - - for key, value in cluster_counts.items(): - cluster_names.append(key) - count.append(value) - - y_pos = np.arange(len(cluster_names)) - - ax[0].bar(y_pos, count, color='black') - ax[0].set_xticks(y_pos) - ax[0].set_xticklabels(cluster_names) - ax[0].set_xlabel('Cluster') - ax[0].set_ylabel('Counts') - ax[0].set_title('Cells per cluster') - - ax[1].set_title('Fluorescence profile of clusters') - ax[1].set_xlabel('Fluorescence channel') - plt.yticks(rotation=0) - plt.tight_layout() - - if savefig: - plt.savefig("preliminary_clustering") - - return (final_dictionary, cluster_dict) - - -def dip_test(median_FL_data, total_data, alpha=0.05, save_figure=True): - """ - Perform a Hartigan's dip test to check for unimodality in clusters and splits clusters if bimodality is found. - This function will take the highest intensity channel for each cluster and - check for bimodality to correct for errors in clustering similar fluorescencep profiles. - Changing alpha will alter how stringent the dip test is. A higher alpha will result in higher detection - of bimodality, but runs a greater risk of false identification. It is important to note - that this dip test is relatively coarse grained and will not identify very slight populations - of mixed cells (e.g. 10 orange cells clustered with 1000 red cells) - - Returns an updated clustering of the primary clustering after performing a dip test - """ - - # Create a copy of the dictionary so we can retain the original clustering data - change_dict = deepcopy(total_data) - - # Make kde plots - if 'Cluster 0' in median_FL_data.keys(): - fig, ax = plt.subplots(1, len(median_FL_data.keys()) - 1, figsize=(12, 3)) - - else: - fig, ax = plt.subplots(1, len(median_FL_data.keys()), figsize=(12, 3)) - - # Keep track of what plot we're on - i = 0 - - # Get the index of the max fluorescence for each cluster - for key, value in median_FL_data.items(): - cluster_max_FL_index = np.argmax(value) - - # As long as we aren't cluster one, do our dip test and plot - if int(key[-1]) - 1 != -1: - search_key = int(key[-1]) - 1 - - # Intensity in each cluster where the intensity is max - dat = [row[cluster_max_FL_index] for row in total_data[search_key]] - - # Do the dip test - data = np.msort(dat) - intervals = UniDip(data, alpha=alpha).run() - print("Performing dip test on cluster " + str(search_key + 1) + " ... ") - - # Show on the graph where the intervals are - for j in intervals: - ax[i].axvspan(data[j[0]], data[j[1]], color='lightblue', alpha=0.4) - for q in j: - ax[i].axvline(data[q], color='red') - - # Split the clusters that failed the dip test into separate clusters - if len(intervals) > 1: - split_point = int(np.mean([intervals[0][1], intervals[1][0]])) - clust1 = data[:split_point] - clust2 = data[split_point:] - - # Reset current cluster number to cluster 1 and make a new cluster to the dictionary - print("Identified bimodality in cluster " + str(search_key + 1) + ", reclustering data ... ") - change_dict[max(total_data.keys()) + 1] = [row for row in total_data[search_key] if - row[cluster_max_FL_index] in clust2] - change_dict[search_key] = [row for row in total_data[search_key] if row[cluster_max_FL_index] in clust1] - - # Plot data - sns.kdeplot(data, ax=ax[i], color='black') - - ax[i].set(title='Cluster ' + str(search_key + 1), xlabel='FL ' + str(cluster_max_FL_index + 1), yticks=[]) - - # Move to the next plot - i += 1 - - plt.tight_layout() - - # save first figure of the dip test - if save_figure: - plt.savefig("Dip_test_example") - - final_reclustered = {} - - # Make a new dictionary which will have the median value for each channel in the vector for a heatmap downstream - for key, value in change_dict.items(): - med_values = [] - for i in range(len(value[0])): - med_values.append(np.median([row[i] for row in value])) - final_reclustered["Cluster " + str(key + 1)] = med_values - - search = np.random.choice(list(median_FL_data.keys())) - - cols = ['FL' + str(i + 1) for i in range(len(median_FL_data[search]))] - - # Dataframe to create heatmap - reclustered_df = pd.DataFrame(final_reclustered, index=cols) - - # Counts dictionary for barchart - reclustered_counts = {} - - for key, value in change_dict.items(): - reclustered_counts[key] = len(value) - - # Replot the new clusters - print("Plotting reclustered data ...") - - fig2, ax = plt.subplots(1, 2, figsize=(10, 4)) - sns.heatmap(reclustered_df.transpose(), cmap='copper') - - reclust = [] - recount = [] - - for key, value in reclustered_counts.items(): - reclust.append(int(key) + 1) - recount.append(value) - - rey_pos = np.arange(len(reclust)) - - ax[0].bar(rey_pos, recount, color='black') - ax[0].set_xticks(rey_pos) - ax[0].set_xticklabels(reclust) - ax[0].set_xlabel('Cluster') - ax[0].set_ylabel('Counts') - ax[0].set_title('Cells per cluster') - - ax[1].set_title('Fluorescence profile of clusters') - ax[1].set_xlabel('Fluorescence channel') - plt.yticks(rotation=0) - plt.tight_layout() - - if save_figure: - plt.savefig("reclustered_after_dip_test") - - return change_dict - - - -def gaus_recluster(median_FL_data,total_data,tolerance=.25,savefig=True): - """ - Applies a gaussian mixture model with n_components=2 - to try and separate rare populations of cells from - the original clustering. This will apply the model - and then conduct a Kolmogorov-Smirnov 2 sample test - to assess significant differences in distributions of - the split clusters. Two criteria are used to determine - whether a cluster is saved as split, or if it is preserved - as it originally was: - - P-value of Ks2 test: If p-value is below 1e-10 - - Difference in cluster size: if a cluster is split - and the difference between the sizes of the new clusters - is greater than of the total cells in the original - cluster. - - parameters: - median_FL_data - data with median FL for each cluster - - total_data - data with all measured FL for each cluster - - tolerance - how different do the sizes of clusters have to - be before they are considered actually distinct spectrally? - Increase this to be more stringent in splitting clusters. - Decrease the value to allow more reclustering at the cost of - false positives. - - savefig - save figures - - returns: - reclustered - reclustered dataset of all cells analyzed - - """ - index_max = {} - - # Get the max FL channel index for each cluster that is not 0 (i.e. unclustered) - for key, value in median_FL_data.items(): - if key[-1] !='0': - index_max[int(key[-1])-1] = np.argmax(value) - - - fig, ax = plt.subplots(1,len(list(index_max.keys())),figsize=(12,3)) - - # create a copy of the input data to preserve new and old datasets - reclustered = deepcopy(total_data) - - i = 0 - for key,value in total_data.items(): - if key != -1: - - # Max fluorescence channel for each cluster - max_channel = index_max[key] - - # Apply a gaussian mixture model and split into 2 components - gmm = GaussianMixture(n_components=2) - gmm.fit(value) - - # Label each cell in our clusters with the label for how they split - labels = gmm.predict(value) - - # Create a dataframe of the intensity vectors and their new cluster after the split - frame = pd.DataFrame(value) - frame['cluster'] = labels - - # subset dataframe based on new cluster number - pre_clust1 = frame[frame['cluster']==0] - pre_clust2 = frame[frame['cluster']==1] - - # Remove the cluster column. Probably redundant to do things this way - clust1 = pre_clust1[pre_clust1.columns[:-1]] - clust2 = pre_clust2[pre_clust2.columns[:-1]] - - # Do a ks 2 test to see if clusters are different - result = ks_2samp(clust1[max_channel],clust2[max_channel]) - - # Test how different our cluster populations are. If the difference between the sizes is more than , of the - # total, then we'll say we actually found a bimodal population to split - clust_split = abs(len(clust1)-len(clust2))/(len(clust1)+len(clust2)) - - - # Keep the split clusters if they meet our splitting criteria, otherwise retain original clusters from DB scan - if clust_split > tolerance: - if result[1] < 1e-10: - new_val = clust1.values.tolist() - new_val2 = clust2.values.tolist() - - - reclustered[key] = new_val - - reclustered[max(total_data.keys())+1] = new_val2 - - # Provide kde plots of the distributions to show which ones might - sns.kdeplot(clust1[max_channel],ax=ax[i],color='crimson') - sns.kdeplot(clust2[max_channel],ax=ax[i],color='navy') - ax[i].get_legend().remove() - ax[i].set_title("Cluster " + str(key+1) + ' split') - - i += 1 - - - - plt.tight_layout() - - if savefig: - plt.savefig('gaus_mix_cluster_split') - - - final_reclustered = {} - - # Make a new dictionary which will have the median value for each channel in the vector for a heatmap downstream - for key, value in reclustered.items(): - med_values = [] - for i in range(len(value[0])): - med_values.append(np.median([row[i] for row in value])) - final_reclustered["Cluster " + str(key+1)] = med_values - - - # Create a list of column names of the vector (FL1-6) - search = np.random.choice(list(median_FL_data.keys())) - cols = ['FL' + str(i + 1) for i in range(len(median_FL_data[search]))] - - - # Dataframe to create heatmap - reclustered_df = pd.DataFrame(final_reclustered,index=cols) - - - # Counts dictionary for barchart - reclustered_counts = {} - - for key,value in reclustered.items(): - reclustered_counts[key] = len(value) - - - # Replot the new clusters - print("Plotting reclustered data ...") - - fig2, ax = plt.subplots(1,2,figsize=(10,4)) - sns.heatmap(reclustered_df.transpose(),cmap='copper') - - reclust = [] - recount = [] - - for key, value in reclustered_counts.items(): - reclust.append(int(key)+1) - recount.append(value) - - rey_pos = np.arange(len(reclust)) - - ax[0].bar(rey_pos,recount,color='black') - ax[0].set_xticks(rey_pos) - ax[0].set_xticklabels(reclust) - ax[0].set_xlabel('Cluster') - ax[0].set_ylabel('Counts') - ax[0].set_title('Cells per cluster') - - ax[1].set_title('Fluorescence profile of clusters') - ax[1].set_xlabel('Fluorescence channel') - plt.yticks(rotation=0) - plt.tight_layout() - - if savefig: - plt.savefig('reclustered_after_gaus_mix_ks2') - - return reclustered - - - - diff --git a/flowsym/__init__.py b/flowsym/__init__.py new file mode 100644 index 0000000..0c3d049 --- /dev/null +++ b/flowsym/__init__.py @@ -0,0 +1,5 @@ +"""Top-level package for flowsym.""" + +__author__ = """Michael M. Shavlik; Luis Perez Morales""" +__email__ = 'mshavlik@uoregon.edu; lperezmo@uoregon.edu' +__version__ = '0.1.0' diff --git a/flowsym/cli.py b/flowsym/cli.py new file mode 100644 index 0000000..bdb4fc2 --- /dev/null +++ b/flowsym/cli.py @@ -0,0 +1,16 @@ +"""Console script for flowsym.""" +import sys +import click + + +@click.command() +def main(args=None): + """Console script for flowsym.""" + click.echo("Replace this message by putting your code into " + "flowsym.cli.main") + click.echo("See click documentation at https://click.palletsprojects.com/") + return 0 + + +if __name__ == "__main__": + sys.exit(main()) # pragma: no cover diff --git a/data/FPbase_Spectra.csv b/flowsym/data/FPbase_Spectra.csv similarity index 100% rename from data/FPbase_Spectra.csv rename to flowsym/data/FPbase_Spectra.csv diff --git a/data/FPbase_Spectra_updated.csv b/flowsym/data/FPbase_Spectra_updated.csv similarity index 100% rename from data/FPbase_Spectra_updated.csv rename to flowsym/data/FPbase_Spectra_updated.csv diff --git a/data/sample_output.fcs b/flowsym/data/sample_output.fcs similarity index 100% rename from data/sample_output.fcs rename to flowsym/data/sample_output.fcs diff --git a/flowsym/flowsym.py b/flowsym/flowsym.py new file mode 100644 index 0000000..dd0b80e --- /dev/null +++ b/flowsym/flowsym.py @@ -0,0 +1 @@ +"""Main module.""" diff --git a/requirements.txt b/requirements.txt index 38982bd..821e2b2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,8 +1,12 @@ -numpy~=1.18.1 -pandas~=1.0.1 -fcsy~=0.3.1 -pytest~=5.4.2 -matplotlib~=3.1.3 -seaborn~=0.10.0 +pytest~=6.0.1 +click~=7.1.2 +numpy~=1.15.4 +pandas~=0.23.4 hdbscan~=0.8.26 -unidip~=0.1.1 \ No newline at end of file +matplotlib~=3.0.2 +seaborn~=0.9.0 +fcsy~=0.4.0 +unidip~=0.1.1 +scipy~=1.1.0 +scikit-learn~=0.20.1 +setuptools~=49.6.0 diff --git a/requirements_dev.txt b/requirements_dev.txt new file mode 100644 index 0000000..283f5d5 --- /dev/null +++ b/requirements_dev.txt @@ -0,0 +1,12 @@ +pip==19.2.3 +bump2version==0.5.11 +wheel==0.33.6 +watchdog==0.9.0 +flake8==3.7.8 +tox==3.14.0 +coverage==4.5.4 +Sphinx==1.8.5 +twine==1.14.0 +Click==7.0 +pytest==4.6.5 +pytest-runner==5.1 \ No newline at end of file diff --git a/setup.cfg b/setup.cfg new file mode 100644 index 0000000..7f96b19 --- /dev/null +++ b/setup.cfg @@ -0,0 +1,26 @@ +[bumpversion] +current_version = 0.1.0 +commit = True +tag = True + +[bumpversion:file:setup.py] +search = version='{current_version}' +replace = version='{new_version}' + +[bumpversion:file:flowsym/__init__.py] +search = __version__ = '{current_version}' +replace = __version__ = '{new_version}' + +[bdist_wheel] +universal = 1 + +[flake8] +exclude = docs + +[aliases] +# Define setup.py command aliases here +test = pytest + +[tool:pytest] +collect_ignore = ['setup.py'] + diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..6393ce3 --- /dev/null +++ b/setup.py @@ -0,0 +1,53 @@ +#!/usr/bin/env python + +"""The setup script.""" + +from setuptools import setup, find_packages + +with open('README.rst') as readme_file: + readme = readme_file.read() + +with open('HISTORY.rst') as history_file: + history = history_file.read() + +requirements = ['Click>=7.0', ] + +setup_requirements = ['pytest-runner', ] + +test_requirements = ['pytest>=3', ] + +setup( + author="Michael M. Shavlik; Luis Perez Morales", + author_email='mshavlik@uoregon.edu; lperezmo@uoregon.edu', + python_requires='>=3.5', + classifiers=[ + 'Development Status :: 2 - Pre-Alpha', + 'Intended Audience :: Developers', + 'License :: OSI Approved :: MIT License', + 'Natural Language :: English', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.5', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + ], + description="A Python API for simulating flow cytometry data", + entry_points={ + 'console_scripts': [ + 'flowsym=flowsym.cli:main', + ], + }, + install_requires=requirements, + license="MIT license", + long_description=readme + '\n\n' + history, + include_package_data=True, + keywords='flowsym', + name='flowsym', + packages=find_packages(include=['flowsym', 'flowsym.*']), + setup_requires=setup_requirements, + test_suite='tests', + tests_require=test_requirements, + url='https://github.com/mshavlik; lperezmo/flowsym', + version='0.1.0', + zip_safe=False, +) diff --git a/test_flowsym.py b/test_flowsym.py deleted file mode 100644 index ba2ce2c..0000000 --- a/test_flowsym.py +++ /dev/null @@ -1,76 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Created on Thu Apr 2 11:29:28 2020 - -:author: Michael -:author: Luis -""" - -import pytest -import flowsym -import pandas as pd -import numpy as np - - -def test_create_controls(): - """ - Test the create_controls function to make sure that we created - all of our control DataFrames correctly - """ - - greens, reds = flowsym.create_controls(10, ['green', 'red']) # Params for test function - - assert len(greens) == 10 # Did we output dataframe of correct size? - assert type(reds) == type(pd.DataFrame()) # Did we output an actual dataframe object? - assert list(greens.columns) == ['Wavelength', 'Excitation Efficiency', - 'Emission Efficiency'] # Did we make the right columns? - - # Check to make sure wavelengths are equal - for index, val in greens.iterrows(): - assert val['Wavelength'] == reds['Wavelength'][index] - assert val['Excitation Efficiency'] != reds['Excitation Efficiency'][index] - assert val['Emission Efficiency'] != reds['Emission Efficiency'][index] - - # Make sure all excitation or emission efficiencies are the same in a given dataframe - assert greens['Excitation Efficiency'][0] == greens['Excitation Efficiency'][ - np.random.choice(range(1, len(greens)))] - assert reds['Emission Efficiency'][0] == reds['Emission Efficiency'][np.random.choice(range(1, len(reds)))] - - -def test_create_sample(): - """ - Test the create sample function to make sure we made our sample DataFrames correctly - """ - sample = flowsym.create_sample(10, ['blue', 'green', 'NIR']) # Params for test function - - assert len(sample) == 10 # Is dataframe correct size from input step? - assert type(sample) == type(pd.DataFrame()) # Did we actually output a dataframe? - assert list(sample.columns) == ['Wavelength', 'Excitation Efficiency', 'Emission Efficiency', - 'Copy number'] # Are these the columns? - - # Check to make sure excitation wavelengths aren't the same as emission - for index, val in sample.iterrows(): - assert val['Excitation Efficiency'] != val['Emission Efficiency'] - - -# Now that we've tested the create sample function, make a fixture for following function tests -@pytest.fixture() -def sample(): - dataframe = flowsym.create_sample(100) - - return dataframe - - -# Now that we've tested the create controls function, make a fixture for following function tests -@pytest.fixture() -def controls(): - blue, green, red, far_red, NIR, IR = flowsym.create_controls(100) - - return blue, green, red, far_red, NIR, IR - - -def test_measure(sample): - measured = flowsym.measure(sample) - - assert len(list(measured.columns)) == 6 - assert type(measured) == type(pd.DataFrame()) diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..b279c39 --- /dev/null +++ b/tests/__init__.py @@ -0,0 +1 @@ +"""Unit test package for flowsym.""" diff --git a/tests/data/FPbase_Spectra.csv b/tests/data/FPbase_Spectra.csv new file mode 100644 index 0000000..cb586b6 --- /dev/null +++ b/tests/data/FPbase_Spectra.csv @@ -0,0 +1,552 @@ +"Wavelength","Pacific Blue EM","Pacific Blue EX","Fluorescein (FITC) EX","Kaede (Red) EM","Kaede (Red) EX","APC (allophycocyanin)","PerCP-Cy5.5","APC (allophycocyanin) EM","Fluorescein (FITC) EM","PerCP-Cy5.5 EM","APC/Cy7 EM","APC/Cy7 EX" +300,,0.239,0.5364 +301,,0.2043,0.5057 +302,,0.1699,0.4783 +303,,0.1429,0.4507 +304,,0.1206,0.4301 +305,,0.1059,0.4099 +306,,0.0895,0.3941 +307,,0.0842,0.3839 +308,,0.0782,0.3712 +309,,0.0706,0.3608 +310,,0.0651,0.3644 +311,,0.0636,0.357,,0.2498 +312,,0.0615,0.3537,,0.2555 +313,,0.0598,0.3561,,0.2603 +314,,0.0587,0.3496,,0.2665 +315,,0.0574,0.3468,,0.273 +316,,0.0583,0.3397,,0.2772 +317,,0.058,0.3387,,0.2849 +318,,0.056,0.3299,,0.2924 +319,,0.0568,0.3225,,0.302 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+843,,,,,,,,,,0.0228,0.152 +844,,,,,,,,,,0.0224,0.146 +845,,,,,,,,,,0.0221 +846,,,,,,,,,,0.0219 +847,,,,,,,,,,0.0218 +848,,,,,,,,,,0.0217 +849,,,,,,,,,,0.0217 +850,,,,,,,,,,0.0213 \ No newline at end of file diff --git a/tests/data/FPbase_Spectra_updated.csv b/tests/data/FPbase_Spectra_updated.csv new file mode 100644 index 0000000..f011908 --- /dev/null +++ b/tests/data/FPbase_Spectra_updated.csv @@ -0,0 +1,552 @@ +"Wavelength","Fluorescein (FITC) EM","EYFP EM","mOrange EM","Kaede (Red) EM","Kaede (Red) EX","CFP EX","CFP EM","EYFP EX","mOrange EX","Pacific Blue EX","Pacific Blue EM","Fluorescein (FITC) EX","APC (allophycocyanin) AB","APC (allophycocyanin) EM","PerCP-Cy5.5 AB","PerCP-Cy5.5 EM","APC/Cy7 EX","APC/Cy7 EM" +300,,,,,,,,,0.1508,0.239,,0.5364 +301,,,,,,,,,0.1395,0.2043,,0.5057 +302,,,,,,0.8529,,,0.1303,0.1699,,0.4783 +303,,,,,,0.8502,,,0.1222,0.1429,,0.4507 +304,,,,,,0.8474,,,0.115,0.1206,,0.4301 +305,,,,,,0.8398,,,0.1097,0.1059,,0.4099 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+import pytest + +from click.testing import CliRunner + +from flowsym import flowsym +from flowsym import cli + + +@pytest.fixture +def response(): + """Sample pytest fixture. + + See more at: http://doc.pytest.org/en/latest/fixture.html + """ + # import requests + # return requests.get('https://github.com/audreyr/cookiecutter-pypackage') + + +def test_content(response): + """Sample pytest test function with the pytest fixture as an argument.""" + # from bs4 import BeautifulSoup + # assert 'GitHub' in BeautifulSoup(response.content).title.string + + +def test_command_line_interface(): + """Test the CLI.""" + runner = CliRunner() + result = runner.invoke(cli.main) + assert result.exit_code == 0 + assert 'flowsym.cli.main' in result.output + help_result = runner.invoke(cli.main, ['--help']) + assert help_result.exit_code == 0 + assert '--help Show this message and exit.' in help_result.output diff --git a/tox.ini b/tox.ini new file mode 100644 index 0000000..76dbb17 --- /dev/null +++ b/tox.ini @@ -0,0 +1,27 @@ +[tox] +envlist = py35, py36, py37, py38, flake8 + +[travis] +python = + 3.8: py38 + 3.7: py37 + 3.6: py36 + 3.5: py35 + +[testenv:flake8] +basepython = python +deps = flake8 +commands = flake8 flowsym tests + +[testenv] +setenv = + PYTHONPATH = {toxinidir} +deps = + -r{toxinidir}/requirements_dev.txt +; If you want to make tox run the tests with the same versions, create a +; requirements.txt with the pinned versions and uncomment the following line: +; -r{toxinidir}/requirements.txt +commands = + pip install -U pip + pytest --basetemp={envtmpdir} +