Merge pull request #84 from KrishnaswamyLab/dev

scprep v1.0.0

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,36 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: bug
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Standalone code to reproduce the behavior:
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Actual behavior**
+Include full traceback if applicable.
+
+**scprep version**
+Output of `scprep.__version__`
+
+**Output of `pd.show_versions()`**
+
+<details>
+
+```
+paste pd.show_versions() here
+```
+
+</details>
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,20 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: enhancement
+assignees: ''
+
+---
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or code snippets related to the feature request here.

.travis.yml

@@ -17,6 +17,10 @@
         - gfortran
         - libblas-dev
         - liblapack-dev
+        - libglu1-mesa-dev
+        - freeglut3-dev
+        - mesa-common-dev
+        - libgsl-dev
 
   cache: 
     - pip
@@ -25,7 +29,7 @@
       - $HOME/R/Library
 
   install:
-    - python setup.py install
+    - pip install -U .
 
   before_script:
     - sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9

CODE_OF_CONDUCT.md

@@ -0,0 +1,76 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+ advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+ address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+ professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at [email protected]. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

CONTRIBUTING.md

@@ -0,0 +1,32 @@
+
+Contributing to scprep
+============================
+
+There are many ways to contribute to `scprep`, with the most common ones
+being contribution of code or documentation to the project. Improving the
+documentation is no less important than improving the library itself. If you
+find a typo in the documentation, or have made improvements, do not hesitate to
+submit a GitHub pull request.
+
+But there are many other ways to help. In particular answering queries on the
+[issue tracker](https://github.com/KrishnaswamyLab/scprep/issues),
+investigating bugs, and [reviewing other developers' pull
+requests](https://github.com/KrishnaswamyLab/scprep/pulls)
+are very valuable contributions that decrease the burden on the project
+maintainers.
+
+Another way to contribute is to report issues you're facing, and give a "thumbs
+up" on issues that others reported and that are relevant to you. It also helps
+us if you spread the word: reference the project from your blog and articles,
+link to it from your website, or simply star it in GitHub to say "I use it".
+
+Code of Conduct
+---------------
+
+We abide by the principles of openness, respect, and consideration of others
+of the Python Software Foundation: https://www.python.org/psf/codeofconduct/.
+
+Attribution
+---------------
+
+This `CONTRIBUTING.md` was adapted from [scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md).

README.rst

@@ -1,6 +1,5 @@
-=============
-scprep
-=============
+.. image:: logo.png
+    :alt: scprep logo
 
 .. image:: https://img.shields.io/pypi/v/scprep.svg
     :target: https://pypi.org/project/scprep/
@@ -24,8 +23,14 @@ scprep
     :target: https://github.com/KrishnaswamyLab/scprep/
     :alt: GitHub stars
 
+`scprep` provides an all-in-one framework for loading, preprocessing, and plotting matrices in Python, with a focus on single-cell genomics.
 
-Tools for loading and preprocessing biological matrices in Python.
+The philosophy of `scprep`:
+
+* Data shouldn't be hidden in a complex and bespoke class object. `scprep` works with `numpy` arrays, `pandas` data frames, and `scipy` sparse matrices, all of which are popular data formats in Python and accepted as input to most common algorithms.
+* Your analysis pipeline shouldn't have to change based on data format. Changing from a `numpy` array to a `pandas` data frame introduces endless technical differences (e.g. in indexing matrices). `scprep` provides data-agnostic methods that work the same way on all formats.
+* Simple analysis should mean simple code. `scprep` takes care of annoying edge cases and sets nice defaults so you don't have to.
+* Using a framework shouldn't be limiting. Because nothing is hidden from you, you have access to the power of `numpy`, `scipy`, `pandas` and `matplotlib` just as you would if you used them directly.
 
 Installation
 ------------
@@ -72,4 +77,4 @@ Examples
 Help
 ----
 
-If you have any questions or require assistance using scprep, please read the documentation at https://scprep.readthedocs.io/ or contact us at https://krishnaswamylab.org/get-help
+If you have any questions or require assistance using scprep, please read the documentation at https://scprep.readthedocs.io/ or contact us at https://krishnaswamylab.org/get-help

doc/source/index.rst

@@ -1,6 +1,6 @@
-===========================================================================
-scprep
-===========================================================================
+.. raw:: html
+
+    <a href="https://github.com/KrishnaswamyLab/scprep/"><img src="https://raw.githubusercontent.com/KrishnaswamyLab/scprep/dev/logo.png" alt="scprep logo"></a><br>
 
 .. raw:: html
 
@@ -26,7 +26,14 @@ scprep
 
     <a href="https://github.com/KrishnaswamyLab/scprep/"><img src="https://img.shields.io/github/stars/KrishnaswamyLab/scprep.svg?style=social&label=Stars" alt="GitHub stars"></a>
 
-Tools for building and manipulating graphs in Python.
+`scprep` provides an all-in-one framework for loading, preprocessing, and plotting matrices in Python, with a focus on single-cell genomics.
+
+The philosophy of `scprep`:
+
+* Data shouldn't be hidden in a complex and bespoke class object. `scprep` works with `numpy` arrays, `pandas` data frames, and `scipy` sparse matrices, all of which are popular data formats in Python and accepted as input to most common algorithms.
+* Your analysis pipeline shouldn't have to change based on data format. Changing from a `numpy` array to a `pandas` data frame introduces endless technical differences (e.g. in indexing matrices). `scprep` provides data-agnostic methods that work the same way on all formats.
+* Simple analysis should mean simple code. `scprep` takes care of annoying edge cases and sets nice defaults so you don't have to.
+* Using a framework shouldn't be limiting. Because nothing is hidden from you, you have access to the power of `numpy`, `scipy`, `pandas` and `matplotlib` just as you would if you used them directly.
 
 .. toctree::
     :maxdepth: 2
@@ -63,4 +70,4 @@ You can use `scprep` with your single cell data as follows::
 Help
 ====
 
-If you have any questions or require assistance using scprep, please contact us at https://krishnaswamylab.org/get-help
+If you have any questions or require assistance using scprep, please contact us at https://krishnaswamylab.org/get-help

doc/source/reference.rst

@@ -11,6 +11,24 @@ Data Input/Output
     :imported-members:
     :show-inheritance:
 
+HDF5
+~~~~
+
+.. automodule:: scprep.io.hdf5
+    :autosummary:
+    :members:
+    :inherited-members:
+    :show-inheritance:
+
+Download
+~~~~~~~~
+
+.. automodule:: scprep.io.download
+    :autosummary:
+    :members:
+    :inherited-members:
+    :show-inheritance:
+
 Filtering
 ---------
 
@@ -103,10 +121,19 @@ External Tools
     :imported-members:
     :show-inheritance:
 
-HDF5
-----
+Splatter
+~~~~~~~~
 
-.. automodule:: scprep.io.hdf5
+.. automodule:: scprep.run.splatter
+    :autosummary:
+    :members:
+    :inherited-members:
+    :show-inheritance:
+
+Slingshot
+~~~~~~~~~
+
+.. automodule:: scprep.run.slingshot
     :autosummary:
     :members:
     :inherited-members:

doc/source/requirements.txt

@@ -1,9 +1,9 @@
-numpy>=1.10.0
-scipy>=0.18.0
+numpy>=1.12.0
+scipy>=0.18.1
 scikit-learn>=0.19.1
-pandas>=0.19.0,<0.24
-decorator
-matplotlib
+pandas>=0.25
+decorator>=4.3.0
+matplotlib>=3.0
 sphinx<=1.8.5
 sphinxcontrib-napoleon
 autodocsumm

requirements.txt

@@ -1,5 +1,5 @@
-numpy>=1.10.0
-scipy>=0.18.0
+numpy>=1.12.0
+scipy>=0.18.1
 scikit-learn>=0.19.1
-pandas>=0.19.0,<0.24
+pandas>=0.25
 decorator>=4.3.0

scprep/__init__.py

@@ -15,11 +15,13 @@
 import scprep.reduce
 import scprep.run
 
-import pandas as _pd
-if int(_pd.__version__.split(".")[1]) < 24:
-    import numpy as _np
-
-    def __rmatmul__(self, other):
-        """ Matrix multiplication using binary `@` operator in Python>=3.5 """
-        return self.dot(_np.transpose(other))
-    _pd.core.series.Series.__rmatmul__ = __rmatmul__
+import pandas as pd
+if int(pd.__version__.split('.')[1]) < 26:
+    def fill_value(self):
+        # Used in reindex_indexer
+        try:
+            return self.values.dtype.fill_value
+        except AttributeError:
+            return self.values.dtype.na_value
+    from pandas.core.internals.blocks import ExtensionBlock
+    setattr(ExtensionBlock, 'fill_value', property(fill_value))

scprep/_lazyload.py

@@ -14,7 +14,8 @@
              'rinterface',
              {'rinterface_lib': ['callbacks']}],
     'h5py': [],
-    'tables': []
+    'tables': [],
+    'statsmodels': [{'nonparametric': ['smoothers_lowess']}],
 }