| Name | icikt JSON |
| Version |
1.5.3
JSON |
| download |
| home_page | None |
| Summary | Python tool to calculate the KendallTau correlation coefficients. |
| upload_time | 2024-08-30 18:35:03 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | A modified Clear BSD License Copyright (c) 2021, Praneeth S. Bhatt, Robert M. Flight, Hunter N.B. Moseley All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below) provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. * If the source code is used in a published work, then proper citation of the source code must be included with the published work. NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
icikendalltau
missing values
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
numpy
scipy
docopt
Cython
sphinx_rtd_theme
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
icikt
=====
Description
--------------
The ``icikt`` package handles missing data before calculating a correlation
between datasets for variables. The missing values are treated as information from a
left-centered distribution perspective and are included in the calculation of concordant
and discordant pairs used in calculating the correlation value.
Full API documentation, user guide, and tutorial can be found on Github_Pages_
Installation
--------------
The ``icikt`` package runs under Python 3.8+. Use pip_ to install.
Starting with Python 3.4, pip_ is included by default.
Install on Linux, Mac OS X
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code:: bash
python3 -m pip install icikt
Install on Windows
~~~~~~~~~~~~~~~~~~
.. code:: bash
py -3 -m pip install icikt
Upgrade on Linux, Mac OS X
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code:: bash
python3 -m pip install icikt --upgrade
Upgrade on Windows
~~~~~~~~~~~~~~~~~~
.. code:: bash
py -3 -m pip install icikt --upgrade
Get the source code
~~~~~~~~~~~~~~~~~~~
Code is available on GitHub: https://github.com/MoseleyBioinformaticsLab/icikt
To clone the repo, first make sure you have git_ installed:
.. code:: bash
git clone https://github.com/MoseleyBioinformaticsLab/icikt.git
Dependencies
~~~~~~~~~~~~
The ``icikt`` package depends on several Python libraries:
* docopt_ for a command line interface.
* scipy_ and numpy_ for mathmatical calculations.
* Cython_ for optimized performance.
NOTE- NumPy and Cython must be preinstalled in order for this package to work.
The ``pip`` command will install all dependencies automatically, but if you wish to install them manually, run the following commands:
* docopt for a command line interface
* To install the docopt Python library run the following:
.. code:: bash
python3 -m pip install docopt # On Linux, Mac OS X
py -3 -m pip install docopt # On Windows
* scipy for performing the kendall-tau calculations
* To install the scipy Python library run the following:
.. code:: bash
python3 -m pip install scipy # On Linux, Mac OS X
py -3 -m pip install scipy # On Windows
* numpy for creating and modifying ndarrays of data
* To install numpy run the following:
.. code:: bash
python3 -m pip install numpy # On Linux, Mac OS X
py -3 -m pip install numpy # On Windows
* Cython for the cythonized kendall_dis method
* To install the Cython Python library run the following:
.. code:: bash
python3 -m pip install Cython # On Linux, Mac OS X
py -3 -m pip install Cython # On Windows
WARNING- If the following pip error message is generated, then the python3 devel package must be installed:
.. code:: bash
"fatal error: Python.h: No such file or directory"
Basic usage
-----------
To use the ``icikt`` package, input a 2d array with n columns each representing
an array of data for a variable. The `iciktArray` will return two n x n 2d arrays for correlations and p-values.
Each element will correspond to the result of a combination of two columns in the input array. iciktArray can also
be called from the command-line interface given the file path for the data along with several optional parameters(more in docs/tutorial).
Running through command line :
.. code:: bash
icikt iciktArray /path/to/file.tsv --data-format=tsv --replace=None
Running through python script :
.. code:: python
import numpy as np
import icikt
dataArray = np.genfromtxt('/path/to/file.tsv', delimiter="\t")
# or with random values
dataArray = np.random.randn(100, 2)
# running just 2 arrays with icikt
corr, pVal, tMax = icikt.icikt(dataArray[:,0], dataArray[:,1])
# running all combinations with iciktArray
scaled, corrRaw, pVals, tauMax = icikt.iciktArray(dataArray)
License
-------
A modified Clear BSD License
Copyright (c) 2021, Praneeth S. Bhatt, Robert M. Flight, Hunter N.B. Moseley
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted (subject to the limitations in the disclaimer
below) provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its contributors may be used
to endorse or promote products derived from this software without specific
prior written permission.
* If the source code is used in a published work, then proper citation of the source
code must be included with the published work.
NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS
LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
DAMAGE.
.. _Github_Pages: https://moseleybioinformaticslab.github.io/icikt/
.. _pip: https://pip.pypa.io/
.. _git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git/
.. _numpy: http://www.numpy.org/
.. _scipy: https://scipy.org/scipylib/index.html
.. _docopt: http://docopt.org/
.. _Cython: https://cython.org/
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"description": "icikt\n=====\n\nDescription\n--------------\nThe ``icikt`` package handles missing data before calculating a correlation\nbetween datasets for variables. The missing values are treated as information from a \nleft-centered distribution perspective and are included in the calculation of concordant\nand discordant pairs used in calculating the correlation value.\n\nFull API documentation, user guide, and tutorial can be found on Github_Pages_\n\nInstallation\n--------------\nThe ``icikt`` package runs under Python 3.8+. Use pip_ to install.\nStarting with Python 3.4, pip_ is included by default.\n\n\nInstall on Linux, Mac OS X\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code:: bash\n\n python3 -m pip install icikt\n\n\nInstall on Windows\n~~~~~~~~~~~~~~~~~~\n\n.. code:: bash\n\n py -3 -m pip install icikt\n\n\nUpgrade on Linux, Mac OS X\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code:: bash\n\n python3 -m pip install icikt --upgrade\n\n\nUpgrade on Windows\n~~~~~~~~~~~~~~~~~~\n\n.. code:: bash\n\n py -3 -m pip install icikt --upgrade\n\n\n\nGet the source code\n~~~~~~~~~~~~~~~~~~~\nCode is available on GitHub: https://github.com/MoseleyBioinformaticsLab/icikt\n\nTo clone the repo, first make sure you have git_ installed:\n\n.. code:: bash\n\n git clone https://github.com/MoseleyBioinformaticsLab/icikt.git\n\n\nDependencies\n~~~~~~~~~~~~\nThe ``icikt`` package depends on several Python libraries:\n * docopt_ for a command line interface.\n * scipy_ and numpy_ for mathmatical calculations.\n * Cython_ for optimized performance.\n\nNOTE- NumPy and Cython must be preinstalled in order for this package to work.\n\nThe ``pip`` command will install all dependencies automatically, but if you wish to install them manually, run the following commands:\n \n * docopt for a command line interface\n * To install the docopt Python library run the following:\n \n .. code:: bash\n \n python3 -m pip install docopt # On Linux, Mac OS X\n py -3 -m pip install docopt # On Windows\n \n * scipy for performing the kendall-tau calculations\n * To install the scipy Python library run the following:\n\n .. code:: bash\n\n python3 -m pip install scipy # On Linux, Mac OS X\n py -3 -m pip install scipy # On Windows\n\n * numpy for creating and modifying ndarrays of data\n * To install numpy run the following:\n\n .. code:: bash\n\n python3 -m pip install numpy # On Linux, Mac OS X\n py -3 -m pip install numpy # On Windows\n\n * Cython for the cythonized kendall_dis method\n * To install the Cython Python library run the following:\n \n .. code:: bash\n \n python3 -m pip install Cython # On Linux, Mac OS X\n py -3 -m pip install Cython # On Windows\n\n\nWARNING- If the following pip error message is generated, then the python3 devel package must be installed:\n\n .. code:: bash\n\n \"fatal error: Python.h: No such file or directory\"\n\n\nBasic usage\n-----------\n\nTo use the ``icikt`` package, input a 2d array with n columns each representing\nan array of data for a variable. The `iciktArray` will return two n x n 2d arrays for correlations and p-values.\nEach element will correspond to the result of a combination of two columns in the input array. iciktArray can also\nbe called from the command-line interface given the file path for the data along with several optional parameters(more in docs/tutorial).\n\nRunning through command line :\n\n.. code:: bash\n\n icikt iciktArray /path/to/file.tsv --data-format=tsv --replace=None\n\nRunning through python script :\n\n.. code:: python\n\n import numpy as np\n import icikt\n\n dataArray = np.genfromtxt('/path/to/file.tsv', delimiter=\"\\t\")\n # or with random values\n dataArray = np.random.randn(100, 2)\n\n # running just 2 arrays with icikt\n corr, pVal, tMax = icikt.icikt(dataArray[:,0], dataArray[:,1])\n \n # running all combinations with iciktArray\n scaled, corrRaw, pVals, tauMax = icikt.iciktArray(dataArray)\n\n \n\n\nLicense\n-------\n\nA modified Clear BSD License\n\n\nCopyright (c) 2021, Praneeth S. Bhatt, Robert M. Flight, Hunter N.B. Moseley\nAll rights reserved.\n\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted (subject to the limitations in the disclaimer\nbelow) provided that the following conditions are met:\n\n\n* Redistributions of source code must retain the above copyright notice, this\n list of conditions and the following disclaimer.\n \n* Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n \n* Neither the name of the copyright holder nor the names of its contributors may be used\n to endorse or promote products derived from this software without specific\n prior written permission.\n \n* If the source code is used in a published work, then proper citation of the source\n code must be included with the published work.\n \n \nNO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS\nLICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\n\"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,\nTHE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\nARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE\nLIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\nCONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE\nGOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)\nHOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\nLIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT\nOF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH\nDAMAGE.\n\n\n.. _Github_Pages: https://moseleybioinformaticslab.github.io/icikt/\n.. _pip: https://pip.pypa.io/\n.. _git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git/\n.. _numpy: http://www.numpy.org/\n.. _scipy: https://scipy.org/scipylib/index.html\n.. _docopt: http://docopt.org/\n.. _Cython: https://cython.org/\n",
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