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        "author": "Arash Ash",
        "author_email": "arash.ashrafnejad@gmail.com",
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        "description": "# PyPRF\n[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/arash-ash/pRFsim/master?filepath=pRFsim_Tutorial.ipynb)\n\n<img src=\"logo.svg\" width=200 align=\"right\" />\n\nA free & open source *python package* for *population receptive field (PRF) simulation*. This package is mainly developed for functional magnetic resonance imaging (fMRI) experiments.\n\n## Installation\nThe `prfsim` package can directly be installed from PyPI, in the following way:\n\n```bash\npip install prfsim\n```\n\n## Dependencies\n`prfsim` is implemented in [Python 3.6.4]\n\nIf you install `pyprf` using `pip` (as described above), all of the following dependencies are installed automatically - you do not have to take care of this yourself. Simply follow the above installation instructions.\n\n| pRFsim dependencies                                   | Tested version |\n|-------------------------------------------------------|----------------|\n| [NumPy](http://www.numpy.org/)                        | 1.14.0         |\n| [Pandas](https://pandas.pydata.org/)                  | 0.22.0         |\n| [SciPy](http://www.scipy.org/)                        | 1.0.0          |\n| [Seaborn](https://seaborn.pydata.org/)   \t\t| 0.8.1          |\n| [Pillow](https://pillow.readthedocs.io/)   \t\t| 5.0.0          |\n\n## Contributions\n\nFor contributors, we suggest the following procedure:\n\n* Create your own branch (in the web interface, or by `git checkout -b new_branch`)\n    * If you create the branch in the web interface, pull changes to your local repository (`git pull`)\n* Change to new branch: `git checkout new_branch`\n* Make changes\n* Commit changes to new branch (`git add .` and `git commit -m`)\n* Push changes to new branch (`git push origin new_branch`)\n* Create a pull request using the web interface\n\n## References\nThis application is based on the following work:\n\n[1] Dumoulin, S. O. & Wandell, B. A. (2008). Population receptive field estimates in human visual cortex. NeuroImage 39, 647\u2013660.\n\n## Support\nPlease use the [github issues](https://github.com/arash-ash/prfsim/issues) for questions or bug reports.\n\n## License\nThe project is licensed under [GNU General Public License Version 3](http://www.gnu.org/licenses/gpl.html).\n\n## How to use\n```bash\nimport prfsim.sim as psim\nimport numpy as np\n\n# experiment parameters\nradius = 10\nprecision = 0.1\nbarWidth = radius / 4\nangles = [-90, 45, -180, 315, 90, 225, 0, 135]\nnFrames = len(angles)*3\nTR = 3.0\nTRs = 5 # number of TRs for each frame\nduration = nFrames*TRs\n\nx, y = np.mgrid[-radius:radius:precision,\n                -radius:radius:precision]\npos = np.dstack((x, y))\nlength = len(x[0])\nnVoxels = 6\n\n# parameters for double gamma distribution function hrf:\nn1 = 4\nlmbd1 = 2.0\nt01 = 0\nn2 = 7\nlmbd2 = 3\nt02 = 0\na = 0.3\n\nt = np.arange(0,nFrames*TRs*TR,TR)\nhrf_gen = psim.hrf_double_gamma(t, n1, n2, lmbd1, lmbd2, t01, t02, a)\nhrf_est = hrf_gen\n\nstim = psim.generateStim(radius=radius, precision=precision,\n                    barWidth=barWidth, angles=angles,\n                    nFrames=nFrames, length=length,\n\t\t            TR=TR, TRs=TRs, isCheckerboard=False)\nprint('stimulus generated')\n\n\nneuronal_responses = psim.getNeuronalResponse(stim=stim, nVoxels=nVoxels,\n                                        radius=radius, precision=precision,\n                                        duration=duration)\nprint('Neuronal responses generated')\n\n\nbolds = psim.generateData(neuronal_responses=neuronal_responses,\n                     hrf=hrf_gen,\n                     duration=duration, nVoxels=nVoxels)\nprint('BOLD responses generated')\n\n\nprint('pRF estimations started...')\nresults = psim.estimateAll(bolds=bolds, stim=stim,\n                      hrf=hrf_est, radius=radius,\n                      precision=precision,\n                      nVoxels=nVoxels, margin = 1)\nprint('pRF estimation errors generated')\n```\n\n\n\n",
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