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        "author": "Jordan Mackie",
        "author_email": "jmackie@protonmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
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            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Physics"
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        "description": "# rouleur: Cycling performance modelling\n\nMakes the physical modelling of cycling trivially easy.\n\nFor example, let's try and estimate the power required for Wiggo's current hour record:\n\n```pycon\n>>> from rouleur import CyclingParams, calculate_air_density\n>>>\n>>> record = 54.526          # km/h\n>>> record *= 1000 / 60**2   # m/s\n>>> rho = calculate_air_density(30, 777, 0.6)  # about right\n>>> pars = CyclingParams(\n>>>     rider_velocity=record,\n>>>     air_density=rho,\n>>>     CdA=0.19, Crr=0.0025, \n>>>     chain_efficiency_factor=0.98,\n>>>     road_gradient=0,\n>>>     mass_total=82)\n>>>     \n>>> pars.solve_for.power_output()\n440.9565671224358\n```\n\nThat's all there is to it. \n\nThe API consists almost exclusively of the `CyclingParams` class, which holds all the parameters required for modelling a cyclist. The class constructor combines a number of sensible defaults with any (keyword) arguments passed. Details of recognised keyword arguments---i.e. model parameters---can be found in the class docstring (`help(CyclingParams)`).\n\nInstances then have a number of solver methods accessible via `parameters.solve_for.*`. \n\n# References\n\nThis package is an implementation of a number of published algorithms. Important references are:\n\n1. [Martin JC, Milliken DL, Cobb JE, McFadden KL, Coggan AR. Validation of a Mathematical Model for Road Cycling Power. Journal of Applied Biomechanics 14: 276--291, 1998.](http://journals.humankinetics.com/doi/10.1123/jab.14.3.276)\n\n2. [Martin JC, Gardner AS, Barras M, Martin DT. Modeling sprint cycling using field-derived parameters and forward integration. Med Sci Sports Exerc 38: 592--597, 2006.](https://www.ncbi.nlm.nih.gov/pubmed/16540850)\n\n3. [Atkinson G, Peacock O, Passfield L. Variable versus constant power strategies during cycling time-trials: Prediction of time savings using an up-to-date mathematical model. Journal of Sports Sciences 25: 1001--1009, 2007.](https://www.ncbi.nlm.nih.gov/pubmed/17497402)\n\n4. [Wells MS, Marwood S. Effects of power variation on cycle performance during simulated hilly time-trials. European Journal of Sport Science 16: 912--918, 2016.](https://www.ncbi.nlm.nih.gov/pubmed/26949050)\n",
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        "name": "rouleur",
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