typos in docs

docs/MCMC.rst

@@ -26,32 +26,33 @@ Under this assumption, the likelihood of observed data given the spectral model
 
 .. math::
     \mathcal{L} = \prod^N_{i=1} \frac{1}{\sqrt{2 \pi \sigma^2_i}} 
-                \exp\left(-\frac{(S(\vec{p};E_i) - F_i)^2}{2\sigma^2_i}\right)
+                \exp\left(-\frac{(S(\vec{p};E_i) - F_i)^2}{2\sigma^2_i}\right),
 
 where :math:`(F_i,\sigma_i)` are the flux measurement and uncertainty at an
 energy :math:`E_i` over :math:`N` spectral measurements. Taking the logarithm,
 
 .. math::
-    \ln\mathcal{L} = K - \sum^N_{i=1} \frac{(S(\vec{p};E_i) - F_i)^2}{2\sigma^2_i}
+    \ln\mathcal{L} = K - \sum^N_{i=1} \frac{(S(\vec{p};E_i) - F_i)^2}{2\sigma^2_i}.
 
 Given that the MCMC procedure will sample the areas of the distribution with
 maximum value of the objective function, it is useful to define the objective
 function as the negative log-likelihood (NLL) disregarding constant factors:
 
 .. math::
-    \mathrm{NLL} =  \sum^N_{i=1} \frac{(S(\vec{p};E_i) - F_i)^2}{\sigma^2_i}
+    \mathrm{NLL} =  \sum^N_{i=1} \frac{(S(\vec{p};E_i) - F_i)^2}{\sigma^2_i}.
 
 The NLL function in this assumption can be related to the :math:`\chi^2`
 parameter as :math:`\chi^2=-2\mathrm{NLL}`, so that maximization of the NLL is
 equivalent to a minimization of :math:`\chi^2`.
 
 This NLL function is passed onto the `emcee.EnsembleSampler`, and the MCMC run
 is started. `emcee <http://dan.iel.fm/emcee/current/>`_ uses an affine-invariant
-MCMC sampler (`Goodman & Weare (2010)
+MCMC sampler (`Goodman & Weare 2010
 <http://msp.org/camcos/2010/5-1/p04.xhtml>`_) that has the advantage of being
-able to sample complex parameter spaces without any sampling. In addition,
-having multiple simultaneous *walkers* improves the efficiency of the sampling
-and reduces the number of computationally-expensive likelihood calls required.
+able to sample complex parameter spaces without any tuning required. In
+addition, having multiple simultaneous *walkers* improves the efficiency of the
+sampling and reduces the number of computationally-expensive likelihood calls
+required.
 
 The sampler works best by using as many samplers as possible, and starting them
 in a compact ball around the best fitting parameter values. After a *burn-in*

docs/installation.rst

@@ -39,14 +39,4 @@ version is released), install ``naima`` from the `github repository`_ through pi
 
     pip install git+http://github.com/zblz/naima.git#egg=naima
 
-
-Contributing
-------------
-
-All development of ``naima`` is done through the `github repository`_, and
-contributions to the code are welcome.  The development model is similar to that
-of `astropy`_, so you can check the `astropy Developer Documentation
-<https://astropy.readthedocs.org/en/latest/#developer-documentation>`_ if you
-need information on how to make a code contribution.
-
 .. _github repository: https://github.com/zblz/naima

docs/radiative.rst

@@ -106,8 +106,8 @@ advantage of being computationally cheap compared to a numerical integration
 over the spectrum of the blackbody, and remain accurate within one percent over
 a wide range of energies. Both the isotropic IC and anisotropic IC
 approximations are available in ``naima``. If you use this class in your
-research, please cite `Khangulyan, D., Aharonian, F.A., & Kelner, S.R.  2014,
-Astrophysical Journal, 783, 100
+research, please consult and cite `Khangulyan, D., Aharonian, F.A., & Kelner,
+S.R.  2014, Astrophysical Journal, 783, 100
 <http://adsabs.harvard.edu/abs/2014ApJ...783..100K>`_.
 
 .. _Khangulyan et al. (2014): http://adsabs.harvard.edu/abs/2014ApJ...783..100K
@@ -152,7 +152,7 @@ A full description and derivation of its properties can be found in `Blumenthal
 uniform magnetic field direction, but that is rarely thought to be the case in
 astrophysical sources. Considering random magnetic fields results in a shift of
 the maximum emissivity from :math:`E_\mathrm{peak}=0.29 E_\mathrm{c}` to
-:math:`0.3 E_c`, where :math:`E_c` is the synchrotron characteristic energy. The
+:math:`0.23 E_c`, where :math:`E_c` is the synchrotron characteristic energy. The
 `~naima.models.Synchrotron` class implements the parametrization of the
 emissivity function of synchrotron radiation in random magnetic fields presented
 by `Aharonian et al. (2010; Appendix D)`_. This parametrization is particularly
@@ -173,15 +173,15 @@ Nonthermal Bremsstrahlung radiative model
 
 Nonthermal bremsstrahlung radiation arises when a population of relativistic
 particles interact with a thermal particle population (see `Blumenthal & Gould
-(1970)`_). For the computation of the bremsstrahlung emission spectrum, The
+1970`_). For the computation of the bremsstrahlung emission spectrum, The
 `~naima.models.Bremsstrahlung` class implements the approximation of `Baring et
 al. (1999)`_ to the original cross-section presented by `Haug (1975)`_.
 Electron-electron bremsstrahlung is implemented for the complete energy range,
 whereas electron-ion bremsstrahlung is at the moment only available for photon
 energies above 10 MeV. The normalization of the emission, and importance of the
 electron-electron versus the electron-ion channels, are given by the class
 arguments ``n0`` (ion total number density), ``weight_ee`` (weight of the e-e
-channel, given by :math:`\sum_i Z_i X_i`, and ``weight_ep`` (weight of the e-p
+channel, given by :math:`\sum_i Z_i X_i`), and ``weight_ep`` (weight of the e-p
 channel, given by  :math:`\sum_i Z_i^2 X_i`). The defaults for ``weight_ee`` and
 ``weight_ep`` correspond to a fully ionised medium with solar abundances.
 
@@ -202,8 +202,8 @@ followed by pion decay, which results in a photon with :math:`E_\gamma >
 100\,\mathrm{MeV}`. Until recently, the only parametrizations available for the
 integral cross-section and photon emission spectra were either only applicable
 to limited energy ranges, or were given as extensive numerical tables (e.g.,
-`Kelner et al. (2006) <http://ukads.nottingham.ac.uk/abs/2006PhRvD..74c4018K>`_;
-`Kamae et al. (2006) <http://ukads.nottingham.ac.uk/abs/2006ApJ...647..692K>`_).
+`Kelner et al. 2006 <http://ukads.nottingham.ac.uk/abs/2006PhRvD..74c4018K>`_;
+`Kamae et al. 2006 <http://ukads.nottingham.ac.uk/abs/2006ApJ...647..692K>`_).
 By considering Monte Carlo results and a compilation of accelerator data on p-p
 interactions, `Kafexhiu et al. (2014)
 <http://adsabs.harvard.edu/abs/2014PhRvD..90l3014K>`_ were able to develop
@@ -212,8 +212,9 @@ rays from p-p interactions. The `~naima.models.PionDecay` class uses an
 implementation of the formulae presented in their paper, and gives the choice of
 which high-energy model to use (from the parametrization to the different Monte
 Carlo results) through the `hiEmodel` parameter. If you use this class, please
-cite `Kafexhiu, E., Aharonian, F., Taylor, A.M., & Vila, G.S. 2014, Physical
-Review D, 90, 123014 <http://adsabs.harvard.edu/abs/2014PhRvD..90l3014K>`_. 
+consult and cite `Kafexhiu, E., Aharonian, F., Taylor, A.M., & Vila, G.S. 2014,
+Physical Review D, 90, 123014
+<http://adsabs.harvard.edu/abs/2014PhRvD..90l3014K>`_. 
 
 
 .. _Blumenthal & Gould 1970: 

docs/units.rst

@@ -4,9 +4,9 @@ Units system used
 =================
 
 The package makes use of the :mod:`astropy.units` package to handle units and
-unit conversions. Several of the options that need to be specified in the
-functions described below require :class:`~astropy.units.quantity.Quantity`
-instances. Defining quantities is straightforward::
+unit conversions. Several of the arguments of the functions and classes of
+``naima`` require :class:`~astropy.units.quantity.Quantity` instances. Defining
+quantities is straightforward::
 
     from astropy import units as u