Mention conda-forge in Readme

Author: aseyboldt

README.md

@@ -14,16 +14,29 @@ sunode comes with a theano wrapper so that parameters of an ode can be estimated
 using pymc3.
 
 ### Installation
+sunode is available on conda-forge. Set up a conda environment to use conda-forge
+and install sunode:
 ```bash
+conda create -n sunode-env
+conda activate sunode-env
+conda config --add channels conda-forge
+conda config --set channel_priority strict
+
+conda install sunode
+```
+
+You can also install the development version. One windows you have to make
+sure the correct visual studio version is install and in the PATH.
+```
 git clone [email protected]:aseyboldt/sunode
+# Or if no ssh key is configured:
+git clone https://github.com/aseyboldt/sunode
+
 cd sunode
-conda create -n sunode -c conda-forge python numba pymc3 sympy pandas xarray sundials
-conda activate sunode
+conda install --only-deps sunode
 pip install -e .
 ```
 
-Installation instructions for windows can be found [here](https://gist.github.com/michaelosthege/5bd75c99cd5e806ee049b02ed528bab3).
-
 ### Solve an ode outside of a pymc3 model
 
 We will use the Lotka-Volterra equations as an example ODE:
@@ -205,14 +218,14 @@ with pm.Model() as model:
     pm.Lognormal('lynx', mu=y_hat['lynx'], sd=sd, observed=lynx_data)
 ```
 
-We can sample using pymc3 (I suspect you might need `cores=1` on windows for the moment):
+We can sample using pymc3 (You need `cores=1` on windows for the moment):
 ```
 with model:
     trace = pm.sample(tune=1000, draws=1000, chains=6, cores=6)
 ```
 
-Many solver options can not be specified with a nice interface at the moment,
-we can call the raw sundials functions however (this should change in the future):
+Many solver options can not be specified with a nice interface for now,
+we can call the raw sundials functions howeve:
 
 ```
 lib = sunode._cvodes.lib

doc/source/quickstart_pymc3.rst

@@ -3,41 +3,35 @@
 Quickstart with PyMC3
 =====================
 
-Official conda packages are not yet available in conda-forge. You can either
-build your own conda package or install the master version from github.
+sunode is available on conda-forge. You can setup an environmet to use conda-forge
+package if you don't have that already, and install sunode:::
 
-To use the development version, we create a new conda environment with the requirements
-and install using pip::
+    conda create -n sunode-env
+    conda activate sunode-env
+    conda config --add channels conda-forge
+    conda config --set channel_priority strict
+
+    conda install sunode
+
+You can also checkout the development version and install that:::
 
     git clone [email protected]:aseyboldt/sunode
     # Or if no ssh key is configured:
     git clone https://github.com/aseyboldt/sunode
 
     cd sunode
-    conda create -n sunode -c conda-forge python numba pymc3 sympy pandas xarray sundials
-    conda activate sunode
+    conda install --only-deps sunode
     pip install -e .
 
-To build and install a conda package locally, we clone the repo as above, and then run::
-
-    cd sunode
-    conda build ./conda
-
-    conda install -c local sunode
-    # Install it into a new environment:
-    conda create -n sunode -c local -c conda-forge sunode
-
-Instructions for installation on Windows can be found
-`here <https://gist.github.com/michaelosthege/5bd75c99cd5e806ee049b02ed528bab3>`_
+Installing the development version on Windows requires a compatible visual studio
+version.
 
 Sampling Bayesian models with Hamiltonian MCMC involving an ODE is where the
 features of sunode shine.  We need to solve the ODE (ofter rather small ODEs) a
 large number of times, so Python overhead will hurt us a lot, and we need to
 compute gradients as well. Sunode provides some utility functions that make it
 easy to include an ODE into a PyMC3 model.  If you want to use it in a
 different context, see :ref:`usage-basic`.
-
-
 We will use the Lotka-Volterra equations as example:
 
 .. math::