Update python.md

docs/src/python.md

@@ -1,89 +1,10 @@
 # [Calling from Python](@id python)
 
 This page provides some guidance on how Octofitter can be used from Python. 
-Our general recomendation is to download Julia and copy-paste the examples as needed, but there may be cases where it useful to embed Octofitter within a larger Python project or pipeline
+Our general recomendation is to download Julia and copy-paste the examples as needed, but there may be cases where it useful to embed Octofitter within a larger Python project or pipeline.
 
-In those cases, you might consider using Octofitter via [juliacall.py](https://pyjulia.readthedocs.io/en/stable/index.html), as demonstrated in these examples.
+In those cases, you might consider using [octofitterpy](https://github.com/sefffal/octofitterpy). This python package uses [juliacall.py](https://pyjulia.readthedocs.io/en/stable/index.html) to make some Octofitter functionality available in python.
 
-The broad instructions are as follows:
+Besides the model definition, most functions can be used the same in Python as in Julia. This [notebook](https://github.com/sefffal/octofitterpy/blob/master/examples/demo.ipynb)  provides some examples translated into Python.
 
-### Step 1
-Install the "JuliaCall" python package:
-```bash
-python3 -m pip install juliacall
-```
-
-### Step 3
-From inside python, install the Octofitter and Distributions Julia packages:
-```python
-import juliacall
-from juliacall import Main as jl
-from juliacall import Pkg
-Pkg.add(jl.map(jl.String, ['Octofitter','Distributions','Plots', 'CairoMakie', 'PairPlots']))
-```
-
-!!! note
-    You only need to run this step once to install everything. Don't repeat it each time you fit a model.
-
-### Step 4 
-Use Octofitter from inside python.
-
-```python
-# Import packages
-import juliacall
-from juliacall import Main as jl
-jl.seval("using Octofitter, Distributions, Plots, CairoMakie, PairPlots")
-import numpy as np
-
-
-# Now create a data table
-jl.astrom = jl.PlanetRelAstromLikelihood(jl.Table(
-    epoch = np.array([5000,5120,5240,5360,5480,5600,5720,5840]),
-    ra = np.array([-505.7637580573554,-502.570356287689,-498.2089148883798,-492.67768482682357,-485.9770335870402,-478.1095526888573,-469.0801731788123,-458.89628893460525]),
-    dec = np.array([-66.92982418533026,-37.47217527025044,-7.927548139010479,21.63557115669823,51.147204404903704,80.53589069730698,109.72870493064629,138.65128697876773]),
-    σ_ra = np.array([10,10,10,10,10,10,10,10.0]),
-	σ_dec = np.array([10,10,10,10,10,10,10,10]),
-	cor= np.array([0,0,0,0,0,0,0,0.0])
-))
-# Print it out to the screen (optional)
-jl.astrom._jl_display()
-
-jl.seval("""
-@planet B Visual{KepOrbit} begin
-    a ~ LogUniform(0.1, 500)
-    e ~ Uniform(0.0, 0.99)
-    i ~ Sine()
-    ω ~ UniformCircular()
-    Ω ~ UniformCircular()
-    θ ~ UniformCircular()
-    tp = θ_at_epoch_to_tperi(system,b,50000) # use MJD epoch of your data here!!
-end astrom
-""")
-jl.seval("""
-@system HD82134 begin
-    M ~ truncated(Normal(1.2, 0.1), lower=0)
-    plx ~ truncated(Normal(50.0, 0.02), lower=0)
-end B
-""")
-
-# Print it out to the screen (optional)
-jl.HD82134._jl_display()
-
-model = jl.Octofitter.LogDensityModel(jl.HD82134)
-# Print it out to the screen (optional)
-model._jl_display()
-
-# Sample
-chain = jl.octofit(model,)
-# Display results summary (recommended)
-chain._jl_display()
-
-# Save chain to FITS file (optional)
-jl.Octofitter.savechain("mychain.fits", chain)
-
-# Make corner plot
-fig = jl.octocorner(model, chain, small=True) # saved to "HD82134-pair-plot-small.png"
-
-# Plot orbits
-jl.octoplot(model, chain) # saved to "HD82134-plot-grid.png"
-```
+See the [octofitterpy](https://github.com/sefffal/octofitterpy) site for installation instructions.