fix rendering of readme

README.md

@@ -1,14 +1,6 @@
 # HECSS
 
-::: {.cell 0=‘h’ 1=‘i’ 2=‘d’ 3=‘e’}
-
-``` python
-from nbdev import *
-```
-
-:::
-
-> High Efficiency Configuration Space Sampler
+<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
 
 HECSS is a Monte-Carlo, configuration space sampler using sample
 weighting algorithm for probability distribution sampling. It provides
@@ -44,42 +36,32 @@ OpenKIM database. Here we will sample the thermodynamic distribution of
 the crystal and energy/forces calculator, run the sampler and finally
 plot the energy distribution.
 
-::: {.cell 0=‘a’ 1=‘s’ 2=‘a’ 3=‘p’}
-
 ``` python
 from hecss import HECSS
 from hecss.util import select_asap_model, create_asap_calculator
 from hecss.monitor import plot_stats
 from ase.build import bulk
 ```
 
-:::
-
 Then we define the crystal and interaction model used in the
 calculation. In this case we use 3x3x3 supercell of the SiC crystal in
 zincblende structure and describe the interaction using LAMMPS potential
 from the OpenKIM database and ASAP3 implementation of the calculator.
 
-::: {.cell 0=‘a’ 1=‘s’ 2=‘a’ 3=‘p’}
-
 ``` python
 model = select_asap_model('SiC')
 cryst = bulk('SiC', crystalstructure='zincblende', 
              a=4.38120844, cubic=True).repeat((3,3,3))
 cryst.set_calculator(create_asap_calculator(model))
 ```
 
-:::
-
 Then we define the sampler parameters (N – number of samples, T –
 temperature) and run it. The parameter with the `lambda` anonymous
 function is required in this case, due to the peculiarities of the ASAP
 implementation of the ASE calculator which cannot be re-used when the
 sampler is re-executed. This construct is probably not required for
 other calculators.
 
-::: {.cell 0=‘a’ 1=‘s’ 2=‘a’ 3=‘p’}
-
 ``` python
 T = 300
 N = 100
@@ -88,24 +70,14 @@ samples = hecss.sample(T, N)
 distrib = hecss.generate(samples, T)
 ```
 
-:::
-
 And finally we plot the histogram of the resulting energy distribution
 which corresponds to the thermal equilibrium distribution.
 
-::: {.cell 0=‘a’ 1=‘s’ 2=‘a’ 3=‘p’}
-
 ``` python
 plot_stats(distrib, T, sqrN=True)
 ```
 
-<div class="cell-output cell-output-display">
-
-![](index_files/figure-commonmark/cell-6-output-1.png)
-
-</div>
-
-:::
+![](index_files/figure-commonmark/cell-5-output-1.png)
 
 ## Install