more documentation updates.

doc/source/index.rst

@@ -12,6 +12,7 @@ Welcome to pyQMC's documentation!
 
    install
    tutorial
+   howto
    specific_instructions
    developer
 

doc/source/reduced_density_matrix_snippets.md

@@ -0,0 +1,49 @@
+Reduced density matrix snippets
+------------------------------------
+
+
+### Read in the 1-RDM
+
+You should have computed the 1-RDM by setting `accumulators={'rdm1':True}` in pyqmc.recipes.VMC or DMC.
+
+```
+import pyqmc.obdm
+def avg(vec):
+    nblock = vec.shape[0]
+    avg = np.mean(vec,axis=0)
+    std = np.std(vec,axis=0)
+    return avg, std/np.sqrt(nblock)
+
+with h5py.File("h2o_sj_vmc.hdf5") as f:
+    warmup=2
+    en, en_err = avg(f['energytotal'][warmup:,...])
+    rdm1, rdm1_err=avg(f['rdm1value'][warmup:,...])
+    rdm1norm, rdm1norm_err = avg(f['rdm1norm'][warmup:,...])
+    rdm1=pyqmc.obdm.normalize_obdm(rdm1,rdm1norm)
+    rdm1_err=pyqmc.obdm.normalize_obdm(rdm1_err,rdm1norm)
+```
+
+### Compute the density from the 1-RDM
+
+```
+mol, mf = pyqmc.recover_pyscf("h2o.hdf5")
+import pyscf.tools
+ao_rdm1 = np.einsum('pi,ij,qj->pq', mf.mo_coeff, rdm1, mf.mo_coeff.conj())
+resolution=0.05
+dens=pyscf.tools.cubegen.density(mol, "h2o_sj_density.cube",ao_rdm1,resolution=resolution)
+```
+
+### Plot the density from a cube file
+
+```
+import ase.io
+data = ase.io.cube.read_cube(open("h2o_sj_density.cube"))
+print(data.keys())
+print(data['data'].shape)
+yzplane = data['data'][int(data['data'].shape[0]/2),:,:]
+fig = plt.figure(figsize=(8,8))
+vmax=np.max(yzplane)
+plt.contourf(yzplane,levels=[vmax*x for x in np.logspace(-6,-1,80)], cmap='magma')
+plt.xticks([])
+plt.yticks([])
+```

doc/source/snippets.md

@@ -0,0 +1,35 @@
+Snippets
+--------------------
+
+### Periodic systems
+
+```
+def run_si_scf(chkfile="si_scf.chk"):
+    a = 5.43
+    cell = gto.Cell(
+        atom="Si 0. 0. 0.; Si {0} {0} {0}".format(a / 4),
+        unit="angstrom",
+        basis="ccecp-ccpvtz",
+        ecp="ccecp",
+        a=(np.ones((3, 3)) - np.eye(3)) * a / 2,
+    )
+    cell.exp_to_discard = 0.1
+    cell.build()
+
+    kpts = cell.make_kpts([8, 8, 8])
+    mf = scf.KRKS(cell, kpts=kpts)
+    mf.chkfile = chkfile
+    mf.run()
+```
+
+```
+import pyqmc.recipes
+import numpy as np
+
+def run_si_qmc(chkfile="si_scf.chk"):
+    # Define periodic supercell in PyQMC
+    conventional_S = np.ones((3, 3)) - 2 * np.eye(3)
+    S = 2 * conventional_S
+    pyqmc.recipes.OPTIMIZE(chkfile, "si_opt.chk", S=S)
+    pyqmc.recipes.DMC(chkfile, "si_dmc.chk", start_from="si_opt.chk", S=S)
+```