.. _sec_ini3d:

De novo 3D model generation
===============================

|RELION|-4.0 uses a gradient-driven algorithm to generate a *de novo* :jobtype:`3D initial model` from the 2D particles. 
As of release 4.0, this algorithm is different from the SGD algorithm in the CryoSPARC program :cite:`punjani_cryosparc:_2017`.
Provided you have a reasonable distribution of viewing directions, and your data were good enough to yield detailed class averages in :jobtype:`2D classification`, this algorithm is likely to yield a suitable, low-resolution model that can subsequently be used for :jobtype:`3D classification` or :jobtype:`3D auto-refine`.


Running the job
---------------

Select the ``Select/job014/particles.star`` file on the :guitab:`I/O` tab of the :jobtype:`3D initial model` jobtype.
Everything is aready in order on the :guitab:`CTF`.
Fill in the :guitab:`Optimisation` tab as follows (leave the defaults for the angular and offset sampling):

:Number of iterations: 100

     (The algorithm will loop over mini-batches, which contain only hundreds to thousands of particles.)

:Number of classes: 1

     (Sometimes, using more than one class may help in providing a 'sink' for sub-optimal particles that may still exist in the data set.
     In this case, which is quite homogeneous, a single class should work just fine.)

:Mask diameter (A): 200

     (The same as before).

:Flatten and enforce non-negative solvent: Yes

:Symmetry: D2

     (The actual refinement will be run in C1, which has been observed to converge better than performing it in higher symmetry groups.
     After the refinement, the ``relion_align_symmetry`` program is run to automatically detect the symmetry axes and the symmetry will be applied.)

:Initial angular sampling:: 15 degrees

     (The default angular and offset samplings should be fine for most cases, perhaps with the exception of highly symmetric particles like viruses, which may require finer samplings.) 

:Offset search range (pix):: 6

:Offset search step (pix):: 2


On the :guitab:`Compute` tab, set:

:Use parallel disc I/O?: Yes

:Number of pooled particles:: 30

:Pre-read all particles into RAM?: Yes

     (Again, this is only possible here because the data set is small. For your own data, you would like write the particles to a scratch disk instead, see below.)

:Copy particles to scratch directory: \ 

:Combine iterations through disc?: No

:Use GPU acceleration?: Yes

:Which GPUs to use: 0,1,2,3

On the :guitab:`Running` tab, set:

:Number of MPI procs: 1

     (Remember that the gradient-driven algorithm does not scale well with MPI.)

:Number of threads: 12

Using the settings above, this job took 2 minutes on our system.


Analysing the results
---------------------

You could look at the output map from the gradient-driven algorithm (``InitialModel/job015/run_it100_class001.mrc``) with a 3D viewer like UCSF :textsc:`chimera`. 
You should probably conform that the symmetry point group was correct and that the symmetry axes were identified correctly. 
If so, the symmetrised output map (``InitialModel/job015/initial_model.mrc``) should look similar to the output map from the gradient-driven algorithm.