usage: prog [options] This program will compute a variance map, using the results from an iteration of e2refine_easy.py as a basis for the computation. It uses a bootstrap resampling technique, where random particles are excluded from the model with replacement. This is repeated N times, producing a new 3-D model each time. The variance of the 3-D models is then computed. Note that this program requires a fair bit of memory. If running the entire program on a single machine, you will need enough memory to hold ~5 copies of a 3-D map + whatever is required by e2classaverage.py. It may be best-used on downsampled data (also for speed).

Option | Type | Description |
---|---|---|

--version | None | show program's version number and exit |

--verbose, -v | int | verbose level [0-9], higher number means higher level of verboseness |

--shrink3d | int | Shrink the class-averages and make a downsampled variance map |

--reslimit | float | Low-pass filter the individual maps to target the variance to the specified resolution in A. Variance maps cannot be filtered as a post-processing operation. Default = 10 |

--input | str | The name of the image containing the particle data |

--usefilt | str | Specify a particle data file that has been low pass or Wiener filtered. Has a one to one correspondence with your particle data. If specified will be used in projection matching routines, and elsewhere. |

--path | str | The name of an existing refine_XX folder to use for input and output |

--output | str | The name of a directory where the variance calculated should be placed. If unspecified will generate one automatically of type refinevar_??. |

--mass | float | The mass of the particle in kilodaltons, used to run normalize.bymass. If unspecified nothing happens. Requires the --apix argument. |

--apix | float | The angstrom per pixel of the input particles. This argument is required if you specify the --mass argument. If unspecified, the convergence plot is generated using either the project apix, or if not an apix of 1. |

--nmodels | int | The number of different bootstrap models to generate for the variance computation. Default=10 |

--iteration | int | The refinement iteration to use as a basis for the variance map |

--volfiles | None | This will bypass the construction of the individual resampled models, and use files previously generated with the --keep3d options |

--threads | int | Number of threads to run in parallel on a single computer when multi-computer parallelism isn't useful |

--sym | None | Specify symmetry - choices are: c<n>, d<n>, h<n>, tet, oct, icos |

--classkeep | float | The fraction of particles to keep in each class, based on the similarity score generated by the --cmp argument. |

--classkeepsig | None | Change the keep ('--keep') criterion from fraction-based to sigma-based. |

--classiter | int | The number of iterations to perform. Default is 1. |

--classalign | str | If doing more than one iteration, this is the name and parameters of the 'aligner' used to align particles to the previous class average. |

--classaligncmp | str | This is the name and parameters of the comparitor used by the fist stage aligner Default is dot. |

--classralign | str | The second stage aligner which refines the results of the first alignment in class averaging. Default is None. |

--classraligncmp | str | The comparitor used by the second stage aligner in class averageing. Default is dot:normalize=1. |

--classaverager | str | The averager used to generate the class averages. Default is 'mean'. |

--classcmp | str | The name and parameters of the comparitor used to generate similarity scores, when class averaging. Default is 'dot:normalize=1' |

--classnormproc | str | Normalization applied during class averaging |

--classrefsf | None | Use the setsfref option in class averaging to produce better filtered averages. |

--prefilt | None | Filter each reference (c) to match the power spectrum of each particle (r) before alignment and comparison |

--pad | int | To reduce Fourier artifacts, the model is typically padded by ~25 percent - only applies to Fourier reconstruction |

--recon | None | Reconstructor to use see e2help.py reconstructors -v |

--m3dkeep | float | The percentage of slices to keep in e2make3d.py |

--m3dkeepsig | None | The standard deviation alternative to the --m3dkeep argument |

--m3dsetsf | None | The standard deviation alternative to the --m3dkeep argument |

--m3diter | int | The number of times the 3D reconstruction should be iterated |

--m3dpreprocess | str | Normalization processor applied before 3D reconstruction |

--m3dpostprocess | str | Post processor to be applied to the 3D volume once the reconstruction is completed |

--keep3d | None | Keep all of the individual 3-D models used to make the variance map. This make take substantial disk space. |

--lowmem | None | Make limited use of memory when possible - useful on lower end machines |

--parallel, -P | str | Run in parallel, specify type:<option>=<value>:<option>:<value> |

--ppid | int | Set the PID of the parent process, used for cross platform PPID |