clustering/affinity_clustering_lsi.py

   1 import fire
   2 from affinity_clustering import affinity_clustering_result, affinity_job, affinity_grid_sweep
   3 from grid_sweep import grid_sweep
   4 from lsi_base import lsi_result_mixin, lsi_grid_sweep, lsi_mixin
   5 from dataclasses import dataclass
   6
   7 @dataclass
   8 class affinity_clustering_result_lsi(affinity_clustering_result, lsi_result_mixin):
   9     pass
  10
  11
  12 class affinity_lsi_job(affinity_job, lsi_mixin):
  13     def __init__(self, infile, outpath, name, lsi_dims, *args, **kwargs):
  14         super().__init__(infile,
  15                          outpath,
  16                          name,
  17                          *args,
  18                          **kwargs)
  19         super().set_lsi_dims(lsi_dims)
  20
  21     def get_info(self):
  22         result = super().get_info()
  23         self.result = affinity_clustering_result_lsi(**result.__dict__,
  24                                                      lsi_dimensions=self.lsi_dims)
  25         return self.result
  26
  27 class affinity_lsi_grid_sweep(lsi_grid_sweep):
  28     def __init__(self,
  29                  inpath,
  30                  lsi_dims,
  31                  outpath,
  32                  dampings=[0.9],
  33                  max_iters=[10000],
  34                  convergence_iters=[30],
  35                  preference_quantiles=[0.5]):
  36
  37         super().__init__(affinity_lsi_job,
  38                          _affinity_lsi_grid_sweep,
  39                          inpath,
  40                          lsi_dims,
  41                          outpath,
  42                          dampings,
  43                          max_iters,
  44                          convergence_iters,
  45                          preference_quantiles)
  46
  47
  48 class _affinity_lsi_grid_sweep(grid_sweep):
  49     def __init__(self,
  50                  inpath,
  51                  outpath,
  52                  lsi_dim,
  53                  *args,
  54                  **kwargs):
  55         self.lsi_dim = lsi_dim
  56         self.jobtype = affinity_lsi_job
  57         super().__init__(self.jobtype,
  58                          inpath,
  59                          outpath,
  60                          self.namer,
  61                          [self.lsi_dim],
  62                          *args,
  63                          **kwargs)
  64
  65     def namer(self, *args, **kwargs):
  66         s = affinity_grid_sweep.namer(self, *args[1:], **kwargs)
  67         s += f"_lsi-{self.lsi_dim}"
  68         return s
  69
  70 def run_affinity_lsi_grid_sweep(savefile, inpath, outpath, dampings=[0.8], max_iters=[3000], convergence_iters=[30], preference_quantiles=[0.5], lsi_dimensions='all',n_cores=30):
  71     """Run affinity clustering once or more with different parameters.
  72
  73     Usage:
  74     affinity_clustering.py --savefile=SAVEFILE --inpath=INPATH --outpath=OUTPATH --max_iters=<csv> --dampings=<csv> --preference_quantiles=<csv> --lsi_dimensions: either "all" or one or more available lsi similarity dimensions at INPATH.
  75
  76     Keword arguments:
  77     savefile: path to save the metadata and diagnostics
  78     inpath: path to folder containing feather files with LSI similarity labeled matrices of subreddit similarities.
  79     outpath: path to output fit kmeans clusterings.
  80     dampings:one or more numbers in [0.5, 1). damping parameter in affinity propagatin clustering.
  81     preference_quantiles:one or more numbers in (0,1) for selecting the 'preference' parameter.
  82     convergence_iters:one or more integers of number of iterations without improvement before stopping.
  83     max_iters: one or more numbers of different maximum interations.
  84     lsi_dimensions: either "all" or one or more available lsi similarity dimensions at INPATH.
  85     """
  86
  87     obj = affinity_lsi_grid_sweep(inpath,
  88                             lsi_dimensions,
  89                             outpath,
  90                             map(float,dampings),
  91                             map(int,max_iters),
  92                             map(int,convergence_iters),
  93                             map(float,preference_quantiles))
  94
  95     obj.run(n_cores)
  96     obj.save(savefile)
  97
  98 if __name__ == "__main__":
  99     fire.Fire(run_affinity_lsi_grid_sweep)