912 Remove event model - phase1

#912

[author: gonzaponte]

This PR is the first step towards removing the superfluous parts of
the event model. It replaces the Hit class and its subsidiaries with
DataFrames, which are much more convenient.

[reviewer: jwaiton]

This PR begins the much desired process of removing the Hit class from IC, including changes across many cities and functions to accommodate this removal while retaining the same functionality.

It also adds documentation to some darker areas of the code related to
these changes, and has highlighted some new issues (#939, #936).

Approved! Great work, I'm excited for phase 2 😸

Author: jwaiton

invisible_cities/cities/beersheba.py

@@ -93,31 +93,6 @@
 from typing import Union
 
 
-# Temporary. The removal of the event model will fix this.
-def hitc_to_df_(hitc):
-    columns = "event time npeak Xpeak Ypeak nsipm X Y Xrms Yrms Z Q E Qc Ec track_id Ep".split()
-    columns = {col:[] for col in columns}
-
-    for hit in hitc.hits:
-        columns["event"   ].append(hitc.event)
-        columns["time"    ].append(hitc.time)
-        columns["npeak"   ].append(hit .npeak)
-        columns["Xpeak"   ].append(hit .Xpeak)
-        columns["Ypeak"   ].append(hit .Ypeak)
-        columns["nsipm"   ].append(hit .nsipm)
-        columns["X"       ].append(hit .X)
-        columns["Y"       ].append(hit .Y)
-        columns["Xrms"    ].append(hit .Xrms)
-        columns["Yrms"    ].append(hit .Yrms)
-        columns["Z"       ].append(hit .Z)
-        columns["Q"       ].append(hit .Q)
-        columns["E"       ].append(hit .E)
-        columns["Qc"      ].append(hit .Qc)
-        columns["Ec"      ].append(hit .Ec)
-        columns["track_id"].append(hit .track_id)
-        columns["Ep"      ].append(hit .Ep)
-    return pd.DataFrame(columns)
-
 def event_info_adder(timestamp : float, dst : pd.DataFrame):
     return dst.assign(time=timestamp/1e3, nsipm=0, Xrms=0, Yrms=0)
 
@@ -490,7 +465,6 @@ def beersheba( files_in         : OneOrManyFiles
     """
     correct_hits   = fl.map(hits_corrector(**corrections), item="hits")
     threshold_hits = fl.map(hits_thresholder(threshold, same_peak), item="hits")
-    hitc_to_df     = fl.map(hitc_to_df_, item="hits")
 
     deconv_params['psf_fname'       ] = expandvars(deconv_params['psf_fname'])
     deconv_params['satellite_params'] = satellite_params
@@ -537,7 +511,6 @@ def beersheba( files_in         : OneOrManyFiles
                                     correct_hits                              ,
                                     threshold_hits                            ,
                                     fl.branch(write_thr_hits)                 ,
-                                    hitc_to_df                                ,
                                     cut_sensors                               ,
                                     drop_sensors                              ,
                                     filter_events_no_hits                     ,