Remove old GridTPT parser

schedgen/opt/gridtptresult.py

-import re
-import pandas as pd
-
-
-class GridTPTResult:
-    __type_re = r"^Type +: (\w+)$"
-    __options_re = r"^Options +: (.*)$"
-    __cpu_limit_re = r"^CPU limit +: ([0-9]+)s"
-    __header_re = r"^Name +total_time +result"
-    __data_re = r"^([^ ]+) +([-0-9\.]+) +([^ ]+)"
-
-    def __init__(self, path, logics=None):
-        results = []
-        if logics:
-            logics = list(map(lambda s: s.strip(), logics))
-        with path.open() as f:
-            for line in f:
-                m = re.match(self.__data_re, line)
-                if m:
-                    r = m.group(3).strip()
-                    if r == "1" or r == "0":
-                        time = float(m.group(2))
-                    else:
-                        time = float("inf")  # unsolved
-                    if logics:
-                        exp_logic = m.group(1).split("/")[0]
-                        if exp_logic in logics:
-                            results.append((m.group(1), time))
-                    else:
-                        results.append((m.group(1), time))
-                    continue
-                m = re.match(self.__type_re, line)
-                if m:
-                    r = m.group(1).strip()
-                    if not r == "perf":
-                        raise ValueError("Experiment type not 'perf'.")
-                    else:
-                        continue
-                m = re.match(self.__options_re, line)
-                if m:
-                    self.options = m.group(1)
-                    continue
-                m = re.match(self.__cpu_limit_re, line)
-                if m:
-                    self.cpu_limit = int(m.group(1))
-        if not hasattr(self, "cpu_limit"):
-            raise ValueError("Could not parse cpu limit.")
-        if not hasattr(self, "options"):
-            raise ValueError("Could not parse strategy.")
-        r = [list(t) for t in zip(*results)]
-        if len(r) != 2:
-            raise ValueError("Could not get any solved benchmarks.")
-        [names, times] = r
-        self.results = pd.DataFrame(times, index=names, columns=["Time"])
-
-    def remove_results(self, index):
-        self.old_results = self.results.copy()
-        new_idx = self.results.index.difference(index)
-        self.results = self.results.reindex(new_idx)
-
-    def restore_results(self):
-        self.results = self.old_results
-
-    def solves_in(self, benchmark, time_slice):
-        try:
-            return self.results.loc[benchmark].Time <= time_slice
-        except KeyError:
-            return False
-
-    """ Returns the indices of the time slices that solve it. Assumes
-    time_slices is sorted in acending order. """
-
-    def solve_index(self, benchmark, time_slices, epsilon):
-        try:
-            time = self.results.loc[benchmark].Time
-        except KeyError:
-            return []
-        for i in range(len(time_slices)):
-            if time_slices[i] >= (time + epsilon):
-                return range(i, len(time_slices))
-        return []