Allow completed logs to be loaded for Analysis

Whereas previously the files were not written back to disk first, here
we do. This is because I don't think I will continue working in Dash
(#97), so I feel like this temporary solution is good enough.

gama/dashboard/pages/analysispage.py

@@ -1,4 +1,8 @@
-# import base64
+import base64
+import itertools
+import os
+import shutil
+import uuid
 from typing import Dict, List, Optional
 
 import dash_core_components as dcc
@@ -174,26 +178,21 @@ def build_page(self, app, controller):
  def load_logs(self, list_of_contents, list_of_names):
  # global aggregate_dataframe
  if list_of_contents is not None:
+ tmp_dir = f"tmp_{str(uuid.uuid4())}"
+ os.makedirs(tmp_dir)
  for content, filename in zip(list_of_contents, list_of_names):
- # content_type, content_string = content.split(",")
- # decoded = base64.b64decode(content_string).decode("utf-8")
- # log_lines = decoded.splitlines()
- dirname = r"C:\Users\Work\GamaLog"
- report = GamaReport(dirname)
- self.reports[filename] = report
-
- # eval_copy = report.evaluations.copy()
- # eval_copy["search_method"] = report.search_method
- # if aggregate_dataframe is None:
- # eval_copy["log_no"] = 0
- # eval_copy["filename"] = filename
- # aggregate_dataframe = eval_copy
- # else:
- # eval_copy["log_no"] = len(
- # aggregate_dataframe["log_no"].unique())
- # eval_copy["filename"] = filename
- # aggregate_dataframe = pd.concat(
- # [aggregate_dataframe, eval_copy])
+ content_type, content_string = content.split(",")
+ decoded = base64.b64decode(content_string).decode("utf-8")
+ with open(os.path.join(tmp_dir, filename), "w") as fh:
+ fh.write(decoded)
+
+ report = GamaReport(tmp_dir)
+ report_name = report.search_method
+ for i in itertools.count():
+ if f"{report_name}_{i}" not in self.reports:
+ break
+ self.reports[f"{report_name}_{i}"] = report
+ shutil.rmtree(tmp_dir)
  return [{"label": logname, "value": logname} for logname in self.reports]
  return []
 

gama/logging/GamaReport.py

@@ -56,13 +56,16 @@ def __init__(self, log_directory: str):
  self.metrics += ["length"]
 
  self.incomplete = len(self.phases) < 3
- self.update() # updates self.evaluations and self.method_data
- # [ ] Dashboard -- how point to directory??
+ self.update(force=True) # updates self.evaluations and self.method_data
+ # [ ] Dashboard -- how point to directory?? => #97
 
  self.search_method = self.hyperparameters["search_method"]
  self.method_data = self.evaluations
 
- def update(self) -> bool:
+ def update(self, force: bool = False) -> bool:
+ if not force and not self.incomplete:
+ return False
+
  with open(os.path.join(self._log_directory, "evaluations.log"), "r") as fh:
  header = fh.readline()[:-1]
  self._last_tell = max(self._last_tell, fh.tell())