pre-release 0.10.0

rl_coach/dashboard_components/signals_file.py

@@ -0,0 +1,63 @@
+import os
+from os.path import basename
+
+import pandas as pd
+from pandas.errors import EmptyDataError
+
+from rl_coach.dashboard_components.signals_file_base import SignalsFileBase
+from rl_coach.dashboard_components.globals import x_axis_options
+from rl_coach.utils import break_file_path
+
+
+class SignalsFile(SignalsFileBase):
+    def __init__(self, csv_path, load=True, plot=None, use_dir_name=False):
+        super().__init__(plot)
+        self.use_dir_name = use_dir_name
+        self.full_csv_path = csv_path
+        self.dir, self.filename, _ = break_file_path(csv_path)
+
+        if use_dir_name:
+            parent_directory_path = os.path.abspath(os.path.join(os.path.dirname(csv_path), '..'))
+            if len(os.listdir(parent_directory_path)) == 1:
+                # get the parent directory name (since the current directory is the timestamp directory)
+                self.dir = parent_directory_path
+                self.filename = basename(self.dir)
+            else:
+                # get the common directory for all the experiments
+                self.dir = os.path.dirname(csv_path)
+                self.filename = "{}/{}".format(basename(parent_directory_path), basename(self.dir))
+
+        if load:
+            self.load()
+            # this helps set the correct x axis
+            self.change_averaging_window(1, force=True)
+
+    def load_csv(self, idx=None, result=None):
+        # load csv and fix sparse data.
+        # csv can be in the middle of being written so we use try - except
+        new_csv = None
+        while new_csv is None:
+            try:
+                new_csv = pd.read_csv(self.full_csv_path)
+                break
+            except EmptyDataError:
+                new_csv = None
+                continue
+
+        new_csv['Wall-Clock Time'] /= 60.
+        new_csv = new_csv.interpolate()
+        # remove signals which don't contain any values
+        for k, v in new_csv.isna().all().items():
+            if v and k not in x_axis_options:
+                del new_csv[k]
+        new_csv.fillna(value=0, inplace=True)
+
+        self.csv = new_csv
+
+        self.last_modified = os.path.getmtime(self.full_csv_path)
+
+        if idx is not None:
+            result[idx] = (self.csv, self.last_modified)
+
+    def file_was_modified_on_disk(self):
+        return self.last_modified != os.path.getmtime(self.full_csv_path)