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81 lines
2.9 KiB
Python
81 lines
2.9 KiB
Python
#
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# Copyright (c) 2017 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import os
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from os.path import basename
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import pandas as pd
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from pandas.errors import EmptyDataError
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from rl_coach.dashboard_components.signals_file_base import SignalsFileBase
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from rl_coach.dashboard_components.globals import x_axis_options
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from rl_coach.utils import break_file_path
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class SignalsFile(SignalsFileBase):
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def __init__(self, csv_path, load=True, plot=None, use_dir_name=False):
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super().__init__(plot)
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self.use_dir_name = use_dir_name
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self.full_csv_path = csv_path
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self.dir, self.filename, _ = break_file_path(csv_path)
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if use_dir_name:
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parent_directory_path = os.path.abspath(os.path.join(os.path.dirname(csv_path), '..'))
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if len(os.listdir(parent_directory_path)) == 1:
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# get the parent directory name (since the current directory is the timestamp directory)
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self.dir = parent_directory_path
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self.filename = basename(self.dir)
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else:
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# get the common directory for all the experiments
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self.dir = os.path.dirname(csv_path)
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self.filename = "{}/{}".format(basename(parent_directory_path), basename(self.dir))
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if load:
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self.load()
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# this helps set the correct x axis
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self.change_averaging_window(1, force=True)
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def load_csv(self, idx=None, result=None):
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# load csv and fix sparse data.
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# csv can be in the middle of being written so we use try - except
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new_csv = None
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while new_csv is None:
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try:
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new_csv = pd.read_csv(self.full_csv_path)
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break
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except EmptyDataError:
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new_csv = None
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continue
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new_csv['Wall-Clock Time'] /= 60.
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new_csv = new_csv.interpolate()
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# remove signals which don't contain any values
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for k, v in new_csv.isna().all().items():
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if v and k not in x_axis_options:
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del new_csv[k]
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new_csv.fillna(value=0, inplace=True)
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self.csv = new_csv
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self.last_modified = os.path.getmtime(self.full_csv_path)
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if idx is not None:
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result[idx] = (self.csv, self.last_modified)
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def file_was_modified_on_disk(self):
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return self.last_modified != os.path.getmtime(self.full_csv_path)
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