def daily_plot(self, days): """Bar plot displaying the number of block visits per day. The number of block visits is shown for the `days` days leading to but excluding `self.date`. A day here refers to the time from noon to noon. For example, 22 May 2016 refers to the period from 22 May 2016, 12:00 to 23 May 2016, 12:00. Params: ------- days : int Number of days. Returns: -------- app.plot.plot.TimeBarPlot Plot of number of block visits as a function of the day. """ start_date, end_date = day_range(self.date, days) trend_func = functools.partial(day_running_average, ignore_missing_values=False) df = self.df.copy() df['TimeLostToProblemsPercentage'] = 100 * np.divide(df.TimeLostToProblems, df.NightLength) df['TimeLostToProblems'] /= 60 return daily_bar_plot(df=df, start_date=start_date, end_date=end_date, date_column='Date', y_column=['TimeLostToProblems', 'TimeLostToProblemsPercentage'], y_range=[Range1d(start=0, end=250), Range1d(start=0, end=40)], y_formatters=[PrintfTickFormatter(format='%.0fm'), PrintfTickFormatter(format='%.0f%%')], trend_func=trend_func, **self.kwargs)
def daily_plot(self, days): """Bar plot displaying the number of block visits per day. The number of block visits is shown for the `days` days leading to but excluding `self.date`. A day here refers to the time from noon to noon. For example, 22 May 2016 refers to the period from 22 May 2016, 12:00 to 23 May 2016, 12:00. Params: ------- days : int Number of days. Returns: -------- app.plot.plot.TimeBarPlot Plot of number of block visits as a function of the day. """ start_date, end_date = day_range(self.date, days) trend_func = functools.partial(day_running_average, ignore_missing_values=False) return daily_bar_plot(df=self.df, start_date=start_date, end_date=end_date, date_column='Date', y_column='BlockCount', y_range=Range1d(start=0, end=30), trend_func=trend_func, **self.kwargs)
def daily_plot(self, days): """Bar plot displaying the operation efficiency per day. The operation efficiency is shown for the `days` days leading to but excluding `self.date`. A day here refers to the time from noon to noon. For example, 22 May 2016 refers to the period from 22 May 2016, 12:00 to 23 May 2016, 12:00. Params: ------- days : int Number of days. Returns: -------- app.plot.plot.TimeBarPlot Plot of operation efficiency as a function of the day. """ df = self.df.copy() df['OperationEfficiency'] = 100 * np.divide(df.ObsTime, df.ScienceTime) start_date, end_date = day_range(self.date, days) trend_func = functools.partial(day_running_average, ignore_missing_values=True) return daily_bar_plot( df=df, start_date=start_date, end_date=end_date, date_column='Date', y_column='OperationEfficiency', y_range=Range1d(start=0, end=140), trend_func=trend_func, y_formatters=[PrintfTickFormatter(format='%d%%')], **self.kwargs)
def daily_plot(self, days): """Bar plot displaying the operation efficiency per day. The operation efficiency is shown for the `days` days leading to but excluding `self.date`. A day here refers to the time from noon to noon. For example, 22 May 2016 refers to the period from 22 May 2016, 12:00 to 23 May 2016, 12:00. Params: ------- days : int Number of days. Returns: -------- app.plot.plot.TimeBarPlot Plot of operation efficiency as a function of the day. """ df = self.df.copy() df['OperationEfficiency'] = 100 * np.divide(df.ObsTime, df.ScienceTime) start_date, end_date = day_range(self.date, days) trend_func = functools.partial(day_running_average, ignore_missing_values=True) return daily_bar_plot(df=df, start_date=start_date, end_date=end_date, date_column='Date', y_column='OperationEfficiency', y_range=Range1d(start=0, end=140), trend_func=trend_func, y_formatters=[PrintfTickFormatter(format='%d%%')], **self.kwargs)
def daily_plot(self, days): """Bar plot displaying the number of block visits per day. The number of block visits is shown for the `days` days leading to but excluding `self.date`. A day here refers to the time from noon to noon. For example, 22 May 2016 refers to the period from 22 May 2016, 12:00 to 23 May 2016, 12:00. Params: ------- days : int Number of days. Returns: -------- app.plot.plot.TimeBarPlot Plot of number of block visits as a function of the day. """ start_date, end_date = day_range(self.date, days) trend_func = functools.partial(day_running_average, ignore_missing_values=False) df = self.df.copy() df['EngineeringTimePercentage'] = 100 * np.divide(df.EngineeringTime, df.NightLength) df['EngineeringTime'] /= 60 return daily_bar_plot(df=df, start_date=start_date, end_date=end_date, date_column='Date', y_column=['EngineeringTime', 'EngineeringTimePercentage'], y_range=[Range1d(start=0, end=200), Range1d(start=0, end=30)], y_formatters=[PrintfTickFormatter(format='%.0fm'), PrintfTickFormatter(format='%.0f%%')], trend_func=trend_func, **self.kwargs)