Merge pull request #807 from lnls-sirius/update-macreport

Update machine reports

siriuspy/siriuspy/clientarch/pvarch.py

@@ -4,13 +4,13 @@
 
 import numpy as _np
 
+from mathphys.functions import save_pickle as _save_pickle, \
+    load_pickle as _load_pickle
+
 from . import exceptions as _exceptions
 from .client import ClientArchiver as _ClientArchiver
 from .time import Time as _Time, get_time_intervals as _get_time_intervals
 
-from mathphys.functions import save_pickle as _save_pickle, \
-    load_pickle as _load_pickle
-
 
 class _Base:
 

siriuspy/siriuspy/clientconfigdb/pvsconfig.py

@@ -40,7 +40,6 @@ def connected(self):
     @property
     def pvs(self):
         """Return dict with PVs and values."""
-        self.load()
         pvslist = self._value['pvs']
         pvsdict = {item[0]: item[1] for item in pvslist}
         return pvsdict

siriuspy/siriuspy/machshift/macreport.py

@@ -1259,10 +1259,18 @@ def _compute_stats(self):
         self._raw_data = dict()
 
         # current data
-        self._curr_times, self._curr_values = \
+        _curr_times, _curr_values = \
             self._get_pv_data('SI-Glob:AP-CurrInfo:Current-Mon')
-        self._curr_values[self._curr_values < 0] = 0
-        self._curr_values[self._curr_values > 500] = 0
+        _curr_values[_curr_values < 0] = 0
+        _curr_values[_curr_values > 500] = 0
+
+        # resample current data, from 1 pt in 60s, to 1pt in 5s
+        new_len = (len(_curr_times)-1)*12 + 1
+        new_times = _np.linspace(_curr_times[0], _curr_times[-1], new_len)
+        self._curr_times = new_times
+        self._curr_values = _np.interp(
+            new_times, _curr_times, _curr_values)
+
         self._raw_data['Timestamp'] = self._curr_times
         self._raw_data['Current'] = self._curr_values
 
@@ -1407,8 +1415,18 @@ def _compute_stats(self):
             self._gamblk_fail_values.astype(int)
         self._raw_data['Failures']['NoEBeam'] = \
             _np.logical_not(self._is_stored_users)
-        self._raw_data['Failures']['WrongShift'] = \
+
+        # # # ignore wrong shift failures shorter than 60s
+        wrong_shift = \
             1 * ((self._user_shift_progmd_values-self._user_shift_values) > 0)
+        ignore_wrong_shift = _np.zeros(wrong_shift.shape)
+        for i, val in enumerate(wrong_shift):
+            if i >= len(wrong_shift)-12:
+                break
+            if val == 1 and not _np.sum(wrong_shift[(i-12):(i+12)]) >= 12:
+                ignore_wrong_shift[i] = 1
+        consider_wrong_shift = wrong_shift - ignore_wrong_shift
+        self._raw_data['Failures']['WrongShift'] = consider_wrong_shift
 
         self._failures_users = 1 * _np.logical_or.reduce(
             [value for value in self._raw_data['Failures'].values()]) * \

siriuspy/siriuspy/machshift/test_macreport.py

@@ -13,10 +13,15 @@
     [Time(2021, 4, 1, 0, 0), Time(2021, 4, 30, 23, 59)],
     [Time(2021, 5, 1, 0, 0), Time(2021, 5, 31, 23, 59)],
     [Time(2021, 6, 1, 0, 0), Time(2021, 6, 30, 23, 59)],
-    [Time(2021, 7, 1, 0, 0), Time(2021, 7, 30, 23, 59)],
+    [Time(2021, 7, 1, 0, 0), Time(2021, 7, 31, 23, 59)],
     [Time(2021, 8, 1, 0, 0), Time(2021, 8, 31, 23, 59)],
     [Time(2021, 9, 1, 0, 0), Time(2021, 9, 30, 23, 59)],
     [Time(2021, 10, 1, 0, 0), Time(2021, 10, 31, 23, 59)],
+    [Time(2021, 11, 1, 0, 0), Time(2021, 11, 30, 23, 59)],
+    [Time(2021, 12, 1, 0, 0), Time(2021, 12, 31, 23, 59)],
+    [Time(2022, 1, 1, 0, 0), Time(2022, 1, 31, 23, 59)],
+    [Time(2022, 2, 1, 0, 0), Time(2022, 2, 28, 23, 59)],
+    [Time(2022, 3, 1, 0, 0), Time(2022, 3, 31, 23, 59)],
 ]
 
 macreports = dict()
@@ -28,19 +33,38 @@
     macreports[intvl[0]].update()
 
 mtbfs, mttrs, reliabs = dict(), dict(), dict()
+progrmd, delivd, usertot = dict(), dict(), dict()
+stable, unstable, relstable = dict(), dict(), dict()
 for date, macr in macreports.items():
     mtbfs[date] = macr.usershift_time_between_failures_average
     mttrs[date] = macr.usershift_time_to_recover_average
     reliabs[date] = macr.usershift_beam_reliability
+    progrmd[date] = macr.usershift_progmd_time
+    delivd[date] = macr.usershift_delivd_time
+    usertot[date] = macr.usershift_total_time
+    stable[date] = macr.usershift_total_stable_beam_time
+    unstable[date] = macr.usershift_total_unstable_beam_time
+    relstable[date] = macr.usershift_relative_stable_beam_time
 
-str_ = '{:<12s}    {:<12s}    {:<12s}    {:<12s}'
-print(str_.format('Y-M', 'MTBF', 'MTTR', 'Reliability'))
-str_ = '{:<12s}    {:<9.3f}    {:<9.3f}    {:<9.3f}'
+str_ = '{:<10s}' + '{:>16s}'*9
+print(str_.format(
+    'Y-M', 'MTBF', 'MTTR',
+    'Reliability', 'Progrmd hours', 'Delivd hours', 'Total hours',
+    '% stable hours', 'Stable hours', 'Unstable hours'))
+str_ = '{:<10s}' + '    {:>12.3f}'*9
 for date in macreports:
-    print(str_.format(str(date.year)+'-'+str(date.month),
-                      mtbfs[date],
-                      mttrs[date],
-                      reliabs[date]))
+    print(str_.format(
+        str(date.year)+'-'+str(date.month),
+        mtbfs[date],
+        mttrs[date],
+        reliabs[date],
+        progrmd[date],
+        delivd[date],
+        usertot[date],
+        relstable[date],
+        stable[date],
+        unstable[date],
+    ))
 
 fig, axs = plt.subplots(3, 1, sharex=True)
 fig.set_size_inches(9, 6)
@@ -65,10 +89,20 @@
 # programmed vs. delivered hours
 macr = MacReport()
 macr.connector.timeout = 120
-macr.time_start = Time(2020, 7, 1, 0, 0)
-macr.time_stop = Time(2021, 6, 30, 23, 59)
+macr.time_start = Time(2021, 3, 1, 0, 0)
+macr.time_stop = Time(2022, 3, 31, 23, 59)
 macr.update()
 
+print('MTBF', macr.usershift_time_between_failures_average)
+print('MTTR', macr.usershift_time_to_recover_average)
+print('Reliability', macr.usershift_beam_reliability)
+print('Progrmd hours', macr.usershift_progmd_time)
+print('Delivd hours', macr.usershift_delivd_time)
+print('Total hours', macr.usershift_total_time)
+print('% stable hours', macr.usershift_relative_stable_beam_time)
+print('Stable hours', macr.usershift_total_stable_beam_time)
+print('Unstable hours', macr.usershift_total_unstable_beam_time)
+
 rd = macr.raw_data
 dtimes = np.diff(rd['Timestamp'])
 dtimes = np.r_[dtimes, dtimes[-1]]