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Merge pull request #45 from jzuhone/json_limits
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Use limits from the JSON file, refactor prediction plots
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@jzuhone
jzuhone authored Jan 26, 2022
2 parents eee5bf1 + b8e0793 commit f3eae05
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Showing 25 changed files with 552 additions and 506 deletions.
2 changes: 1 addition & 1 deletion acis_thermal_check/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
ACISThermalCheck, \
DPABoardTempCheck
from acis_thermal_check.utils import \
get_options, mylog
get_options, mylog, get_acis_limits
from acis_thermal_check.acis_obs import \
fetch_ocat_data, acis_filter

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9 changes: 7 additions & 2 deletions acis_thermal_check/acis_obs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -133,7 +133,7 @@ def fetch_ocat_data(obsid_list):
return table_dict


def find_obsid_intervals(cmd_states):
def find_obsid_intervals(cmd_states, load_start):
"""
User reads the SKA commanded states archive, via
a call to the SKA kadi.commands.states.get_states,
Expand Down Expand Up @@ -191,6 +191,11 @@ def find_obsid_intervals(cmd_states):
if 60000 > eachstate['obsid'] >= 38001:
continue

# Only check states which are at least partially
# within the load being reviewed
if eachstate["tstop"] < load_start:
continue

pow_cmd = eachstate['power_cmd']

# is this the first WSPOW of the interval?
Expand Down Expand Up @@ -273,7 +278,7 @@ def acis_filter(obsid_interval_list):
"""
This method will filter between the different types of
ACIS observations: ACIS-I, ACIS-S, "hot" ACIS-S, and
cold science-orbit ECS.
cold science-orbit ECS.
"""
acis_hot = []
acis_s = []
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169 changes: 86 additions & 83 deletions acis_thermal_check/apps/acisfp_check.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
get_options, \
mylog
from acis_thermal_check.utils import \
plot_two, paint_perigee
paint_perigee, PredictPlot
import os
import sys
from astropy.table import Table
Expand All @@ -42,11 +42,18 @@ def __init__(self):
'TSCPOS': [(1, 2.5), (99, 2.5)]
}
hist_limit = [(-120.0, -100.0)]
limits_map = {
"planning.data_quality.high.acisi": "acis_i",
"planning.data_quality.high.aciss": "acis_s",
"planning.data_quality.high.aciss_hot": "acis_hot",
"planning.data_quality.high.cold_ecs": "cold_ecs"
}
super(ACISFPCheck, self).__init__("fptemp", "acisfp", valid_limits,
hist_limit,
other_telem=['1dahtbon'],
other_map={'1dahtbon': 'dh_heater',
"fptemp_11": "fptemp"})
"fptemp_11": "fptemp"},
limits_map=limits_map)
# Create an empty observation list which will hold the results. This
# list contains all ACIS and all ECS observations.
self.acis_and_ecs_obs = []
Expand Down Expand Up @@ -132,13 +139,13 @@ def make_prediction_plots(self, outdir, states, temps, load_start):

# extract the OBSID's from the commanded states. NOTE: this contains all
# observations including ECS runs and HRC observations
observation_intervals = find_obsid_intervals(states)
observation_intervals = find_obsid_intervals(states, load_start)

# Filter out any HRC science observations BUT keep ACIS ECS observations
self.acis_and_ecs_obs = hrc_science_obs_filter(observation_intervals)

# create an empty dictionary called plots to contain the returned
# figures, axes 1 and axes 2 of the plot_two call
# figures, axes 1 and axes 2 of the PredictPlot class
plots = {}

# Start time of loads being reviewed expressed in units for plotdate()
Expand All @@ -156,35 +163,27 @@ def make_prediction_plots(self, outdir, states, temps, load_start):
fontsize = [12, 9, 9]
for i in range(3):
name = f"{self.name}_{i+1}"
plots[name] = plot_two(fig_id=i+1, x=times, y=temps[self.name],
x2=self.predict_model.times,
y2=self.predict_model.comp["pitch"].mvals,
xlabel='Date', ylabel='Temperature ($^\circ$C)',
ylabel2='Pitch (deg)', xmin=plot_start,
ylim=ylim[i], ylim2=(40, 180),
figsize=(12, 7.142857142857142),
width=w1, load_start=load_start)
plots[name]['ax'].set_title(self.msid.upper(), loc='left', pad=10)
# Draw a horizontal line indicating the FP Sensitive Observation Cut off
plots[name]['ax'].axhline(self.cold_ecs_limit, linestyle='--',
color='dodgerblue', linewidth=2.0,
label='Cold ECS')
# Draw a horizontal line showing the ACIS-I -114 deg. C cutoff
plots[name]['ax'].axhline(self.acis_i_limit, linestyle='--',
color='purple', linewidth=2.0,
label="ACIS-I")
# Draw a horizontal line showing the ACIS-S -112 deg. C cutoff
plots[name]['ax'].axhline(self.acis_s_limit, linestyle='--',
color='blue', linewidth=2.0,
label='ACIS-S')
# Draw a horizontal line showing the ACIS-S -109 deg. C cutoff
plots[name]['ax'].axhline(self.acis_hot_limit, linestyle='--',
color='red', linewidth=2.0,
label="Hot ACIS-S")
plots[name] = PredictPlot(fig_id=i+1, x=times, y=temps[self.name],
x2=self.predict_model.times,
y2=self.predict_model.comp["pitch"].mvals,
xlabel='Date', ylabel='Temperature ($^\circ$C)',
ylabel2='Pitch (deg)', xmin=plot_start,
ylim=ylim[i], ylim2=(40, 180),
figsize=(12, 7.142857142857142),
width=w1, load_start=load_start)
plots[name].ax.set_title(self.msid.upper(), loc='left', pad=10)
# Draw a horizontal line indicating cold ECS cutoff
plots[name].add_limit_line(self.limits["cold_ecs"], "Cold ECS", ls='--')
# Draw a horizontal line showing the ACIS-I cutoff
plots[name].add_limit_line(self.limits["acis_i"], "ACIS-I", ls='--')
# Draw a horizontal line showing the ACIS-S cutoff
plots[name].add_limit_line(self.limits["acis_s"], "ACIS-S", ls='--')
# Draw a horizontal line showing the hot ACIS-S cutoff
plots[name].add_limit_line(self.limits["acis_hot"], "Hot ACIS-S", ls='--')
# Get the width of this plot to make the widths of all the
# prediction plots the same
if i == 0:
w1, _ = plots[name]['fig'].get_size_inches()
w1, _ = plots[name].fig.get_size_inches()

# Now draw horizontal lines on the plot running from start to stop
# and label them with the Obsid
Expand All @@ -193,28 +192,27 @@ def make_prediction_plots(self, outdir, states, temps, load_start):
textypos[i], fontsize[i], plot_start)

# These next lines are dummies so we can get the obsids in the legend
plots[name]['ax'].errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='red',
capsize=4, capthick=2, label='ACIS-I')
plots[name]['ax'].errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='green',
capsize=4, capthick=2, label='ACIS-S')
plots[name]['ax'].errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='blue',
capsize=4, capthick=2, label='ECS')
plots[name].ax.errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='red',
capsize=4, capthick=2, label='ACIS-I')
plots[name].ax.errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='green',
capsize=4, capthick=2, label='ACIS-S')
plots[name].ax.errorbar([0.0, 0.0], [1.0, 1.0], xerr=1.0,
lw=2, xlolims=True, color='blue',
capsize=4, capthick=2, label='ECS')

# Make the legend on the temperature plot
plots[name]['ax'].legend(bbox_to_anchor=(0.15, 0.99),
loc='lower left',
ncol=4, fontsize=14)
plots[name].ax.legend(bbox_to_anchor=(0.15, 0.99),
loc='lower left', ncol=4, fontsize=14)

# Build the file name
filename = f'{self.msid.lower()}' \
f'M{-int(ylim[i][0])}toM{-int(ylim[i][1])}.png'
plots[name]['filename'] = filename
plots[name].filename = filename

self._make_state_plots(plots, 3, w1, plot_start,
states, load_start,
figsize=(12, 6))
states, load_start)

# Now plot any perigee passages that occur between xmin and xmax
# for eachpassage in perigee_passages:
Expand All @@ -226,9 +224,9 @@ def make_prediction_plots(self, outdir, states, temps, load_start):
# customizations have been made
for key in plots:
if key != self.msid:
outfile = os.path.join(outdir, plots[key]['filename'])
outfile = os.path.join(outdir, plots[key].filename)
mylog.info('Writing plot file %s' % outfile)
plots[key]['fig'].savefig(outfile)
plots[key].fig.savefig(outfile)

return plots

Expand Down Expand Up @@ -275,13 +273,18 @@ def make_prediction_viols(self, temps, load_start):
# science run. These are load killers
# ------------------------------------------------------------
#
mylog.info(f'\n\nACIS-I Science ({self.acis_i_limit} C) violations')
acis_i_limit = self.limits["acis_i"].value
acis_s_limit = self.limits["acis_s"].value
acis_hot_limit = self.limits["acis_hot"].value
cold_ecs_limit = self.limits["cold_ecs"].value

mylog.info(f'\n\nACIS-I Science ({acis_i_limit} C) violations')

# Create the violation data structure.
acis_i_viols = self.search_obsids_for_viols("ACIS-I",
self.acis_i_limit, ACIS_I_obs, temp, times, load_start)
acis_i_limit, ACIS_I_obs, temp, times, load_start)

viols["ACIS_I"] = {"name": f"ACIS-I ({self.acis_i_limit} C)",
viols["ACIS_I"] = {"name": f"ACIS-I ({acis_i_limit} C)",
"type": "Max",
"values": acis_i_viols}

Expand All @@ -290,11 +293,11 @@ def make_prediction_viols(self, temps, load_start):
# science run. These are load killers
# ------------------------------------------------------------
#
mylog.info(f'\n\nACIS-S Science ({self.acis_s_limit} C) violations')
mylog.info(f'\n\nACIS-S Science ({acis_s_limit} C) violations')

acis_s_viols = self.search_obsids_for_viols("ACIS-S",
self.acis_s_limit, ACIS_S_obs, temp, times, load_start)
viols["ACIS_S"] = {"name": f"ACIS-S ({self.acis_s_limit} C)",
acis_s_limit, ACIS_S_obs, temp, times, load_start)
viols["ACIS_S"] = {"name": f"ACIS-S ({acis_s_limit} C)",
"type": "Max",
"values": acis_s_viols}

Expand All @@ -303,23 +306,23 @@ def make_prediction_viols(self, temps, load_start):
# science run which can run hot. These are load killers
# ------------------------------------------------------------
#
mylog.info(f'\n\nACIS-S Science ({self.acis_hot_limit} C) violations')
mylog.info(f'\n\nACIS-S Science ({acis_hot_limit} C) violations')

acis_hot_viols = self.search_obsids_for_viols("Hot ACIS-S",
self.acis_hot_limit, ACIS_hot_obs, temp, times, load_start)
viols["ACIS_S_hot"] = {"name": f"ACIS-S Hot ({self.acis_hot_limit} C)",
acis_hot_limit, ACIS_hot_obs, temp, times, load_start)
viols["ACIS_S_hot"] = {"name": f"ACIS-S Hot ({acis_hot_limit} C)",
"type": "Max",
"values": acis_hot_viols}

# ------------------------------------------------------------
# Science Orbit ECS -119.5 violations; -119.5 violation check
# ------------------------------------------------------------
mylog.info(f'\n\nScience Orbit ECS ({self.cold_ecs_limit} C) violations')
mylog.info(f'\n\nScience Orbit ECS ({cold_ecs_limit} C) violations')

ecs_viols = self.search_obsids_for_viols("Science Orbit ECS",
self.cold_ecs_limit, sci_ecs_obs, temp, times, load_start)
cold_ecs_limit, sci_ecs_obs, temp, times, load_start)

viols["ecs"] = {"name": f"Science Orbit ECS ({self.cold_ecs_limit} C)",
viols["ecs"] = {"name": f"Science Orbit ECS ({cold_ecs_limit} C)",
"type": "Min",
"values": ecs_viols}

Expand Down Expand Up @@ -438,39 +441,39 @@ def draw_obsids(obs_list, plots, msid, ypos, endcapstart, endcapstop,
if in_fp.startswith("ACIS-") or obsid > 60000:
# For each ACIS Obsid, draw a horizontal line to show
# its start and stop
plots[msid]['ax'].hlines(ypos,
obs_start,
obs_stop,
linestyle='-',
color=color,
linewidth=2.0)
plots[msid].ax.hlines(ypos,
obs_start,
obs_stop,
linestyle='-',
color=color,
linewidth=2.0)

# Plot vertical end caps for each obsid to visually show start/stop
plots[msid]['ax'].vlines(obs_start,
endcapstart,
endcapstop,
color=color,
linewidth=2.0)
plots[msid]['ax'].vlines(obs_stop,
endcapstart,
endcapstop,
color=color,
linewidth=2.0)
plots[msid].ax.vlines(obs_start,
endcapstart,
endcapstop,
color=color,
linewidth=2.0)
plots[msid].ax.vlines(obs_stop,
endcapstart,
endcapstop,
color=color,
linewidth=2.0)

# Now print the obsid in the middle of the time span,
# above the line, and rotate 90 degrees.

obs_time = obs_start + (obs_stop - obs_start)/2
if obs_time > plot_start:
# Now plot the obsid.
plots[msid]['ax'].text(obs_time,
textypos,
obsid_txt,
color=color,
va='bottom',
ma='left',
rotation=90,
fontsize=fontsize)
plots[msid].ax.text(obs_time,
textypos,
obsid_txt,
color=color,
va='bottom',
ma='left',
rotation=90,
fontsize=fontsize)


def main():
Expand Down
30 changes: 17 additions & 13 deletions acis_thermal_check/apps/dpa_check.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -29,8 +29,11 @@ def __init__(self):
'TSCPOS': [(1, 2.5), (99, 2.5)]
}
hist_limit = [20.0]
limits_map = {
"planning.caution.low": "zero_feps"
}
super(DPACheck, self).__init__("1dpamzt", "dpa", valid_limits,
hist_limit)
hist_limit, limits_map=limits_map)

def custom_prediction_viols(self, times, temp, viols, load_start):
"""
Expand All @@ -52,13 +55,14 @@ def custom_prediction_viols(self, times, temp, viols, load_start):
"""
# Only check this violation when all FEPs are off
mask = self.predict_model.comp['fep_count'].dvals == 0
zf_viols = self._make_prediction_viols(times, temp, load_start,
self.zero_feps_limit,
"zero-feps", "min",
mask=mask)
viols["zero_feps"] = {"name": f"Zero FEPs ({self.zero_feps_limit} C)",
"type": "Min",
"values": zf_viols}
zf_viols = self._make_prediction_viols(
times, temp, load_start, self.limits["zero_feps"].value,
"zero-feps", "min", mask=mask)
viols["zero_feps"] = {
"name": f"Zero FEPs ({self.limits['zero_feps'].value} C)",
"type": "Min",
"values": zf_viols
}

def custom_prediction_plots(self, plots):
"""
Expand All @@ -71,9 +75,8 @@ def custom_prediction_plots(self, plots):
and can be used to customize plots before they are written,
e.g. add limit lines, etc.
"""
plots[self.name]['ax'].axhline(self.zero_feps_limit, linestyle='--',
color='dodgerblue', label="Zero FEPs",
linewidth=2.0)
plots[self.name].add_limit_line(self.limits["zero_feps"],
"Zero FEPs", ls='--')

def custom_validation_plots(self, plots):
"""
Expand All @@ -87,8 +90,9 @@ def custom_validation_plots(self, plots):
e.g. add limit lines, etc.
"""
plots["1dpamzt"]['lines']['ax'].axhline(
self.zero_feps_limit, linestyle='--', color='dodgerblue', zorder=-8,
linewidth=2, label="Zero FEPs")
self.limits["zero_feps"].value, linestyle='--', zorder=-8,
color=self.limits["zero_feps"].color, linewidth=2,
label="Zero FEPs")

def _calc_model_supp(self, model, state_times, states, ephem, state0):
"""
Expand Down
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