A_Scheduler.py
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#!/usr/bin/env python3
#
# To launch this agent from the root of Pyros:
#
# Linux console:
# cd /srv/develop/pyros/docker
# ./PYROS_DOCKER_START.sh
# ./PYROS_RUN_WEBSERVER_ONLY -o tnc -fg
# cd ..
# ./PYROS start -o tnc -fg -a A_Scheduler
#
# Launch from Power Shell:
# To go from docker to Powershell: pyros_user@ORION:~/app$ exit (or Ctrl+d)
# Prompt is now PS ...>
# cd \srv\develop\pyros
# .\PYROS -t new-start -o tnc -fg -a A_Scheduler
#
# Launch from docker:
# To go from Powershell to docker: PS ...> .\PYROS_DOCKER_SHELL
# Prompt is now pyros_user@ORION:~/app$
# ./PYROS -t new-start -o tnc -fg -a A_Scheduler
#
# To use debug
# ./PYROS -d -t new-start -o tnc -fg -a A_Scheduler
#
# ./PYROS -d -t start -o tnc -fg A_Scheduler
# ---------------------------------------------------
import sys
import time
import argparse
import os
import pickle
import socket
import yaml
pwd = os.environ['PROJECT_ROOT_PATH']
if pwd not in sys.path:
sys.path.append(pwd)
short_paths = ['src', 'src/core/pyros_django']
for short_path in short_paths:
path = os.path.abspath(os.path.join(pwd, short_path))
if path not in sys.path:
sys.path.insert(0, path)
#from src.core.pyros_django.majordome.agent.Agent import Agent, build_agent, log, parse_args
from majordome.agent.Agent import Agent, build_agent, log, parse_args
from seq_submit.models import Sequence
from user_mgmt.models import Period, ScientificProgram, SP_Period
from scp_mgmt.models import Quota
from scheduling.models import PredictiveSchedule, EffectiveSchedule
# = Specials
import glob
import shutil
import guitastro
import datetime
from decimal import Decimal
import zoneinfo
import numpy as np
from pyros_api import PyrosAPI
class A_Scheduler(Agent):
DPRINT = True
# - Sampling of the night arrays (bins/night)
BINS_NIGHT = 86400
# - status of the sequence after schedule computation
SEQ_NOT_PROCESSED = 0
SEQ_SCHEDULED = 1
SEQ_SCHEDULED_OVER_QUOTA = 2
SEQ_REJECTED_NO_QUOTA_ENOUGH = -1
SEQ_REJECTED_NO_SLOT_AVAILABLE = -2
# - enum of the matrix line
SEQ_K = 0
SEQ_SEQ_ID = 1
SEQ_KOBS0 = 2
SEQ_SP_ID = 3
SEQ_PRIORITY = 4
SEQ_DURATION = 5
SEQ_STATUS = 6
NB_SEQ = 7
# - All possible running states
RUNNING_NOTHING = 0
RUNNING_SCHEDULE_PROCESSING = 1
_AGENT_SPECIFIC_COMMANDS = {
# Format : “cmd_name” : (timeout, exec_mode)
"do_compute_schedule_1" : (60, Agent.EXEC_MODE.SEQUENTIAL, ''),
"do_create_seq_1" : (60, Agent.EXEC_MODE.SEQUENTIAL, ''),
}
# Test scenario to be executed (option -t)
# "self do_stop_current_processing"
# AgentCmd.CMD_STATUS_CODE.CMD_EXECUTED
_TEST_COMMANDS_LIST = [
# Format : ("self cmd_name cmd_args", timeout, "expected_result", expected_status),
(True, "self do_create_seq_1 6", 200, '', Agent.CMD_STATUS.CMD_EXECUTED),
(True, "self do_stop asap", 500, "STOPPING", Agent.CMD_STATUS.CMD_EXECUTED),
]
"""
=================================================================
Methods running inside main thread
=================================================================
"""
def __init__(self, name:str=None,simulated_computer=None):
if name is None:
name = self.__class__.__name__
super().__init__(simulated_computer=simulated_computer)
def _init(self):
super()._init()
log.debug("end super init()")
log.info(f"self.TEST_MODE = {self.TEST_MODE}")
# === Get the config object
self.config = self._oc['config']
self.pconfig = self._oc['pyros_config']
# === Get agent_alias
hostname = socket.gethostname()
log.info(f"{hostname=}")
log.info(f"{self.name=}")
agent_alias = self.config.get_agent_real_name(self.name, hostname)
log.info(f"{agent_alias=}")
# === Get all file contexts from pyros config
self._fn = self.config.fn
log.info(f"=== List of file name contexts available for the unit")
self.check_contexts(True)
log.info(f"{self._fn.longitude=}")
# TBD duskelev a parametrer from obsconfig (yml)
self._duskelev = -7
# === Status of routine processing
self._routine_running = self.RUNNING_NOTHING
log.debug("end init()")
##### TBD suppress redondant paths in print(f"=>=>=> {sys.path=}")
# Note : called by _routine_process() in Agent
# @override
def _routine_process_iter_start_body(self):
log.debug("in routine_process_before_body()")
# Note : called by _routine_process() in Agent
# @override
def _routine_process_iter_end_body(self):
log.debug("in routine_process_after_body()")
# TODO EP est-ce utile ?
if self._routine_running == self.RUNNING_NOTHING:
# Get files to process
# - Thread TODO
self._routine_running = self.RUNNING_SCHEDULE_PROCESSING
self.do_compute_schedule_1()
"""
=================================================================
Methods of specific commands
=================================================================
"""
def do_create_seq_1(self, nb_seq:int):
"""Create sequences to debug
:raises ExceptionType: Some multi-line
exception description.
"""
try:
self._create_seq_1(nb_seq)
except Exception as e:
self.dprint(f"ERROR {e}")
def do_compute_schedule_1(self):
"""Compute a schedule
According the current time, select the night directory.
List the *.p file list (.p for sequences)
Read the *.p, *.f file contents (.f for ephemeris)
Compute the schedule
Output is a matrix to unpack in the database.
Each line of the matrix is a sequence
Columns are defined by the enum SEQ_* (see the python code itself).
"""
try:
self._compute_schedule_1()
except Exception as e:
self.dprint(f"ERROR {e}")
"""
=================================================================
Methods called by commands or routine. Overload these methods
=================================================================
# ---
# osp = ScientificProgram.objects.get(id=scientific_program_id)
# --- ospperiod is the SP object
# ospperiod = SP_Period.objects.get(period = period_id, scientific_program = osp)
# print(f"dir(ospperiod)={dir(ospperiod)}")
# dir(spperiod)=['DoesNotExist',
# 'IS_VALID', 'IS_VALID_ACCEPTED', 'IS_VALID_REJECTED',
# 'MultipleObjectsReturned', 'SP_Period_Guests', 'SP_Period_Users',
# 'STATUSES', 'STATUSES_ACCEPTED', 'STATUSES_DRAFT',
# 'STATUSES_EVALUATED', 'STATUSES_REJECTED', 'STATUSES_SUBMITTED',
# 'VISIBILITY_CHOICES', 'VISIBILITY_NO', 'VISIBILITY_YES',
# 'VOTES', 'VOTES_NO', 'VOTES_TO_DISCUSS', 'VOTES_YES',
# 'can_submit_sequence', 'check', 'clean', 'clean_fields',
# 'date_error_message', 'delete', 'from_db', 'full_clean',
# 'get_constraints', 'get_deferred_fields', 'get_is_valid_display',
# 'get_public_visibility_display', 'get_status_display',
# 'get_vote_referee1_display', 'get_vote_referee2_display',
# 'id', 'is_currently_active', 'is_valid', 'objects',
# 'over_quota_duration', 'over_quota_duration_allocated',
# 'over_quota_duration_remaining', 'period', 'period_id',
# 'pk', 'prepare_database_save', 'priority', 'public_visibility',
# 'quota_allocated', 'quota_minimal', 'quota_nominal',
# 'quota_remaining', 'reason_referee1', 'reason_referee2',
# 'referee1', 'referee1_id', 'referee2', 'referee2_id',
# 'refresh_from_db', 'save', 'save_base', 'scientific_program',
# 'scientific_program_id', 'serializable_value', 'status', 'token',
# 'token_allocated', 'token_remaining', 'unique_error_message',
# 'validate_constraints', 'validate_unique', 'vote_referee1',
# 'vote_referee2'
"""
def update_db_quota_sequence(self, sequence_id, quota_attributes):
sequence = Sequence.objects.get(id=sequence_id)
new_quota = Quota()
new_quota.set_attributes_and_save(quota_attributes)
sequence.quota = new_quota
sequence.save()
def _compute_schedule_1(self):
"""Simple scheduler based on selection-insertion one state algorithm.
Quotas are available only fo the night.
No token.
"""
t0 = time.time()
self.DPRINT = True
# ===================
# --- Initializations
# ===================
# --- Get the incoming directory of the night
info = self.get_infos()
rootdir = info['rootdir']
subdir = info['subdir']
# --- Get the night
night = info['night']
# --- Get ephemeris informations of the night and initialize quotas
self.update_sun_moon_ephems()
# Get quota for night
oquota = Quota.objects.get(id_period=info["operiod"].id, night_id=info["night"])
# --- Build the wildcard to list the sequences
wildcard = os.path.join(rootdir, subdir, "*.p")
self.dprint(f"{wildcard=}")
# --- List the sequences from the incoming directory
seqfiles = glob.glob(wildcard)
log.info(f"{len(seqfiles)} file sequences to process")
# --- Initialize the predictive schedule from start of the night (=all the night)
schedule_sequence_id = np.zeros(self.BINS_NIGHT, dtype=int) -1
schedule_binary = np.ones(self.BINS_NIGHT, dtype=int)
schedule_visibility = np.zeros(self.BINS_NIGHT, dtype=float)
schedule_order = np.zeros(self.BINS_NIGHT, dtype=int) -1
schedule_jd = np.zeros(self.BINS_NIGHT, dtype=float)
schedule_scientific_programm_id = np.zeros(self.BINS_NIGHT, dtype=int) -1
# ===========================================================================================================
# --- Initialize the predictive schedule by the effective schedule from start of the current instant (=index)
# ===========================================================================================================
try:
last_schedule = EffectiveSchedule.objects.last()
except EffectiveSchedule.DoesNotExist:
self.dprint(f"No effective schedule in the database (table is void)")
# --- Get the numpy matrix of the effective schedule from the database (via Json)
if last_schedule != None:
input_matrix = last_schedule.conv_numpy()
# --- Unpack the matrix to effective schedule arrays
schedule_eff_jd, schedule_eff_binary, schedule_eff_sequence_id, schedule_eff_scientific_programm_id, schedule_eff_order, schedule_eff_visibility = input_matrix
# --- Get the index of the current instant in the night
nownight, index = self._fn.date2night("now", self.BINS_NIGHT)
self.dprint(f"{nownight=} {index=}")
# --- Add all ever observed sequences from 0 to index
if nownight == night and (index >= 0 or index < self.BINS_NIGHT):
schedule_sequence_id[0:index] = schedule_eff_sequence_id[0:index]
schedule_binary[0:index] = schedule_eff_binary[0:index]
schedule_visibility[0:index] = schedule_eff_visibility[0:index]
schedule_order[0:index] = schedule_eff_order[0:index]
schedule_jd[0:index] = schedule_eff_jd[0:index]
schedule_scientific_programm_id[0:index] = schedule_eff_scientific_programm_id[0:index]
else:
# --- Case when there is no effective schedule for this night
print(f"No effective schedule for this night {night}")
else:
# --- Case of invalid entry in the database
print(f"Invalid entry in the database")
#print(f"{schedule_jd=}")
# ===================================================================
# --- Loop over the sequences of the night to extract useful infos
# ===================================================================
self.dprint("\n" + "="*70 + f"\n=== Read {len(seqfiles)} sequence files of the night {info['night']}\n" + "="*70 + "\n")
sequence_infos = []
# --- Initialize the list of scientific_program_ids
scientific_program_ids = []
kseq = 0
for seqfile in seqfiles:
# --- seqfile = sequence file name
kseq += 1
sequence_info = {}
sequence_info['id'] = -1 # TBD replace by idseq of the database
sequence_info['seqfile'] = seqfile
sequence_info['error'] = ""
sequence_info['kobs0'] = -1
# --- ephfile = ephemeris file name
ephfile = os.path.splitext(seqfile)[0] + ".f"
# --- If ephemeris file exists, read files
if os.path.exists(ephfile):
self.dprint(f"Read file {seqfile}")
# --- seq_info = sequence dictionary
seq_info = pickle.load(open(seqfile,"rb"))
#print("="*20 + "\n" + f"{seq_info=}")
# --- eph_info = ephemeris dictionary
eph_info = pickle.load(open(ephfile,"rb"))
#print("="*20 + "\n" + f"{eph_info=}")
# ---
self._fn.fcontext = "pyros_seq"
param = self._fn.naming_get(seqfile)
sequence_info['id'] = int(param['id_seq'])
# --- scientific_program_id is an integer
scientific_program_id = seq_info['sequence']['scientific_program']
# --- Dictionary of informations about the sequence
sequence_info['seq_dico'] = seq_info # useful for duration
# --- Search the last time when the start of the sequence is observable (visibility > 0)
visibility_duration = eph_info['visibility_duration']
kobss = np.where(visibility_duration > 0)
kobss = list(kobss[0])
if len(kobss) == 0:
self.dprint(" Sequence has no visibility")
sequence_info['error'] = f"Sequence has no visibility_duration"
sequence_infos.append(sequence_info)
continue
# --- TODO manage the case the sequence is before the current time (because of the effective schedule)
kobs0 = kobss[0]
sequence_info['kobs0'] = kobs0
sequence_info['visibility'] = eph_info['visibility'] # total slots
sequence_info['visibility_duration'] = visibility_duration # total slots - duration
sequence_info['duration'] = seq_info['sequence']['duration']
sequence_info['scientific_program_id'] = scientific_program_id
sequence_info["period"] = seq_info["sequence"]["period"]
sequence_info["night_id"] = seq_info["sequence"]["night_id"]
self.dprint(f" {scientific_program_id=} range to start={len(kobss)}")
if scientific_program_id not in scientific_program_ids:
scientific_program_ids.append(scientific_program_id)
# --- TODO
quota_attributes = {}
quota_attributes["d_total"] = int(np.ceil(sequence_info["duration"]))
quota_attributes["d_schedule"] = int(np.ceil(sequence_info["duration"]))
quota_attributes["night_id"] = sequence_info["night_id"]
quota_attributes["id_period"] = sequence_info["period"]
self.update_db_quota_sequence(seq_info["sequence"]["id"], quota_attributes)
else:
sequence_info['error'] = f"File {ephfile} not exists"
sequence_infos.append(sequence_info)
try:
schedule_jd = eph_info['jd']
except:
pass
# ===================================================================
# --- Get informations of priority and quota from scientific programs
# ===================================================================
self.dprint("\n" + "="*70 + f"\n=== Get information from {len(scientific_program_ids)} scientific programs of the night\n" + "="*70 + "\n")
scientific_program_infos = {}
period_id = info['operiod'].id
self.dprint(f"{scientific_program_ids=}")
for scientific_program_id in scientific_program_ids:
scientific_program_info = {}
try:
osp = ScientificProgram.objects.get(id=scientific_program_id)
# --- ospperiod is the SP object
ospperiod = SP_Period.objects.get(period = period_id, scientific_program = osp)
scientific_program_info['priority'] = ospperiod.priority
scientific_program_info['over_quota_duration'] = ospperiod.over_quota_duration
scientific_program_info['over_quota_duration_allocated'] = ospperiod.over_quota_duration_allocated
scientific_program_info['over_quota_duration_remaining'] = ospperiod.over_quota_duration_remaining
scientific_program_info['quota_allocated'] = ospperiod.quota_allocated
scientific_program_info['quota_minimal'] = ospperiod.quota_minimal
scientific_program_info['quota_nominal'] = ospperiod.quota_nominal
scientific_program_info['quota_remaining'] = ospperiod.quota_remaining
scientific_program_info['token_allocated'] = ospperiod.token_allocated
scientific_program_info['token_remaining'] = ospperiod.token_allocated
except:
# --- simulation
scientific_program_info['priority'] = 0
if scientific_program_info['priority'] == 0:
# --- simulation
priority = 50 + scientific_program_id*5
scientific_program_info['priority'] = priority
scientific_program_info['quota_allocated'] = 12000
scientific_program_info['quota_remaining'] = 12000
scientific_program_infos[str(scientific_program_id)] = scientific_program_info
self.dprint(f"{scientific_program_id=} priority={scientific_program_info['priority']} quota={scientific_program_info['quota_remaining']}")
# ===================================================================
# --- Build the numpy matrix seqs to make rapid computations
# ===================================================================
self.dprint("\n" + "="*70 + f"\n=== Build the matrix for scheduling {len(sequence_infos)} sequences\n" + "="*70 + "\n")
self.dprint("Order ID_seq K_start ID_sp Priority Duration Status\n")
nseq = len(sequence_infos)
if nseq == 0:
self._routine_running = self.RUNNING_NOTHING
return
seqs = np.zeros((nseq, self.NB_SEQ), dtype=int)
k = 0
for sequence_info in sequence_infos:
if 'scientific_program_id' not in sequence_info.keys():
self.dprint(f"No scientific program for ID sequence {sequence_info['id']}")
continue
scientific_program_id = sequence_info['scientific_program_id']
scientific_program_info = scientific_program_infos[str(scientific_program_id)]
priority = scientific_program_info['priority']
# Order of the following list refers to the enum
seq = [ k, sequence_info['id'], sequence_info['kobs0'], scientific_program_id, priority, int(np.ceil(sequence_info['duration'])), self.SEQ_NOT_PROCESSED]
self.dprint(f"{seq=}")
seqs[k] = seq
k += 1
seqs = seqs[:k]
# --- Save the matrix sequence
#print(f"{seqs=}")
fpathname = os.path.join(rootdir, subdir, "scheduler_seq_matrix1.txt")
np.savetxt(fpathname, seqs)
# ===================================================================
# --- Compute the matrix seq_sorteds (priority and chronology)
# ===================================================================
self.dprint("\n" + "="*70 + "\n=== Sort the matrix for scheduling by priority and chronology\n" + "="*70 + "\n")
# --- Sort the matrix sequence: priority=SEQ_PRIORITY (decreasing -1) and then chronology=SEQ_KOBS0 (increasing +1)
seq_sorteds = seqs[np.lexsort(([1,-1]*seqs[:,[self.SEQ_KOBS0, self.SEQ_PRIORITY]]).T)]
# --- Save the matrix sequence
self.dprint("Order ID_seq K_start ID_sp Priority Duration Status\n")
self.dprint(f"{seq_sorteds=}")
fpathname = os.path.join(rootdir, subdir, "scheduler_seq_matrix2.txt")
np.savetxt(fpathname, seq_sorteds)
# ===================================================================
# --- Insert sequences in the schedule. Respecting priority and quota
# ===================================================================
self.dprint("\n" + "="*70 + "\n=== Insertion of the sequences in the schedule respecting priority and quota\n" + "="*70 + "\n")
kseq_sorted = -1
for seq_sorted in seq_sorteds:
kseq_sorted += 1
# --- Unpack the sequence
k, sequence_id, kobs0, scientific_program_id, priority, duration, seq_status = seq_sorted
# --- Get the quota remaining of the scientific program
quota_remaining = scientific_program_infos[str(scientific_program_id)]['quota_remaining']
self.dprint('-'*70 + "\n" + f"Process {sequence_id=} {kobs0=} {duration=} sp_id={scientific_program_id} {quota_remaining=}")
# --- Verify if duration < quota_remaining
if duration > quota_remaining:
# --- No remaining quota to insert this sequence
self.dprint(f"{sequence_id=} cannot be inserted because no quota enough")
seqs[k][self.SEQ_STATUS] = self.SEQ_REJECTED_NO_QUOTA_ENOUGH
continue
# --- Compute the remaining visibility and list (k1s) of the best observation start
# =0 if not possible to start observation
# =value with the highest value for the best observation start
# --- Visibility*schedule_binary are transformed into binary
sequence_info = sequence_infos[k]
vis_binarys = sequence_info['visibility'].copy() * schedule_binary
vis_binarys[vis_binarys > 0] = 1
# --- Cumulative sum + offset by -duration to prepare the start_binary computation
obs_starts = np.cumsum(vis_binarys)
obs_ends = obs_starts.copy()
obs_ends[0:-duration] = obs_ends[duration:]
obs_ends[-duration:] = 0
# --- Difference and binarisation to get starts with duration
start_binary = obs_ends - obs_starts
start_binary[start_binary < duration] = 0
start_binary[start_binary == duration] = 1
# --- Compute the remaining visibility (float)
remaining_visibility = sequence_info['visibility'] * start_binary
# --- Check the remaining visibility
if np.sum(remaining_visibility) == 0:
# --- No remaining slot to insert this sequence
self.dprint(f"{sequence_id=} cannot inserted because no more slots available")
seqs[k][self.SEQ_STATUS] = self.SEQ_REJECTED_NO_SLOT_AVAILABLE
continue
# --- From the index of the highest value of remaining visibility to the index of the lowest value of remaining visibility
k1s = np.flip(np.argsort(remaining_visibility))
self.dprint(f"{k1s=} => Start elevation {sequence_info['visibility'][k1s[0]]:+.2f}")
# --- Get k1 as the highest value of remaining visibility
k1 = k1s[0]
k2 = k1 + duration
self.dprint(f"{k} : {sequence_id=} {scientific_program_id=} {priority=} inserted in the slot {k1=} {k2=} (remaining {quota_remaining - duration} s)")
# --- Update the seqs matrix
seqs[k][self.SEQ_STATUS] = self.SEQ_SCHEDULED
# --- Update the schedule arrays
schedule_sequence_id[k1:k2] = sequence_id
schedule_binary[k1:k2] = 0
schedule_visibility[k1:k2] = sequence_info['visibility'][k1:k2]
schedule_order[k1:k2] = kseq_sorted
schedule_scientific_programm_id[k1:k2] = scientific_program_id
# --- Update the scientific program dict
quota_remaining -= duration
scientific_program_infos[str(scientific_program_id)]['quota_remaining'] = quota_remaining
# ===================================================================
# --- Insert sequences in the schedule. Respecting priority but over quota
# ===================================================================
# self.dprint("\n" + "="*70 + "\n=== Insertion of the sequences in the schedule respecting priority but over quota\n" + "="*70 + "\n")
# TBD
# where are remaining free slots
# scan sequences to insert in these free slots
# ===================================================================
# --- Save the schedule
# ===================================================================
self.dprint("\n" + "="*70 + "\n=== Save the schedule\n" + "="*70 + "\n")
self.dprint("Order ID_seq K_start ID_sp Priority Duration Status\n")
self.dprint(f"{seqs=}")
# --- Prepare the output matrix
ouput_matrix = np.array([schedule_jd, schedule_binary, schedule_sequence_id, schedule_scientific_programm_id, schedule_order, schedule_visibility])
# --- Save the numpy matrix in ASCII
fpathname = os.path.join(rootdir, subdir, "scheduler_schedule.txt")
np.savetxt(fpathname, ouput_matrix.T)
# --- Save the numpy matrix in database (via Json)
v = PredictiveSchedule.objects.last()
if v == None:
v = PredictiveSchedule()
#log.info(f"{v=}")
v.scheduler_matrix = ouput_matrix
v.save()
# --- Save the numpy matrix in database (via Json)
v = EffectiveSchedule.objects.last()
if v==None:
v = EffectiveSchedule()
v.scheduler_matrix = ouput_matrix
v.save()
# --- Update the running state
self._routine_running = self.RUNNING_NOTHING
log.info(f"_compute_schedule_1 finished in {time.time() - t0:.2f} seconds")
def _create_seq_1(self, nb_seq: int):
# delete all previous test seq
Sequence.objects.filter(id__gte=9990000000).delete()
t0 = time.time()
self.dprint("Debut _create_seq_1")
seq_template = yaml.safe_load(open("scheduler_seq_template.yml","r"))
#{"simplified":True, 'sequence': {'id': 4, 'start_expo_pref': 'IMMEDIATE', 'pyros_user': 2, 'scientific_program': 1, 'name': 'seq_20230628T102140', 'desc': None, 'last_modified_by': 2, 'is_alert': False, 'status': 'TBP', 'with_drift': False, 'priority': None, 'analysis_method': None, 'moon_min': None, 'alt_min': None, 'type': None, 'img_current': None, 'img_total': None, 'not_obs': False, 'obsolete': False, 'processing': False, 'flag': None, 'period': 1, 'start_date': datetime.datetime(2023, 6, 28, 10, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='UTC')), 'end_date': datetime.datetime(2023, 6, 28, 10, 21, 40, 999640, tzinfo=datetime.timezone.utc), 'tolerance_before': '1s', 'tolerance_after': '1min', 'duration': -1.0, 'submitted': False, 'config_attributes': {'tolerance_before': '1s', 'tolerance_after': '1min', 'target': 'RADEC 0H10M -15D', 'conformation': 'WIDE', 'layout': 'Altogether'}, 'ra': None, 'dec': None, 'complete': True, 'night_id': '20230627'}, 'albums': {'Altogether': {'plans': [{'id': 4, 'album': 4, 'duration': 0.0, 'nb_fnges': 1, 'config_attributes': {'binnings': {'binxy': [1, 1], 'readouttime': 6}, 'exposuretime': 1.0}, 'complete': True}]}}}
# decode general variables info a dict info
info = self.get_infos()
rootdir = info['rootdir']
subdir = info['subdir']
# --- Read or create the sun ephemeris
ephem_sun = self.ephem_target2night("sun")
# --- Read or create the moon ephemeris
ephem_moon = self.ephem_target2night("moon")
# --- Prepare ephemeris object
eph = guitastro.Ephemeris()
eph.set_home(self.config.getHome())
# --- Horizon (TBD get from config)
self.dprint("Debut _create_seq_1 Horizon")
hor = guitastro.Horizon(eph.home)
hor.horizon_altaz = self.config.getHorizonLine(self.config.unit_name)
# --- Delete all existing *.p and *.f files in the night directory
fn_param = {
"period" : f"{info['period_id']}",
"version": "1",
"unit": self.config.unit_name,
"date": info['night'],
"id_seq": 0
}
fname = self._fn.naming_set(fn_param)
self.dprint(f":: {fname=}")
seq_file = self._fn.join(fname)
path_night = os.path.dirname(seq_file)
cards = ['*.p', '*.f']
for card in cards:
wildcard = os.path.join(path_night, card)
seq_dfiles = glob.glob(wildcard)
#print(f"::: {seq_dfiles=}")
for seq_dfile in seq_dfiles:
#print(f":::.1 : os.remove {seq_dfile=}")
os.remove(seq_dfile)
# --- Create new sequences
for k in range(nb_seq):
#print("B"*20 + f" {info['operiod'].id} {info['night']} {k}")
if k < nb_seq/2:
scientific_program = 0
else:
scientific_program = 1
time.sleep(1)
seq = seq_template.copy()
print(f"{seq}")
#seq['sequence']['config_attributes']['target'] = k # int
# ---
#start_expo_pref = "BESTELEV" #"IMMEDIATE"
start_expo_pref = 0 # for bestelev 1, for immediate 0
start_date,_ = self._fn.night2date(info["night"])
start_date = start_date + 0.25 + (0.5*k)
start_date_to_datetime = guitastro.Date(start_date).iso()
#start_date = datetime.datetime(2023, 6, 28, 10, 21, 40)
#end_date = datetime.datetime(2023, 6, 28, 10, 21, 40, 999640, tzinfo=datetime.timezone.utc)
jd1 = Decimal('0E-8')
jd2 = Decimal('0E-8')
tolerance_before = '1s'
tolerance_after = '5min'
duration = 3000.0
target = f"RADEC {k}h {10+2*k}d"
# ---
seq['sequence']['start_expo_pref'] = start_expo_pref
seq['sequence']['scientific_program'] = scientific_program
seq['sequence']['start_date'] = start_date_to_datetime
# seq['sequence']['jd1'] = jd1
# seq['sequence']['jd2'] = jd2
seq['sequence']['tolerance_before'] = tolerance_before
seq['sequence']['tolerance_after'] = tolerance_after
seq['sequence']['target'] = target
# --- Build the path and file name of the sequence file
seq["sequence"]["id"] = int("999" + f"{k:07d}")
seq["sequence"]["name"] = "seq_"+str(seq["sequence"]["id"])
# Add sequence to db
# with pyros_api script
pyros_api = PyrosAPI(None)
self._fn.fcontext = "pyros_seq_tmp"
self._fn.extension = ".json"
seq_fname = self._fn.join(str(seq["sequence"]["id"]))
seq_file = open(seq_fname,"w")
seq_file.write(yaml.dump(seq, sort_keys=False))
seq_file.close()
response = pyros_api.submit_sequence_file(seq_fname)
log.info(f"{response}")
"""
self.dprint(f"{k} : {self._fn.fcontext=}")
self._fn.fname = self._fn.naming_set(fn_param)
self.dprint(f"{k} : {self._fn.fname=}")
seq_file = self._fn.join(self._fn.fname)
self.dprint(f"{k} : {seq_file=}")
# --- Build the path and file name of the ephemeris file
eph_file = f"{seq_file[:-2]}.f"
# --- Create directory if it doesn't exist
self.dprint(f"{k} : {seq_file=}")
os.makedirs(os.path.dirname(seq_file), exist_ok=True)
# --- Compute the ephemeris of the sequence and manage errors
#print(f"{k} : TRY")
errors = []
try:
ephem = eph.target2night(seq["sequence"]["config_attributes"]["target"], info['night'], ephem_sun, ephem_moon, preference=seq['sequence']['start_expo_pref'], duskelev=self._duskelev, horizon=hor, duration=duration)
except ValueError:
errors.append("Target value is not valid")
except guitastro.ephemeris.EphemerisException as ephemException:
errors.append(str(ephemException))
if len(errors) == 0 and np.sum(ephem["visibility"]) == 0 :
errors.append("Target is not visible.")
if len(errors) == 0:
pickle.dump(ephem, open(eph_file,"wb"))
pickle.dump(seq, open(seq_file,"wb"))
#dprint(f"{errors=}")
#dprint("C"*20)
"""
log.info(f"_create_seq_1 finished in {time.time() - t0:.2f} seconds")
def load_sequence(self):
sequence = ""
return sequence
def get_infos(self):
self._fn.fcontext = "pyros_seq"
rootdir = self._fn.rootdir
operiod = Period.objects.exploitation_period()
if operiod == None:
log.info("No period valid in the database")
self._routine_running = self.RUNNING_NOTHING
return
# retourne un str -> id de la période sous le format Pxxx
period_id = operiod.get_id_as_str()
night_id = self._fn.date2night("now")
subdir = os.path.join(period_id, night_id)
dico = {}
dico['rootdir'] = rootdir
dico['subdir'] = subdir
dico['operiod'] = operiod # object
dico['period_id'] = period_id # str formated (P000)
dico['night'] = night_id # str (YYYYMMDD)
return dico
def dprint(self, *args, **kwargs):
if self.DPRINT:
log.info(*args, **kwargs)
if __name__ == "__main__":
agent = build_agent(A_Scheduler)
print(agent)
agent.run()