def __init__(self, day, parent=None):
super().__init__(parent)
self.signals = TimeLineWidget.Signals()
self.logger = getLogger(__name__ + "." + self.__class__.__name__)
self.logger.propagate = False
self.setFSTimeLimits(None)
self.setBlockTimeLimits(None)
self.setSelTimeLimits(None)
self.makeTools()
self.setDay(day)
self.setupUi()
def __init__(self, filepath):
"""
@summary: Constructor
@param filepath: Path for input and output datafiles
"""
self.fullpath = filepath
self.gbifRes = GBIFCodes()
self._files = []
logname, _ = os.path.splitext(os.path.basename(__file__))
logfname = os.path.join(filepath, logname + '.log')
if os.path.exists(logfname):
os.remove(logfname)
self._log = getLogger(logname, logfname)
def __init__(self, interpretedFname, metaFname, outFname):
"""
@summary: Constructor
@param interpretedFname: Full filename containing records from the GBIF
interpreted occurrence table
@param metaFname: Full filename containing metadata for all data files in the
Darwin Core GBIF Occurrence download:
https://www.gbif.org/occurrence/search
@param outFname: Full filename for the output BISON CSV file
"""
# self.gbifRes = GBIFCodes()
self._files = []
# Interpreted GBIF occurrence file
self.interpFname = interpretedFname
self._if = None
self._files.append(self._if)
self._iCsvrdr = None
# GBIF metadata file for occurrence files
self._metaFname = metaFname
self.fldMeta = None
# Output BISON occurrence file
self.outFname = outFname
self._outf = None
self._files.append(self._outf)
self._outWriter = None
pth, outbasename = os.path.split(outFname)
outbase, ext = os.path.splitext(outbasename)
# Input for Canonical name lookup
self.name4LookupFname = os.path.join(pth, 'nameUUIDForLookup.csv')
self._name4lookupf = None
self._files.append(self._name4lookupf)
self._name4lookupWriter = None
self._name4lookup = {}
logname, _ = os.path.splitext(os.path.basename(__file__))
logfname = os.path.join(pth, outbase + '.log')
if os.path.exists(logfname):
import time
ts = int(time.time())
logfname = os.path.join(pth, outbase + '.log.{}'.format(ts))
self._log = getLogger(logname, logfname)
def _setLogger(self, logfname):
scriptname, ext = os.path.splitext(os.path.basename(__file__))
self.log = getLogger(scriptname, logfname)
#!/usr/bin/env python
import glob
import re
import os
import time
import numpy as np
from image import Image
import primitives
import tools
import unittest
from astropy.io import fits
from scipy import ndimage
log = tools.getLogger('main')
def buildcalibrations(filelist,
lamlist,
date="20160408",
calibdir="calibrations/",
order=3,
lam1=1150,
lam2=2400,
R=25,
genwavelengthsol=True,
makehiresPSFlets=True,
savehiresimages=True):
"""
"""
import sys
import shutil
import time
import tarfile
import cPickle
import hashlib
import traceback
import scan
import mpi
import tools
import trajectory
logger = tools.getLogger('dyn')
if mpi.mpi:
from mpi4py import MPI
else:
logger.fatal('You can not run ensemble simulation without MPI!')
sys.exit(1)
__author__ = "Beat Amrein"
__email__ = "*****@*****.**"
logger.debug('Starting...')
if mpi.rank == mpi.root:
print('Rank 0: Started @', time.time(), mpi.get_info())
def setLogLevel(self, level):
getLogger(self.logger, level=level)
from filecmp import cmp as comparefiles
from platform import node as hostname
import gzip
import os
import subprocess
import shutil
import time
import analysis
import tools
from tools import File
__author__ = "Beat Amrein"
__email__ = "*****@*****.**"
logger = tools.getLogger('dyn.traj')
# This class is running a simulation
# Its essentially my python-implementation of submit.sh
# RELEVANT FOR PYTHON - MPI Interaction:
# http://stackoverflow.com/questions/10590064/interact-with-a-mpi-binary-via-a-non-mpi-python-script
# TODO 1: Custom Exceptions / Handling
# 2: if hot-atoms in first 4 steps, restart with smaller stepsize
# 3: automatic mapping
# 4: compress/uncompress pdbfile
# 5: compress/uncompress topology
# 6: compress/uncompress input files
# 7: fastforward md.QdynPackage, when loaded
# 8: mutation starting from just a sequence