class FargoMovieMaker:
def __init__(self, inputDir, outputDir, batchSize):
self.outputDir = outputDir
self.batchSize = batchSize
self.parser = FargoParser(inputDir, batchSize)
secondaryOrbit = np.loadtxt(inputDir + "/planet0.dat")
secondaryX = secondaryOrbit[:, 1]
secondaryY = secondaryOrbit[:, 2]
self.secondaryRadius = np.sqrt(np.add(np.square(secondaryX), np.square(secondaryY)))
self.secondaryTheta = np.arctan2(secondaryY, secondaryX)
params = self.parser.getParams()
self.params = params
self.outputDir = outputDir
def go(self, start, end):
start = (start / self.batchSize) * self.batchSize
end = (end / self.batchSize + 1) * self.batchSize
cur = 0
# skip to the start
for _ in range(start / self.batchSize):
cur += self.batchSize
self.parser.getNextBatch()
for _ in range((end - start) / self.batchSize):
dens, _, _ = self.parser.getNextBatch()
r, theta = np.meshgrid(self.params['radialIntervals'], self.params['thetaIntervals'])
plt.ioff()
#-- Plot... ------------------------------------------------
for i in range(len(dens)):
fig = plt.figure()
ax = plt.subplot(111, polar=True)
ax.contourf(theta, r, np.log(dens[i]).transpose(), cmap=plt.cm.afmhot)
ax.scatter([self.secondaryTheta[cur]], [self.secondaryRadius[cur]], s=150)
ax.set_rmax(1.5)
#ax.set_title(r"$\theta_{sec}=" + "{0:.2f}$ rad".format(self.secondaryTheta[cur] % 6.283), va='bottom')
plt.savefig(self.outputDir + "/figs/dens" + str(cur) + ".png")
plt.close(fig)
cur += 1
def finish(self):
os.system("tar -zcvf " + self.outputDir + "/animation.tar.gz " + self.outputDir + "/figs")
def __init__(self, inputDir, outputDir, batchSize):
self.outputDir = outputDir
self.batchSize = batchSize
self.parser = FargoParser(inputDir, batchSize)
secondaryOrbit = np.loadtxt(inputDir + "/planet0.dat")
secondaryX = secondaryOrbit[:, 1]
secondaryY = secondaryOrbit[:, 2]
self.secondaryRadius = np.sqrt(np.add(np.square(secondaryX), np.square(secondaryY)))
self.secondaryTheta = np.arctan2(secondaryY, secondaryX)
params = self.parser.getParams()
self.params = params
self.outputDir = outputDir
def __init__(self, inputDir, outputDir, plotDir, batchSize):
self.outputDir = outputDir
self.parser = FargoParser(inputDir, batchSize)
params = self.parser.getParams()
radIntervals = params['radialIntervals']
numOutputs = params['totalNumOutputs']
timeIntervals = np.linspace(0, numOutputs/5.0, num=numOutputs)
self.params = params
self.outputDir = outputDir
self.plotter = FargoPlotter(radIntervals * 20.0, timeIntervals, plotDir, 'Radius, AU', 'Time, binary periods')
class FargoDiagnosticsRunner:
def __init__(self, inputDir, outputDir, plotDir, batchSize):
self.outputDir = outputDir
self.parser = FargoParser(inputDir, batchSize)
params = self.parser.getParams()
radIntervals = params['radialIntervals']
numOutputs = params['totalNumOutputs']
timeIntervals = np.linspace(0, numOutputs/5.0, num=numOutputs)
self.params = params
self.outputDir = outputDir
self.plotter = FargoPlotter(radIntervals * 20.0, timeIntervals, plotDir, 'Radius, AU', 'Time, binary periods')
def _getDiagnostic(self, fmt):
filePaths = glob.glob(self.outputDir + fmt)
sortedPaths = sorted(filePaths, key=self.parser._extractFileIndex)
arrays = [np.load(path) for path in sortedPaths]
if len(arrays) == 0:
print "didn't find any arrays for format " + fmt
return []
return np.concatenate(arrays)
def runBatches(self):
i = 0
while self.parser.hasRemainingBatches():
dens, vrad, vtheta = self.parser.getNextBatch()
calculations = fd.computeDiagnostics(self.params['radialEdges'], self.params['radialIntervals'],
self.params['thetaIntervals'], dens, vrad, vtheta)
avgDens = np.average(dens, axis=2)
for j in range(0, len(dens), 20):
print 'plotting'
print "length of radialDens: " + str(len(calculations['radialDens']))
self.plotter.threePanelVsRadius(avgDens[j],
calculations['radialEccMK'][j], calculations['radialEccLubow'][j],
calculations['radialPeriMK'][j], calculations['radialPeriLubow'][j],
"%.1f" % ((i + j)/5.0), 'threePanel', i + j)
np.save(self.outputDir + '/radialEccMK' + str(i), calculations['radialEccMK'])
np.save(self.outputDir + '/radialEccLubow' + str(i), calculations['radialEccLubow'])
np.save(self.outputDir + '/radialPeriMK' + str(i), calculations['radialPeriMK'])
np.save(self.outputDir + '/radialPeriLubow' + str(i), calculations['radialPeriLubow'])
np.save(self.outputDir + '/radialDens' + str(i), calculations['radialDens'])
np.save(self.outputDir + '/diskEccMK' + str(i), calculations['diskEccMK'])
np.save(self.outputDir + '/diskPeriMK' + str(i), calculations['diskPeriMK'])
np.save(self.outputDir + '/diskEccLubow' + str(i), calculations['diskEccLubow'])
np.save(self.outputDir + '/diskPeriLubow' + str(i), calculations['diskPeriLubow'])
np.save(self.outputDir + '/totalMass' + str(i), calculations['totalMass'])
np.save(self.outputDir + '/diskRadius90' + str(i), calculations['diskRad90'])
np.save(self.outputDir + '/diskRadius95' + str(i), calculations['diskRad95'])
np.save(self.outputDir + '/lubowVsin' + str(i), calculations['lubowVsin'])
np.save(self.outputDir + '/lubowVcos' + str(i), calculations['lubowVcos'])
i += len(dens)
def runDiskTime(self):
diagnosticTypes = [
{
'fileFormat': '/diskEccMK*.npy',
'arrayFilename': 'eccMKVsTime.npy',
'yName': 'diskEccMK',
'yLabel': 'Disk eccentricity (Mueller-Kley)',
'title': 'Disk eccentricity vs time',
'plot': True
},
{
'fileFormat': '/diskPeriMK*.npy',
'arrayFilename': 'periMKVsTime.npy',
'yName': 'diskPeriMK',
'yLabel': 'Disk periastron angle (MK)',
'title': 'Disk periastron vs time',
'plot': True
},
{
'fileFormat': '/diskEccLubow*.npy',
'arrayFilename': 'eccLubowVsTime.npy',
'yName': 'diskEccLubow',
'yLabel': 'Disk eccentricity (Lubow)',
'title': 'Disk eccentricity vs time',
'plot': True
},
{
'fileFormat': '/diskPeriLubow*.npy',
'arrayFilename': 'periLubowVsTime.npy',
'yName': 'diskPeriLubow',
'yLabel': 'Disk periastron angle (Lubow)',
'title': 'Disk periastron vs time',
'plot': True
},
{
'fileFormat': '/totalMass*.npy',
'arrayFilename': 'massVsTime.npy',
'yName': 'totalMass',
'yLabel': 'Disk mass (code units)',
'title': 'Disk mass vs time',
'plot': True
},
{
'fileFormat': '/diskRadius90*.npy',
'arrayFilename': 'radius90VsTime.npy',
'yName': 'diskRadius90',
'yLabel': 'Disk radius (a, 90%)',
'title': 'Disk radius vs time',
'plot': True
},
{
'fileFormat': '/diskRadius95*.npy',
'arrayFilename': 'radius95VsTime.npy',
'yName': 'diskRadius95',
'yLabel': 'Disk radius (a, 95%)',
'title': 'Disk radius vs time',
'plot': True
},
{
'fileFormat': '/lubowVsin*.npy',
'arrayFilename': 'vsinVsTime.npy',
'yName': 'lubowVsin',
'yLabel': 'Lubow V_sin',
'title': 'Lubow V_sin',
'plot': False
},
{
'fileFormat': '/lubowVcos*.npy',
'arrayFilename': 'vcosVsTime.npy',
'yName': 'lubowVcos',
'yLabel': 'Lubow V_cos',
'title': 'Lubow V_cos',
'plot': False
}
]
diags = {}
for type in diagnosticTypes:
diag = self._getDiagnostic(type['fileFormat'])
diags[type['yName']] = diag
np.save(self.outputDir + '/' + type['arrayFilename'], diag)
for type in diagnosticTypes:
diag = diags[type['yName']]
if type['plot']:
print "plotting vs time " + type['yName']
self.plotter.vsTime(diag, type['yName'], type['yLabel'], type['title'])
eccMK = diags['diskEccMK']
periMK = diags['diskPeriMK']
print "plotting twopanel vs time"
self.plotter.twoPanelVsTime(eccMK, periMK, "eccPeriMK_vs_time")