def writeViablesPointsHDF5(filename, dt, p0, l0, dp, dl, np, nl):
with open(filename+".txt", 'w') as f:
f.write("Pas de temps : {:f}\n".format(dt))
firstCol,tabp = computeTrajectoryP(dt, p0, l0, dp, dl, np, nl, umax, nmax, pmax, lmax, b, r, q, m)
iLmin=ceil((lmin-l0)/dl)
iLmax=floor((lmax-l0)/dl)
iPmax=floor(pmax/dp)
# preparing regulargridkernel
grid=numpy.array([
i>=iLmin and i<=iLmax and j<=iPmax and
(i<firstCol or (i<firstCol+len(tabp) and p0+j*dp<=tabp[i-firstCol]))
for i in numpy.arange(nl) for j in numpy.arange(np)
]).reshape(np,nl)
rgk = RegularGridKernel([p0,l0],[dp,dl])
rgk.setGrid(grid)
# preparing gridbarkernel
bars = []
for i in range(int(iLmin),int(iLmax+1)):
viablesPoints=numpy.argwhere(grid[i])
if len(viablesPoints)>0:
bars.append([i,viablesPoints[0][0],viablesPoints[-1][0]])
bgk = BarGridKernel([p0,l0],None, None, data=bars)
# writing raw points
for i in range(nl):
for j in range(np):
if grid[i,j]:
f.write("{:f} {:f}\n".format(l0+i*dl,p0+j*dp))
HDF5Manager.writeKernel(rgk, filename+".h5", compression="gzip", compression_opts=9)
writeHDF5_coords(rgk, filename+"_coords.h5", compression="gzip", compression_opts=9)
def testRead():
dataway = '../samples/lake/2D.txt'
metadataway = '../samples/lake/2D_metadata.txt'
h5way = '2D.h5'
hm = HDF5Manager([BarGridKernel])
grid = FileFormatLoader.PspModifiedLoader().read(dataway)
myre = re.compile('^#(.*):(.*)$')
with open(metadataway) as f:
for line in f:
if line.startswith('#'):
k, v = myre.match(line).groups()
grid.metadata[k.strip()] = v.strip()
grid.metadata[METADATA.statedimension] = int(
grid.metadata[METADATA.statedimension])
grid.metadata['results.submissiondate'] = time.strftime(
'%Y-%m-%d %H:%M', time.localtime())
print grid.permutation
print grid.originCoords
hm.writeKernel(grid, h5way)
grid = []
# grid2 = hm.readKernel(h5way)
# print(grid2.metadata)
# print(metadata.category)
# print(grid2.metadata[METADATA.category])
# print(grid2.metadata[METADATA.results_submissiondate])
# print(grid2.metadata[METADATA.results_formatparametervalues])
# print grid2.permutation
# print grid2.originCoords
# print(grid2.kernelMinPoint)
# print(grid2.kernelMaxPoint)
return grid
def testReadKdTree():
dataway = '../samples/3D_languesIsa_dil0.txt'
metadataway = '../samples/3D_languesIsa_dil0_metadata.txt'
h5way = '3D_languesIsa_dil0.h5'
hm = HDF5Manager([KdTree])
metadata = {}
myre = re.compile('^#(.*):(.*)$')
with open(metadataway) as f:
for line in f:
if line.startswith('#'):
k, v = myre.match(line).groups()
metadata[k.strip()] = v.strip()
metadata[METADATA.statedimension] = int(metadata[METADATA.statedimension])
metadata['results.submissiondate'] = time.strftime('%Y-%m-%d %H:%M',
time.localtime())
# return metadata
explorationdomain = metadata[
METADATA.results_softwareparametervalues].split("/")[0].split(",")
origin = explorationdomain[:len(explorationdomain) / 2]
opposite = explorationdomain[len(explorationdomain) / 2:]
k = KdTree.readViabilitree(dataway, metadata, origin, opposite)
print(k.cells[0])
print("Kdtree loaded with %d cells" % len(k.cells))
hm.writeKernel(k, h5way)
k2 = hm.readKernel(h5way)
return k2
def CompareProcedure():
with HDF5Reader('2Dlake_light.h5') as f:
# TODO nothing is done with these metadata
metadata = f.readMetadata()
# reading the data attributes for determining the format
dataAttributes = f.readDataAttributes()
data = f.readData()
print dataAttributes['intervals']
print dataAttributes[METADATA.resultformat_title]
bargridoh = BarGridKernel.initFromHDF5(metadata, dataAttributes, data)
hm = HDF5Manager([BarGridKernel])
bargrid = hm.readKernel('2Dlake_light.h5')
bargrid2 = FileFormatLoader.PspModifiedLoader().read(
'../samples/2D_light.txt')
distancegriddimensions = [31, 31] #[301,301]
distancegridintervals = map(lambda e: e - 1, distancegriddimensions)
resizebargrid = bargrid.toBarGridKernel(bargrid.originCoords,
bargrid.oppositeCoords,
distancegridintervals)
resizebargrid2 = bargrid2.toBarGridKernel(bargrid2.originCoords,
bargrid2.oppositeCoords,
distancegridintervals)
print(bargrid.bars[0])
print(bargrid2.bars[0])
print(bargrid.bars[10000])
print(bargrid2.bars[10000])
for i in range(len(bargrid.bars)):
if bargrid.bars[i][2] != bargrid2.bars[i][2]:
print bargrid.bars[i]
print bargrid2.bars[i]
print "merde"
print(bargrid.originCoords)
print(bargridoh.originCoords)
print(bargrid.oppositeCoords)
print(bargridoh.oppositeCoords)
print(bargrid.intervalNumberperaxis)
print(bargridoh.intervalNumberperaxis)
print(bargrid.permutation)
print(bargridoh.permutation)
print(resizebargrid.bars[0])
print(resizebargrid2.bars[0])
print(resizebargrid.bars[30])
print(resizebargrid2.bars[30])
for i in range(len(resizebargrid.bars)):
if resizebargrid.bars[i][2] != resizebargrid2.bars[i][2]:
print resizebargrid.bars[i]
print resizebargrid2.bars[i]
print "merde"
print "youpi"
break
else:
next_point[i] = start_int[i]
bgk.addBar(next_point, start_int[-1], end_int[-1])
return bgk
if __name__ == "__main__":
data = []
minbounds = []
maxbounds = []
neworigin = []
newopposite = []
resizebargrids = []
hm = HDF5Manager([BarGridKernel])
bargrid = hm.readKernel('2Dlake_light.h5')
data1 = bargrid.getDataToPlot()
intervalSizes = np.array(bargrid.getIntervalSizes())
if (len(minbounds) > 0):
minbounds = [min(minbounds[i],list(np.array(bargrid.getMinBounds())-intervalSizes/2)[i]) for i in range(len(minbounds))]
maxbounds = [max(maxbounds[i],list(np.array(bargrid.getMaxBounds())+intervalSizes/2)[i]) for i in range(len(maxbounds))]
else :
minbounds = list(np.array(bargrid.getMinBounds())-intervalSizes/2)
maxbounds = list(np.array(bargrid.getMaxBounds())+intervalSizes/2)
'''
#To delete to show the original bargrid
distancegriddimensions = [10,10]#[int(ppa),int(ppa)] #[301,301]
distancegridintervals = map(lambda e: e-1, distancegriddimensions)
from django.core.management.base import BaseCommand
from sharekernel.models import *
from django.core.files import File
from FileFormatLoader import Loader
import re
import METADATA
from django.utils import timezone
from hdf5common import HDF5Manager
import tempfile
from BarGridKernel import BarGridKernel
from django.utils.text import slugify
from sharekernel.views import findandsaveobject
from django.contrib.auth.models import User
from init_database import clear_database, create_defaultusers, create_defaultformats
hdf5manager = HDF5Manager([BarGridKernel])
def addKernel(kernel, user):
resultformat_md = {
k: v
for k, v in kernel.metadata.iteritems() if k.startswith("resultformat")
}
resultformat = findandsaveobject(
ResultFormat,
metadata={
METADATA.resultformat_title:
resultformat_md[METADATA.resultformat_title]
},
fields={'submitter': user},
add_metadata=resultformat_md)
def initFromHDF5(cls, metadata, dataAttributes, data):
'''
Create an object of class BarGridKernel from attributes and data loaded from an HDF5 file. This method is intended to be used by the method hdf5common.readKernel
'''
return cls(dataAttributes['origin'], dataAttributes['steps'], data=data, metadata=metadata)
@overrides
def getData(self):
return self.grid
def setGrid(self, grid):
self.dimensionsExtents = grid.shape
self.grid = grid
def set(self, coords, value):
self.grid.put([coords], value)
def get(self, coords):
return self.grid[coords]
@overrides
def isInSet(self, point):
# TODO
raise NotImplementedError
if __name__ == "__main__":
from hdf5common import HDF5Manager
grid = RegularGridKernel([0,0,0], [1,1,1], [10,10,10])
grid.set([3,1,0], True)
HDF5Manager.writeKernel(grid, 'test.h5')
return cls(dataAttributes['origin'],
dataAttributes['steps'],
data=data,
metadata=metadata)
@overrides
def getData(self):
return self.grid
def setGrid(self, grid):
self.dimensionsExtents = grid.shape
self.grid = grid
def set(self, coords, value):
self.grid.put([coords], value)
def get(self, coords):
return self.grid[coords]
@overrides
def isInSet(self, point):
# TODO
raise NotImplementedError
if __name__ == "__main__":
from hdf5common import HDF5Manager
grid = RegularGridKernel([0, 0, 0], [1, 1, 1], [10, 10, 10])
grid.set([3, 1, 0], True)
HDF5Manager.writeKernel(grid, 'test.h5')
def __init__(self, strategies=[BarGridKernel, KdTree]):
self.hdf5manager = HDF5Manager(strategies)