def buildHDF(inputFile, inputData, inputLabels, debug=False):
"""Creates a HDF file based on the data given, two possible datasets
can be built, 25band set and 32 band set"""
#Generate HDF5 file for input data stored as a list of datacube
HDFile = dcb_HDF5.openTable(inputFile)
data_gp = dcb_HDF5.build25BandGroup(HDFile, "data")
#determine the number of bands in the data, as well as band wavelenghts
bands = inputData.shape()
data_gp.attrs["RPArrowPrism"] = str(bands[2]) + ' Bands'
label_gp = dcb_HDF5.build25BandGroup(HDFile, 'label')
for p, data in enumerate(
inputData
): #with fix in create_bsq_dataset, now masks and data should be in same data struct
if debug:
if p == len(inputData) - 1:
print(p, inputData[p].Name, "LAST ITEM")
if (inputData[p].Name == data.Name): print(inputData[p].Name)
labelSet = dcb_HDF5.addDataset(label_gp, inputData[p].Name,
inputData[p].MaskData, debug)
dataSet = dcb_HDF5.addDataset(data_gp, inputData[p].Name,
inputData[p].HSdata, debug)
dataSet.attrs["units"] = "AU"
labelSet.attrs["Parent_DCB"] = inputData[p].Name
dcb_HDF5.saveClose(HDFile) #add label to file under correct filename
def buildHDF(inputFile, inputData, inputLabels, debug=False):
"""Creates a HDF file based on the data given, two possible datasets
can be built, 25band set and 32 band set"""
# Generate HDF5 file for input data stored as a list of datacube
HDFile = dcb_HDF5.openTable(inputFile)
data_gp = dcb_HDF5.build25BandGroup(HDFile, "data")
# determine the number of bands in the data, as well as band wavelenghts
bands = inputData.shape()
data_gp.attrs["RPArrowPrism"] = str(bands[2]) + " Bands"
label_gp = dcb_HDF5.build25BandGroup(HDFile, "label")
for p, data in enumerate(
inputData
): # with fix in create_bsq_dataset, now masks and data should be in same data struct
if debug:
if p == len(inputData) - 1:
print(p, inputData[p].Name, "LAST ITEM")
if inputData[p].Name == data.Name:
print(inputData[p].Name)
labelSet = dcb_HDF5.addDataset(label_gp, inputData[p].Name, inputData[p].MaskData, debug)
dataSet = dcb_HDF5.addDataset(data_gp, inputData[p].Name, inputData[p].HSdata, debug)
dataSet.attrs["units"] = "AU"
labelSet.attrs["Parent_DCB"] = inputData[p].Name
dcb_HDF5.saveClose(HDFile) # add label to file under correct filename
def readHDF(inputFile, debug=False):
a = []
with HDF.File(inputFile, "r+") as f:
if debug:
print(f.name)
l = list(f.keys()) # extract keys in root dir of HDF file
data = f["Data"]
masks = f["Masks"]
j = getKeys(f, "Masks")
k = getKeys(f, "Data")
wbc, oth, count = [], [], 0 # settings some initial values
mT = f["data/" + k[count]][..., 0]
for p in k:
if debug:
print(count) # remove later
m1 = f["Masks/" + j[count]][...] # Likewise for the mask data
if debug:
print(np.shape(m1))
d1 = f["Data/" + [count]][...] # numpy style referencing to return nnumpy array of data
if debug:
print(np.shape(d1))
if count == 0:
if debug:
print("wat") # to be removed
wbc = d1[m1.astype(bool)] # compile a dataset of wbc vectors
oth = d1[np.invert(m1.astype(bool))] # compile a dataset of non-wbc vectors
tot = d1[mT.astype(bool)] # compile a dataset of all vectors
cls = m1.ravel()
else:
wbc = np.vstack((wbc, d1[m1.astype(bool)]))
oth = np.vstack((oth, d1[np.invert(m1.astype(bool))]))
tot = np.vstack((tot, d1[mT.astype(bool)])) # appending vectors into band*(x*y) array
cls = np.hstack((cls, m1.ravel()))
count += 1
if debug:
print(np.shape(wbc))
print(np.shape(oth))
print(np.shape(tot))
print(cls.shape)
e = dcb_HDF5.saveClose(f)
if e:
print("File " + inputFile + " saved Successfully!")
def readHDF(inputFile, debug=False):
a = []
with HDF.File(inputFile, 'r+') as f:
if debug: print(f.name)
l = list(f.keys()) #extract keys in root dir of HDF file
data = f["Data"]
masks = f["Masks"]
j = getKeys(f, "Masks")
k = getKeys(f, "Data")
wbc, oth, count = [], [], 0 # settings some initial values
mT = f["data/" + k[count]][..., 0]
for p in k:
if debug: print(count) # remove later
m1 = f["Masks/" + j[count]][...] #Likewise for the mask data
if debug: print(np.shape(m1))
d1 = f["Data/" + [count]][
...] #numpy style referencing to return nnumpy array of data
if debug: print(np.shape(d1))
if count == 0:
if debug: print('wat') #to be removed
wbc = d1[m1.astype(bool)] #compile a dataset of wbc vectors
oth = d1[np.invert(
m1.astype(bool))] #compile a dataset of non-wbc vectors
tot = d1[mT.astype(bool)] #compile a dataset of all vectors
cls = m1.ravel()
else:
wbc = np.vstack((wbc, d1[m1.astype(bool)]))
oth = np.vstack((oth, d1[np.invert(m1.astype(bool))]))
tot = np.vstack((tot, d1[mT.astype(bool)]
)) # appending vectors into band*(x*y) array
cls = np.hstack((cls, m1.ravel()))
count += 1
if debug:
print(np.shape(wbc))
print(np.shape(oth))
print(np.shape(tot))
print(cls.shape)
e = dcb_HDF5.saveClose(f)
if (e): print("File " + inputFile + " saved Successfully!")
maskSet = dcb_HDF5.addDataset(m_group,maskList[p].Name,maskList[p].MaskData)
maskSet.attrs["Parent_DCB"] = dataList[p].Name
#data.setMaskData(maskList[p].MaskData)
#hsList.append(data)
if p == len(dataList)-1:
print(p, data.Name, "LAST ITEM") #only happens when last iteration of for loop runs
print(data.Name + str(p))
tTable = dcb_HDF5.addDataset(d_group,data.Name,dataList[p].HSdata)
tTable.attrs["units"] = "AU"
HDFile.flush()
#tTable = thesis_TABLE.addTable2Group(d_group,HDFile,data)
#thesis_TABLE.add25Vector2DataCube(tTable,data)
dcb_HDF5.saveClose(HDFile)
ddd = dataList[1].HSdata
#print(np.shape(ddd)[2])
im2 = dataList[1].MaskData
rd = ddd[im2.astype(bool)] #returns masked by im2
id = ddd[np.invert(im2.astype(bool))]
#print([np.shape(rd), np.count_nonzero(im2)])
#print([np.shape(ddd), np.shape(im2)])
samp = ddd[:,:,0]
#out = Image.fromarray(im2[:,:,0])
maskplot = plt.imshow(np.float32(im2))
dataplot = plt.imshow(np.float32(samp)) #imshow only works with 32bit grayscale
scipy.misc.imsave(pathName+'Mask.png', im2)
