HDF5矩陣附加在python中

Question

例如，我們有矩陣（例如，我們要存儲numpy數組）並將其存儲在HDF5文件中，然后我們想通過在原始矩陣的末尾追加一些行來擴展矩陣（考慮到原始矩陣可能非常約數十Gb，無法加載到RAM中）

我們還希望能夠在不將整個矩陣加載到RAM中的情況下，從任意點（也許稱為slice（？））讀取矩陣中的幾行。

誰能提供一個示例如何在python中完成嗎？

更新：

我認為另一個選擇是numpy.memmap ，但似乎沒有附加。

這似乎也是一種選擇，但是它可以處理原始二進制數據，但是我想訪問矩陣。在這種情況下，我也不知道如何添加。

Answer 1

如果要使用HDF5文件，那么我建議使用一種可用的庫，例如Pytables。 我在這里發布並簡化了他們的教程： http : //pytables.github.io/usersguide/tutorials.html

from tables import *

# Define a user record to characterize some kind of particles
class Particle(IsDescription):
    name      = StringCol(16)   # 16-character String
    idnumber  = Int64Col()      # Signed 64-bit integer
    ADCcount  = UInt16Col()     # Unsigned short integer
    TDCcount  = UInt8Col()      # unsigned byte
    grid_i    = Int32Col()      # integer
    grid_j    = Int32Col()      # integer
    pressure  = Float32Col()    # float  (single-precision)
    energy    = FloatCol()      # double (double-precision)

filename = "test.h5"
# Open a file in "w"rite mode
h5file = openFile(filename, mode = "w", title = "Test file")
# Create a new group under "/" (root)
group = h5file.createGroup("/", 'detector', 'Detector information')
# Create one table on it
table = h5file.createTable(group, 'readout', Particle, "Readout example")
# Fill the table with 10 particles
particle = table.row
for i in xrange(10):
    particle['name']  = 'Particle: %6d' % (i)
    particle['TDCcount'] = i % 256
    particle['ADCcount'] = (i * 256) % (1 << 16)
    particle['grid_i'] = i
    particle['grid_j'] = 10 - i
    particle['pressure'] = float(i*i)
    particle['energy'] = float(particle['pressure'] ** 4)
    particle['idnumber'] = i * (2 ** 34)
    # Insert a new particle record
    particle.append()
# Close (and flush) the file
h5file.close()

#now we will append some data to the table, after taking some slices 
f=tables.openFile(filename, mode="a")
f.root.detector
f.root.detector.readout
f.root.detector.readout[1::3]
f.root.detector.readout.attrs.TITLE
ro = f.root.detector.readout

#generators work
[row['energy'] for row in ro.where('pressure > 10')]


#append some data
table = f.root.detector.readout
particle = table.row
for i in xrange(10, 15):
  particle['name']  = 'Particle: %6d' % (i)
  particle['TDCcount'] = i % 256
  particle['ADCcount'] = (i * 256) % (1 << 16)
  particle['grid_i'] = i
  particle['grid_j'] = 10 - i
  particle['pressure'] = float(i*i)
  particle['energy'] = float(particle['pressure'] ** 4)
  particle['idnumber'] = i * (2 ** 34)
  particle.append()
table.flush()
f.close()