def to_h5(metAry, dest, debug=False):
"""
Write the metAry into given file path in the HDF5 format
dest can be string or h5py.Group object.
If dest is a string, it is interpret as the destination file path.
If dest is a h5py.Group object, the content will be store under the given group.
"""
# Writing to existing group
if isinstance(dest, h5py.Group):
dest.create_dataset('ndarray', data=metAry.data) # Write the array
__dict_loop(metAry.info, dest.create_group('info')) # Write the meta info
return
# Writing file to path
path = filePath(dest)
if not path.write:
raise ValueError("Unable to write to: " + str(path.full))
with h5py.File(path.full, 'w') as f:
f.create_dataset('ndarray', data=metAry.data) # Write the array
__dict_loop(metAry.info, f.create_group('info')) # Write the meta info
return
def from_h5(src, debug=False):
"""
Read the HDF5 file in the given path, build the metAry accordingly.
dest can be string or h5py.Group object.
If src is a string, it is interpret as the destination file path.
If src is a h5py.Group object, the content will be read from the given group.
"""
# Reading from existing group
if isinstance(src, h5py.Group):
ary = src['ndarray'][()] # Read the array
info = __read_info(src['info']) # Read the meta info
# Reading from file path
path = filePath(src)
if not path.exist:
raise IOError('File ' + str(path.full) + ' does not exist')
if not path.read:
raise IOError("Unable to read from: " + str(path.full))
with h5py.File(path.full, 'r') as f:
ary = f['ndarray'][()] # Read the array
info = __read_info(f['info']) # Read the meta info
return metaArray(ary, info=info)
def __init__(self, path, debug=False):
self.file_path = filePath(path)
self.unpack_str = ''
self.header_len = 0
self.endian = '<'
self.record_pos = 0
self.record_num = 0
self.record_index = []
self.flg_debug = debug
# Try to guess parameters like byte Order and header length.
if self._parameterChk_():
self._index_() # Index the file
else:
# No idea how to unpack the records
msg = "Can not guess how to unpack the records. " + \
"Please try to specify the following parameters manually: " + sep + \
"'.header_len'" + sep + \
"'.unpack_str'" + sep + \
"'.endian'" + sep + \
"then index the file manually using '._index_()'"
print(msg)
if debug:
print'file_path: ', self.file_path.full
print'unpack_str: ', self.unpack_str
print'header_len: ', self.header_len
print'record_pos: ', self.record_pos
print'record_num: ', self.record_num
return
def to_csv(metAry, path, debug=False, \
field_delimiter=',', text_delimiter='"', linesep="\r\n"):
"""
Write the metAry into given file path in the CSV format
dest can be string or h5py.Group object.
If dest is a string, it is interpret as the destination file path.
If dest is a h5py.Group object, the content will be store under the given group.
"""
path = filePath(path)
FD = field_delimiter
TD = text_delimiter
LS = linesep
if not path.write:
print("Given file path is not writable." + path.full)
raise IOError
info = metAry.copy_info()
data = metAry.data
nfo_keys = info.keys()
nfo_keys.sort()
with open(path.full, 'wb') as f:
# Write out the meta info first
for key in nfo_keys:
val = info.pop(key)
if isinstance(val, (int, long, float, complex)):
val = str(val)
else:
val = TD + str(val) + TD
f.write(key + FD + val + LS)
# Write out the content, format depends on the number of data dimensions
if data.ndim == 1:
# One dimentional data, write out the index - value pairs
content = zip(metAry.get_axis(), data)
for idx, val in content:
f.write(str(idx) + FD + str(val) + LS)
elif data.ndim == 2:
# Two dimensional data, write out the x-y grid
x, y = data.shape
for x_idx in range(x):
row = FD.join(map(str, data[x_idx]))
f.write(row + LS)
else:
# N-dimensional data, flatten the array, the dump
f.write(LS.join(map(str, data.flatten())))
f.write(LS)
return
def __init__(self, path=None, debug=False, analyse=True, \
buffer_size=10485760, field_delimiter=',', text_delimiter='"'):
"""
Given the file path, prepare the csv file.
Options:
analyse If true will try to scan the file to guess where the
numerical data starts. It can take a long time for large
files of unsual layouts.
"""
self.file_path = path
self.name = filePath(path).name
self.analyse = analyse
self.debug = debug
# self.f_handler = None
self.rows = None # Number of rows
self.cols = None # Number of column
self.idx = None # File seek index, linking the file
# byte position with each non-blank
# rows.
self.metainfo = {} # File header representations
self.buffer_size = buffer_size # Read file in this size chunks
self.field_delimiter = field_delimiter
self.text_delimiter = text_delimiter
self.label_row = 0 # Row number for column labels
self.data_start = 0 # Row number for where data starts
# Check if the file is readable
f = self.open()
cols = 0
f.seek(0)
idx = [0] # Byte position index of all non-blank rows
#######################################################################
# "for line in f" doesnt work because f.tell() will be stuck at certain
# multiples of buffer length.
#######################################################################
#for line in f:
#
# line = line.strip()
#
# # Skip blank lines
# if ''.join(line.split(field_delimiter)) == '':
# continue
# else:
# idx.append(f.tell())
#
# items = len(line.split(field_delimiter))
# if items > cols:
# cols = items
#######################################################################
while True:
line = f.readline() # Read the CVS file line by line.
# Not used readlines because the file
# can potentially be very large
if line == '':
del idx[-1] # Remove the last index entry
break # Reached the end of the file
line = line.strip() # strip of '\n'
lst = line.split(field_delimiter)
#if ''.join(lst) == '':
# continue # In case of a blank row
#else:
# idx.append(f.tell()) # Write down the next byte position
idx.append(f.tell()) # Don't ignore blank rows
items = len(lst)
if items > cols:
cols = items
self.rows = len(idx)
self.cols = cols
self.idx = idx
f.close()
if analyse == True:
self.chk_data_start()
# Try to read the header if exists (i.e. data isn't starting on the 1st row
if self.data_start != 0:
self.getmetainfo()
return
def to_csv(metAry, path, debug=False, \
field_delimiter=',', text_delimiter='"', linesep="\r\n"):
"""
Write the metAry into given file path in the CSV format
dest can be string or h5py.Group object.
If dest is a string, it is interpret as the destination file path.
If dest is a h5py.Group object, the content will be store under the given group.
"""
path = filePath(path)
FD = field_delimiter
TD = text_delimiter
LS = linesep
if not path.write:
print("Given file path is not writable." + path.full)
raise IOError
info = metAry.copy_info()
data = metAry.data
nfo_keys = info.keys()
nfo_keys.sort()
with open(path.full, 'wb') as f:
# Write out the meta info first
for key in nfo_keys:
val = info.pop(key)
if isinstance(val, (int, long, float, complex)):
val = str(val)
else:
val = TD + str(val) + TD
f.write(key + FD + val + LS)
# Write out the content, format depends on the number of data dimensions
if data.ndim == 1:
# One dimentional data, write out the index - value pairs
content = zip(metAry.get_axis(), data)
for idx, val in content:
f.write(str(idx) + FD + str(val) + LS)
elif data.ndim == 2:
# Two dimensional data, write out the x-y grid
x, y = data.shape
for x_idx in range(x):
row = FD.join(map(str, data[x_idx]))
f.write(row + LS)
else:
# N-dimensional data, flatten the array, the dump
f.write(LS.join(map(str, data.flatten())))
f.write(LS)
return
def __init__(self, path=None, debug=False, analyse=True, \
buffer_size=10485760, field_delimiter=',', text_delimiter='"'):
"""
Given the file path, prepare the csv file.
Options:
analyse If true will try to scan the file to guess where the
numerical data starts. It can take a long time for large
files of unsual layouts.
"""
self.file_path = path
self.name = filePath(path).name
self.analyse = analyse
self.debug = debug
# self.f_handler = None
self.rows = None # Number of rows
self.cols = None # Number of column
self.idx = None # File seek index, linking the file
# byte position with each non-blank
# rows.
self.metainfo = {} # File header representations
self.buffer_size = buffer_size # Read file in this size chunks
self.field_delimiter = field_delimiter
self.text_delimiter = text_delimiter
self.label_row = 0 # Row number for column labels
self.data_start = 0 # Row number for where data starts
# Check if the file is readable
f = self.open()
cols = 0
f.seek(0)
idx = [0] # Byte position index of all non-blank rows
#######################################################################
# "for line in f" doesnt work because f.tell() will be stuck at certain
# multiples of buffer length.
#######################################################################
#for line in f:
#
# line = line.strip()
#
# # Skip blank lines
# if ''.join(line.split(field_delimiter)) == '':
# continue
# else:
# idx.append(f.tell())
#
# items = len(line.split(field_delimiter))
# if items > cols:
# cols = items
#######################################################################
while True:
line = f.readline() # Read the CVS file line by line.
# Not used readlines because the file
# can potentially be very large
if line == '':
del idx[-1] # Remove the last index entry
break # Reached the end of the file
line = line.strip() # strip of '\n'
lst = line.split(field_delimiter)
#if ''.join(lst) == '':
# continue # In case of a blank row
#else:
# idx.append(f.tell()) # Write down the next byte position
idx.append(f.tell()) # Don't ignore blank rows
items = len(lst)
if items > cols:
cols = items
self.rows = len(idx)
self.cols = cols
self.idx = idx
f.close()
if analyse == True:
self.chk_data_start()
# Try to read the header if exists (i.e. data isn't starting on the 1st row
if self.data_start != 0:
self.getmetainfo()
return
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
# MA 02110-1301, USA.
'''
Demo Programme that should the basics of using metaArray project
'''
from os.path import join
from os import linesep
from textwrap import TextWrapper
import cStringIO
from metaArray.misc import filePath
# Enviromental variables
demo_dir = join(filePath(__file__).baseDir, 'example')
tty_width = 72
partition = '-' * tty_width
prompt = '>>> '
# Current dir
# current_dir = dirPath('./')
wrapper = TextWrapper()
wrapper.width = tty_width
wrapper.replace_whitespace = False
# wrapper.drop_whitespace = False
wrapper.initial_indent = "- "
wrapper.subsequent_indent = '- '
def __init__(self, path, debug=False, buffer_size=4096):
"""
4kB buffer size
"""
self.file_path = filePath(path)
self.debug = debug
self.buffer_size = buffer_size = buffer_size * 1024 # f.read(buffer_size) In case of very large files
self.idx = idx = [] # Index of the records in the file, each item
# should have the format:
# [hdr_pos, hdr_len, data_pos, data_len, header_dict, unpack_str]
#metainfo = self.metainfo = {} # File header representations
# Known header fields and value type.
# This is only used for data type conversion from the byte stream
# String values are left as is
hdr_format = self.hdr_format = []
hdr_format.append([':WFMP:NR_P', int])
hdr_format.append([':WFMPRE:NR_PT', int])
hdr_format.append([':WFMP:BYT_N', int])
hdr_format.append([':WFMPRE:BYT_NR', int])
hdr_format.append([':WFMO:BYT_N', int])
hdr_format.append(['BIT_N', int])
hdr_format.append(['BIT_NR', int])
# ENC or ENCDG -> BIN
# BN_F or BN_FMT-> RI
# BYT_O or BYT_OR -> LSB or MSB
# CH2:WFID "Ch2, AC coupling, 20mVolts/div, 50ns/div, 50000 points, Sample mode";
# WFI "Ch2, DC coupling, 1.000mV/div, 40.00us/div, 1000000 points, Average mode";
# PT_F or PT_FMT -> Y
# XUN or XUNIT -> "s"
hdr_format.append(['NR_P', int])
hdr_format.append(['NR_PT', int])
hdr_format.append(['PT_O', int])
hdr_format.append(['PT_OFF', int])
# PT_OR LINEA # Always LINEAr
hdr_format.append(['XIN', float])
hdr_format.append(['XINCR', float])
hdr_format.append(['XZE', float])
# YUN or YUNIT -> "V" or "Volts"
hdr_format.append(['YMU', float])
hdr_format.append(['YMULT', float])
hdr_format.append(['YOF', float])
hdr_format.append(['YOFF', float])
hdr_format.append(['YZE', float])
hdr_format.append(['YZERO', float])
hdr_format.append(['VSCALE', float])
hdr_format.append(['HSCALE', float])
hdr_format.append(['VPOS', float])
hdr_format.append(['VOFFSET', float])
hdr_format.append(['HDELAY', float])
# COMP -> COMPOSITE_YT
hdr_format.append(['FILTERF', int])
hdr_format.append(['CENTERFREQUENCY', float])
# DOMAIN -> TIME
hdr_format.append(['REFLEVEL', float])
hdr_format.append(['SPAN', float])
# WFMTYPE -> ANALOG
# :CURV -> #72000000
debug_str = ''
# Identify the header and data byte positions in the byte streams
#
# The data string can take the following forms:
#
# ":WFMPRE:" --- Header info ---- ":CURVE #" ------ Binary Data -----
# ":WFMP:" ----- Header info ---- ":CURV #" ------- Binary Data -----
# END structure INIT
f = self.open()
f_pos = 0
# Identify key locations in the data stream, write into header_rcd
# There maybe multiple header-data streams
while True:
# Find the beginning of the header
hdr_start = buffered_search(f, ':WFMP:', start=f_pos, buffer_size=buffer_size)
if hdr_start == -1:
hdr_start = buffered_search(f, ':WFMPRE:', start=f_pos, buffer_size=buffer_size)
if hdr_start == -1:
if debug > 0:
debug_str += 'Neither header descriptors (":WFMP:" or ":WFMPRE:") is found.'
print(debug_str)
break # no more header found
elif debug > 0:
debug_str += 'Header descriptor ":WFMPRE:" found at ' + str(hdr_start) + linesep
elif debug > 0:
debug_str += 'Header descriptor ":WFMP:" found at ' + str(hdr_start) + linesep
# Find the following data stream
data_start = buffered_search(f, ':CURV #', start=hdr_start, buffer_size=buffer_size)
if data_start == -1:
data_start = buffered_search(f, ':CURVE #', start=hdr_start, buffer_size=buffer_size)
if data_start == -1:
# Very bad, found header but no data!
# Show debug info if requested, ignore otherwise
if debug > 0:
debug_str += 'Failed to find the following data stream!'
print(debug_str)
f_pos += 6
continue
elif debug > 0:
debug_str += 'Data descriptor ":CURVE #" found at ' + str(data_start) + linesep
elif debug > 0:
debug_str += 'Data descriptor ":CURV #" found at ' + str(data_start) + linesep
# Work out the length of the data stream is
# :CURVE #
# :CURV #<x><yyy><data><newline>
f.seek(data_start)
buf = f.read(20)
pos_x = buf.find('#') + 1
pos_yyy = pos_x + 1
desc_len = int(buf[pos_x:pos_yyy]) # <x>
pos_data = pos_yyy + desc_len
data_byte_len = int(buf[pos_yyy:pos_data]) # <yyy>
# Parse the headers
# Include ":CURV #<x><yyy>" into the header
data_start += pos_data
hdr_len = data_start-hdr_start
# Read the header byte stream
f.seek(hdr_start)
hdr_dict = self.proc_header(f.read(hdr_len))
# Have a quick guess on the unpack string, this is the most rudimentary
# information necessary to decode the binary data
# unpack_str == None if unable to work out from here
unpack_str = self.get_unpackstr(hdr_dict)
if debug > 0:
if unpack_str is None:
debug_str += 'Unable to guess how to unpack the binary data.' + linesep
debug_str += 'Require the knowledge of at least the following header fields:' + linesep
debug_str += '\t BYT_O(R)' + linesep
debug_str += '\t NR_P(T)' + linesep
debug_str += '\t BIT_N(R)' + linesep
debug_str += '\t BN_F(MT)' + linesep
else:
debug_str += 'Binary data is thought to be packed as: ' + unpack_str + linesep
# Assemble into index list
# idx [hdr_pos, hdr_len, data_pos, data_len, hdr_dict, unpack_str]
idx.append([hdr_start, hdr_len, data_start, data_byte_len, hdr_dict, unpack_str])
# Advance to the end of the data stream, prepare for the next search loop
f_pos = data_start + data_byte_len
if debug > 0:
debug_str += 'Continue searching for the next record from ' + str(f_pos) + ' byte......'
print(debug_str)
debug_str = ''
f.close()
return
def __init__(self, path, debug=False, buffer_size=4096):
"""
4kB buffer size
"""
self.file_path = filePath(path)
self.debug = debug
self.buffer_size = buffer_size = buffer_size * 1024 # f.read(buffer_size) In case of very large files
self.idx = idx = [] # Index of the records in the file, each item
# should have the format:
# [hdr_pos, hdr_len, data_pos, data_len, header_dict, unpack_str]
#metainfo = self.metainfo = {} # File header representations
# Known header fields and value type.
# This is only used for data type conversion from the byte stream
# String values are left as is
hdr_format = self.hdr_format = []
hdr_format.append([':WFMP:NR_P', int])
hdr_format.append([':WFMPRE:NR_PT', int])
hdr_format.append([':WFMP:BYT_N', int])
hdr_format.append([':WFMPRE:BYT_NR', int])
hdr_format.append([':WFMO:BYT_N', int])
hdr_format.append(['BIT_N', int])
hdr_format.append(['BIT_NR', int])
# ENC or ENCDG -> BIN
# BN_F or BN_FMT-> RI
# BYT_O or BYT_OR -> LSB or MSB
# CH2:WFID "Ch2, AC coupling, 20mVolts/div, 50ns/div, 50000 points, Sample mode";
# WFI "Ch2, DC coupling, 1.000mV/div, 40.00us/div, 1000000 points, Average mode";
# PT_F or PT_FMT -> Y
# XUN or XUNIT -> "s"
hdr_format.append(['NR_P', int])
hdr_format.append(['NR_PT', int])
hdr_format.append(['PT_O', int])
hdr_format.append(['PT_OFF', int])
# PT_OR LINEA # Always LINEAr
hdr_format.append(['XIN', float])
hdr_format.append(['XINCR', float])
hdr_format.append(['XZE', float])
# YUN or YUNIT -> "V" or "Volts"
hdr_format.append(['YMU', float])
hdr_format.append(['YMULT', float])
hdr_format.append(['YOF', float])
hdr_format.append(['YOFF', float])
hdr_format.append(['YZE', float])
hdr_format.append(['YZERO', float])
hdr_format.append(['VSCALE', float])
hdr_format.append(['HSCALE', float])
hdr_format.append(['VPOS', float])
hdr_format.append(['VOFFSET', float])
hdr_format.append(['HDELAY', float])
# COMP -> COMPOSITE_YT
hdr_format.append(['FILTERF', int])
hdr_format.append(['CENTERFREQUENCY', float])
# DOMAIN -> TIME
hdr_format.append(['REFLEVEL', float])
hdr_format.append(['SPAN', float])
# WFMTYPE -> ANALOG
# :CURV -> #72000000
debug_str = ''
# Identify the header and data byte positions in the byte streams
#
# The data string can take the following forms:
#
# ":WFMPRE:" --- Header info ---- ":CURVE #" ------ Binary Data -----
# ":WFMP:" ----- Header info ---- ":CURV #" ------- Binary Data -----
# END structure INIT
f = self.open()
f_pos = 0
# Identify key locations in the data stream, write into header_rcd
# There maybe multiple header-data streams
while True:
# Find the beginning of the header
hdr_start = buffered_search(f,
':WFMP:',
start=f_pos,
buffer_size=buffer_size)
if hdr_start == -1:
hdr_start = buffered_search(f,
':WFMPRE:',
start=f_pos,
buffer_size=buffer_size)
if hdr_start == -1:
if debug > 0:
debug_str += 'Neither header descriptors (":WFMP:" or ":WFMPRE:") is found.'
print(debug_str)
break # no more header found
elif debug > 0:
debug_str += 'Header descriptor ":WFMPRE:" found at ' + str(
hdr_start) + linesep
elif debug > 0:
debug_str += 'Header descriptor ":WFMP:" found at ' + str(
hdr_start) + linesep
# Find the following data stream
data_start = buffered_search(f,
':CURV #',
start=hdr_start,
buffer_size=buffer_size)
if data_start == -1:
data_start = buffered_search(f,
':CURVE #',
start=hdr_start,
buffer_size=buffer_size)
if data_start == -1:
# Very bad, found header but no data!
# Show debug info if requested, ignore otherwise
if debug > 0:
debug_str += 'Failed to find the following data stream!'
print(debug_str)
f_pos += 6
continue
elif debug > 0:
debug_str += 'Data descriptor ":CURVE #" found at ' + str(
data_start) + linesep
elif debug > 0:
debug_str += 'Data descriptor ":CURV #" found at ' + str(
data_start) + linesep
# Work out the length of the data stream is
# :CURVE #
# :CURV #<x><yyy><data><newline>
f.seek(data_start)
buf = f.read(20)
pos_x = buf.find('#') + 1
pos_yyy = pos_x + 1
desc_len = int(buf[pos_x:pos_yyy]) # <x>
pos_data = pos_yyy + desc_len
data_byte_len = int(buf[pos_yyy:pos_data]) # <yyy>
# Parse the headers
# Include ":CURV #<x><yyy>" into the header
data_start += pos_data
hdr_len = data_start - hdr_start
# Read the header byte stream
f.seek(hdr_start)
hdr_dict = self.proc_header(f.read(hdr_len))
# Have a quick guess on the unpack string, this is the most rudimentary
# information necessary to decode the binary data
# unpack_str == None if unable to work out from here
unpack_str = self.get_unpackstr(hdr_dict)
if debug > 0:
if unpack_str is None:
debug_str += 'Unable to guess how to unpack the binary data.' + linesep
debug_str += 'Require the knowledge of at least the following header fields:' + linesep
debug_str += '\t BYT_O(R)' + linesep
debug_str += '\t NR_P(T)' + linesep
debug_str += '\t BIT_N(R)' + linesep
debug_str += '\t BN_F(MT)' + linesep
else:
debug_str += 'Binary data is thought to be packed as: ' + unpack_str + linesep
# Assemble into index list
# idx [hdr_pos, hdr_len, data_pos, data_len, hdr_dict, unpack_str]
idx.append([
hdr_start, hdr_len, data_start, data_byte_len, hdr_dict,
unpack_str
])
# Advance to the end of the data stream, prepare for the next search loop
f_pos = data_start + data_byte_len
if debug > 0:
debug_str += 'Continue searching for the next record from ' + str(
f_pos) + ' byte......'
print(debug_str)
debug_str = ''
f.close()
return