def __init__(self, time_list, scan_list):
"""
@summary: Initialize the GC-MS data
@param time_list: List of scan retention times
@type time_list: ListType
@param scan_list: List of Scan objects
@type scan_list: ListType
@author: Qiao Wang
@author: Andrew Isaac
@author: Vladimir Likic
"""
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if not is_list(scan_list) or not isinstance(scan_list[0], Scan):
error("'scan_list' must be a list of Scan objects")
self.__set_time(time_list)
self.__scan_list = scan_list
self.__set_min_max_mass()
self.__calc_tic()
def __init__(self, mass_list, intensity_list):
"""
@summary: Initialise the MassSpectrum
@param mass_list: List of binned masses
@type mass_list: ListType
@param intensity_list: List of binned intensities
@type intensity_list: ListType
@author: Andrew Isaac
@author: Qiao Wang
@author: Vladimir Likic
"""
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_list) or \
not is_number(intensity_list[0]):
error("'intensity_list' must be a list of numbers")
if not len(mass_list) == len(intensity_list):
error("'mass_list' is not the same size as 'intensity_list'")
#TODO: should these be public, or accessed through methods???
self.mass_list = mass_list
self.mass_spec = intensity_list
def rmsd(list1, list2):
"""
@summary: Calculates RMSD for the 2 lists
@param list1: First data set
@type list1: ListType, TupleType, or numpy.core.ndarray
@param list2: Second data set
@type list2: ListType, TupleType, or numpy.core.ndarray
@return: RMSD value
@rtype: FloatType
@author: Qiao Wang
@author: Andrew Isaac
@author: Vladimir Likic
"""
if not is_list(list1):
error("argument neither list nor array")
if not is_list(list2):
error("argument neither list nor array")
sum = 0.0
for i in range(len(list1)):
sum = sum + (list1[i] - list2[i]) ** 2
rmsd = math.sqrt(sum / len(list1))
return rmsd
def __init__(self, time_list, scan_list):
"""
@summary: Initialize the GC-MS data
@param time_list: List of scan retention times
@type time_list: ListType
@param scan_list: List of Scan objects
@type scan_list: ListType
@author: Qiao Wang
@author: Andrew Isaac
@author: Vladimir Likic
"""
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if not is_list(scan_list) or not isinstance(scan_list[0], Scan):
error("'scan_list' must be a list of Scan objects")
self.__set_time(time_list)
self.__scan_list = scan_list
self.__set_min_max_mass()
self.__calc_tic()
def __init__(self, mass_list, intensity_list):
"""
@summary: Initialize the Scan data
@param mass_list: mass values
@type mass_list: ListType
@param intensity_list: intensity values
@type intensity_list: ListType
@author: Qiao Wang
@author: Andrew Isaac
@author: Vladimir Likic
"""
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_list) or \
not is_number(intensity_list[0]):
error("'intensity_list' must be a list of numbers")
self.__mass_list = mass_list
self.__intensity_list = intensity_list
self.__min_mass = min(mass_list)
self.__max_mass = max(mass_list)
def __init__(self, mass_list, intensity_list):
"""
@summary: Initialize the Scan data
@param mass_list: mass values
@type mass_list: ListType
@param intensity_list: intensity values
@type intensity_list: ListType
@author: Qiao Wang
@author: Andrew Isaac
@author: Vladimir Likic
"""
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_list) or \
not is_number(intensity_list[0]):
error("'intensity_list' must be a list of numbers")
self.__mass_list = mass_list
self.__intensity_list = intensity_list
self.__min_mass = min(mass_list)
self.__max_mass = max(mass_list)
def __init__(self, mass_list, intensity_list):
"""
@summary: Initialise the MassSpectrum
@param mass_list: List of binned masses
@type mass_list: ListType
@param intensity_list: List of binned intensities
@type intensity_list: ListType
@author: Andrew Isaac
@author: Qiao Wang
@author: Vladimir Likic
"""
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_list) or \
not is_number(intensity_list[0]):
error("'intensity_list' must be a list of numbers")
if not len(mass_list) == len(intensity_list):
error("'mass_list' is not the same size as 'intensity_list'")
#TODO: should these be public, or accessed through methods???
self.mass_list = mass_list
self.mass_spec = intensity_list
def load_peaks(file_name):
"""
@summary: Loads the peak_list stored with 'store_peaks'
@param file_name: File name of peak list
@type file_name: StringType
@return: The list of Peak objects
@rtype: ListType
@author: Andrew Isaac
"""
if not is_str(file_name):
error("'file_name' not a string")
fp = open(file_name,'r')
peak_list = cPickle.load(fp)
fp.close()
if not is_list(peak_list):
error("'file_name' is not a List")
if not len(peak_list) > 0 and not isinstance(peak_list[0], Peak):
error("'peak_list' must be a list of Peak objects")
return peak_list
def load_peaks(file_name):
"""
@summary: Loads the peak_list stored with 'store_peaks'
@param file_name: File name of peak list
@type file_name: StringType
@return: The list of Peak objects
@rtype: ListType
@author: Andrew Isaac
"""
if not is_str(file_name):
error("'file_name' not a string")
fp = open(file_name, 'r')
peak_list = cPickle.load(fp)
fp.close()
if not is_list(peak_list):
error("'file_name' is not a List")
if not len(peak_list) > 0 and not isinstance(peak_list[0], Peak):
error("'peak_list' must be a list of Peak objects")
return peak_list
def exprl2alignment(exprl):
"""
@summary: Converts experiments into alignments
@param exprl: The list of experiments to be converted into an alignment
objects
@type exprl: ListType
@author: Vladimir Likic
"""
if not is_list(exprl):
error("the argument is not a list")
algts = []
for item in exprl:
if not isinstance(item, Experiment):
error("list items must be 'Experiment' instances")
else:
algt = Class.Alignment(item)
algts.append(algt)
return algts
def is_peak_list(peaks):
"""
@summary: Returns True if 'peaks' is a valid peak list, False
otherwise
@param peaks: A list of peak objects
@type peaks: ListType
@return: A boolean indicator
@rtype: BooleanType
@author: Vladimir Likic
"""
flag = True
if not is_list(peaks):
flag = False
else:
for item in peaks:
if not isinstance(item, Peak):
flag = False
return flag
def __init__(self, ia, time_list, mass=None):
"""
@param ia: Ion chromatogram intensity values
@type ia: numpy.array
@param time_list: A list of ion chromatogram retention times
@type time_list: ListType
@param mass: Mass of ion chromatogram (Null if TIC)
@type mass: IntType
@author: Lewis Lee
@author: Vladimir Likic
@author: Vladimir Likic
"""
if not isinstance(ia, numpy.ndarray):
error("'ia' must be a numpy array")
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if len(ia) != len(time_list):
error("Intensity array and time list differ in length")
self.__ia = ia
self.__time_list = time_list
self.__mass = mass
self.__time_step = self.__calc_time_step(time_list)
self.__min_rt = min(time_list)
self.__max_rt = max(time_list)
def MAD(v):
"""
@summary: median absolute deviation
@param v: A list or array
@type v: ListType, TupleType, or numpy.core.ndarray
@return: median absolute deviation
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_list(v):
error("argument neither list nor array")
m = median(v)
m_list = []
for xi in v:
d = math.fabs(xi - m)
m_list.append(d)
mad = median(m_list)/0.6745
return mad
def median(v):
"""
@summary: Returns a median of a list or numpy array
@param v: Input list or array
@type v: ListType or numpy.core.ndarray
@return: The median of the input list
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_list(v):
error("argument neither list nor array")
local_data = copy.deepcopy(v)
local_data.sort()
N = len(local_data)
if (N % 2) == 0:
# even number of points
K = N/2 - 1
median = (local_data[K] + local_data[K+1])/2.0
else:
# odd number of points
K = (N - 1)/2 - 1
median = local_data[K+1]
return median
def std(v):
"""
@summary: Calculates standard deviation
@param v: A list or array
@type v: ListType, TupleType, or numpy.core.ndarray
@return: Mean
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_list(v):
error("argument neither list nor array")
v_mean = mean(v)
s = 0.0
for e in v:
d = e - v_mean
s = s + d*d
s_mean = s/float(len(v)-1)
v_std = math.sqrt(s_mean)
return v_std
def amin(v):
"""
@summary: Finds the minimum element in a list or array
@param v: A list or array
@type v: ListType, TupleType, or numpy.core.ndarray
@return: Tuple (maxi, maxv), where maxv is the minimum
element in the list and maxi is its index
@rtype: TupleType
@author: Vladimir Likic
"""
if not is_list(v):
error("argument neither list nor array")
minv = max(v) # built-in max() function
mini = None
for ii in range(len(v)):
if v[ii] < minv:
minv = v[ii]
mini = ii
if mini == None:
error("finding maximum failed")
return mini, minv
def __init__(self, ia, time_list, mass=None):
"""
@param ia: Ion chromatogram intensity values
@type ia: numpy.array
@param time_list: A list of ion chromatogram retention times
@type time_list: ListType
@param mass: Mass of ion chromatogram (Null if TIC)
@type mass: IntType
@author: Lewis Lee
@author: Vladimir Likic
@author: Vladimir Likic
"""
if not isinstance(ia, numpy.ndarray):
error("'ia' must be a numpy array")
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if len(ia) != len(time_list):
error("Intensity array and time list differ in length")
self.__ia = ia
self.__time_list = time_list
self.__mass = mass
self.__time_step = self.__calc_time_step(time_list)
self.__min_rt = min(time_list)
self.__max_rt = max(time_list)
def exprl2alignment(exprl):
"""
@summary: Converts experiments into alignments
@param exprl: The list of experiments to be converted into an alignment
objects
@type exprl: ListType
@author: Vladimir Likic
"""
if not is_list(exprl):
error("the argument is not a list")
algts = []
for item in exprl:
if not isinstance(item, Experiment):
error("list items must be 'Experiment' instances")
else:
algt = Class.Alignment(item)
algts.append(algt)
return algts
def median_bounds(im, peak, shared=True):
"""
@Summary: Calculates the median of the left and right bounds found
for each apexing peak mass
@param im: The originating IntensityMatrix object
@type im: pyms.GCMS.Class.IntensityMatrix
@param peak: The Peak object
@type peak: pyms.Peak.Class.Peak
@param shared: Include shared ions shared with neighbouring peak
@type shared: BooleanType
@return: median left and right boundary offset in points
@rtype: TupleType
@author: Andrew Isaac
"""
mat = im.get_matrix_list()
ms = peak.get_mass_spectrum()
rt = peak.get_rt()
apex = im.get_index_at_time(rt)
# check if RT based index is simmilar to stored index
tmp = peak.get_pt_bounds()
if is_list(tmp) and apex-1 < tmp[1] and tmp[1] < apex+1:
apex = tmp[1]
# get peak masses with non-zero intensity
mass_ii = [ ii for ii in xrange(len(ms.mass_list)) \
if ms.mass_spec[ii] > 0 ]
# get stats on boundaries
left_list = []
right_list = []
for ii in mass_ii:
# get ion chromatogram as list
ia = [ mat[scan][ii] for scan in xrange(len(mat)) ]
area, left, right, l_share, r_share = ion_area(ia, apex)
if shared or not l_share:
left_list.append(left)
if shared or not r_share:
right_list.append(right)
# return medians
# NB if shared=True, lists maybe empty
l_med = 0
r_med = 0
if len(left_list) > 0:
l_med = median(left_list)
if len(right_list) > 0:
r_med = median(right_list)
return l_med, r_med
def median_bounds(im, peak, shared=True):
"""
@Summary: Calculates the median of the left and right bounds found
for each apexing peak mass
@param im: The originating IntensityMatrix object
@type im: pyms.GCMS.Class.IntensityMatrix
@param peak: The Peak object
@type peak: pyms.Peak.Class.Peak
@param shared: Include shared ions shared with neighbouring peak
@type shared: BooleanType
@return: median left and right boundary offset in points
@rtype: TupleType
@author: Andrew Isaac
"""
mat = im.get_matrix_list()
ms = peak.get_mass_spectrum()
rt = peak.get_rt()
apex = im.get_index_at_time(rt)
# check if RT based index is simmilar to stored index
tmp = peak.get_pt_bounds()
if is_list(tmp) and apex - 1 < tmp[1] and tmp[1] < apex + 1:
apex = tmp[1]
# get peak masses with non-zero intensity
mass_ii = [ ii for ii in xrange(len(ms.mass_list)) \
if ms.mass_spec[ii] > 0 ]
# get stats on boundaries
left_list = []
right_list = []
for ii in mass_ii:
# get ion chromatogram as list
ia = [mat[scan][ii] for scan in xrange(len(mat))]
area, left, right, l_share, r_share = ion_area(ia, apex)
if shared or not l_share:
left_list.append(left)
if shared or not r_share:
right_list.append(right)
# return medians
# NB if shared=True, lists maybe empty
l_med = 0
r_med = 0
if len(left_list) > 0:
l_med = median(left_list)
if len(right_list) > 0:
r_med = median(right_list)
return l_med, r_med
def get_maxima_indices(ion_intensities, points=3):
"""
@summary: Find local maxima.
@param ion_intensities: A list of intensities for a single ion
@type ion_intensities: ListType
@param points: Peak if maxima over 'points' number of scans
@type points: IntType
@return: A list of scan indices
@rtype: ListType
@author: Andrew Isaac
"""
if not is_list(ion_intensities) or not is_number(ion_intensities[0]):
error("'ion_intensities' must be a List of numbers")
# find peak inflection points
# use a 'points' point window
# for a plateau after a rise, need to check if it is the left edge of
# a peak
peak_point = []
edge = -1
points = int(points)
half = int(points/2)
points = 2*half+1 # ensure odd number of points
for index in range(len(ion_intensities)-points+1):
left = ion_intensities[index:index+half]
mid = ion_intensities[index+half]
right = ion_intensities[index+half+1:index+points]
# max in middle
if mid > max(left) and mid > max(right):
peak_point.append(index+half)
edge = -1 # ignore previous rising edge
# flat from rise (left of peak?)
if mid > max(left) and mid == max(right):
edge = index+half # ignore previous rising edge, update latest
# fall from flat
if mid == max(left) and mid > max(right):
if edge > -1:
centre = int((edge+index+half)/2) # mid point
peak_point.append(centre)
edge = -1
return peak_point
def get_maxima_indices(ion_intensities, points=3):
"""
@summary: Find local maxima.
@param ion_intensities: A list of intensities for a single ion
@type ion_intensities: ListType
@param points: Peak if maxima over 'points' number of scans
@type points: IntType
@return: A list of scan indices
@rtype: ListType
@author: Andrew Isaac
"""
if not is_list(ion_intensities) or not is_number(ion_intensities[0]):
error("'ion_intensities' must be a List of numbers")
# find peak inflection points
# use a 'points' point window
# for a plateau after a rise, need to check if it is the left edge of
# a peak
peak_point = []
edge = -1
points = int(points)
half = int(points/2)
points = 2*half+1 # ensure odd number of points
for index in range(len(ion_intensities)-points+1):
left = ion_intensities[index:index+half]
mid = ion_intensities[index+half]
right = ion_intensities[index+half+1:index+points]
# max in middle
if mid > max(left) and mid > max(right):
peak_point.append(index+half)
edge = -1 # ignore previous rising edge
# flat from rise (left of peak?)
if mid > max(left) and mid == max(right):
edge = index+half # ignore previous rising edge, update latest
# fall from flat
if mid == max(left) and mid > max(right):
if edge > -1:
centre = int((edge+index+half)/2) # mid point
peak_point.append(centre)
edge = -1
return peak_point
def sele_peaks_by_rt(peaks, rt_range):
"""
@summary: Selects peaks from a retention time range
@param peaks: A list of peak objects
@type peaks: ListType
@param rt_range: A list of two time strings, specifying lower and
upper retention times
@type rt_range: ListType
@return: A list of peak objects
@rtype: ListType
"""
if not is_peak_list(peaks):
error("'peaks' not a peak list")
if not is_list(rt_range):
error("'rt_range' not a list")
else:
if len(rt_range) != 2:
error("'rt_range' must have exactly two elements")
if not is_str(rt_range[0]) or not is_str(rt_range[1]):
error("lower/upper retention time limits must be strings")
rt_lo = time_str_secs(rt_range[0])
rt_hi = time_str_secs(rt_range[1])
if not rt_lo < rt_hi:
error("lower retention time limit must be less than upper")
peaks_sele = []
for peak in peaks:
rt = peak.get_rt()
if rt > rt_lo and rt < rt_hi:
peaks_sele.append(peak)
# print "%d peaks selected" % (len(peaks_sele))
return peaks_sele
def mean(v):
"""
@summary: Calculates the mean
@param v: A list or array
@type v: ListType, TupleType, or numpy.core.ndarray
@return: Mean
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_list(v):
error("argument neither list nor array")
s = 0.0
for e in v:
s = s + e
s_mean = s/float(len(v))
return s_mean
def set_pt_bounds(self, pt_bounds):
"""
@summary: Sets peak boundaries in points
@param pt_bounds: A list containing left, apex, and right
peak boundaries in points, left and right are offsets
@type pt_bounds: ListType
@return: none
@rtype: NoneType
"""
if not is_list(pt_bounds):
error("'pt_bounds' must be a list")
if not len(pt_bounds) == 3:
error("'pt_bounds' must have exactly 3 elements")
else:
for item in pt_bounds:
if not is_int(item):
error("'pt_bounds' element not an integer")
self.__pt_bounds = pt_bounds
def set_pt_bounds(self, pt_bounds):
"""
@summary: Sets peak boundaries in points
@param pt_bounds: A list containing left, apex, and right
peak boundaries in points, left and right are offsets
@type pt_bounds: ListType
@return: none
@rtype: NoneType
"""
if not is_list(pt_bounds):
error("'pt_bounds' must be a list")
if not len(pt_bounds) == 3:
error("'pt_bounds' must have exactly 3 elements")
else:
for item in pt_bounds:
if not is_int(item):
error("'pt_bounds' element not an integer")
self.__pt_bounds = pt_bounds
def __init__(self, time_list, mass_list, intensity_matrix):
"""
@summary: Initialize the IntensityMatrix data
@param time_list: Retention time values
@type time_list: ListType
@param mass_list: Binned mass values
@type mass_list: ListType
@param intensity_matrix: Binned intensity values per scan
@type intensity_matrix: ListType
@author: Andrew Isaac
"""
# sanity check
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_matrix) or \
not is_list(intensity_matrix[0]) or \
not is_number(intensity_matrix[0][0]):
error("'intensity_matrix' must be a list, of a list, of numbers")
if not len(time_list) == len(intensity_matrix):
error("'time_list' is not the same length as 'intensity_matrix'")
if not len(mass_list) == len(intensity_matrix[0]):
error("'mass_list' is not the same size as 'intensity_matrix'"
" width")
self.__time_list = time_list
self.__mass_list = mass_list
self.__intensity_matrix = intensity_matrix
self.__min_mass = min(mass_list)
self.__max_mass = max(mass_list)
# Direct access for speed (DANGEROUS)
self.intensity_matrix = self.__intensity_matrix
# Try to include parallelism.
try:
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_ranks = comm.Get_size()
rank = comm.Get_rank()
M, N = len(intensity_matrix), len(intensity_matrix[0])
lrr = (rank*M/num_ranks, (rank + 1)*M/num_ranks)
lcr = (rank*N/num_ranks, (rank + 1)*N/num_ranks)
m, n = (lrr[1] - lrr[0], lcr[1] - lcr[0])
self.comm = comm
self.num_ranks = num_ranks
self.rank = rank
self.M = M
self.N = N
self.local_row_range = lrr
self.local_col_range = lcr
self.m = m
self.n = n
# If we can't import mpi4py then continue in serial.
except:
pass
def save_data(file_name,
data,
format_str="%.6f",
prepend="",
sep=" ",
compressed=False):
"""
@summary: Saves a list of numbers or a list of lists of numbers
to a file with specific formatting
@param file_name: Name of a file
@type: StringType
@param data: A list of numbers, or a list of lists
@type: ListType
@param format_str: A format string for individual entries
@type: StringType
@param prepend: A string, printed before each row
@type: StringType
@param sep: A string, printed after each number
@type: StringType
@param compressed: A boolean. If True, the output will be gzipped
@type: BooleanType
@return: none
@rtype: NoneType
@author: Vladimir Likic
"""
if not is_str(file_name):
error("'file_name' is not a string")
if not is_list(data):
error("'data' is not a list")
if not is_str(prepend):
error("'prepend' is not a string")
if not is_str(sep):
error("'sep' is not a string")
fp = open_for_writing(file_name)
# decide whether data is a vector or matrix
if is_number(data[0]):
for item in data:
if not is_number(item):
error("not all elements of the list are numbers")
data_is_matrix = 0
else:
for item in data:
if not is_list(item):
error("not all elements of the list are lists")
data_is_matrix = 1
if data_is_matrix:
for ii in range(len(data)):
fp.write(prepend)
for jj in range(len(data[ii])):
if is_number(data[ii][jj]):
fp.write(format_str % (data[ii][jj]))
if (jj < (len(data[ii]) - 1)): fp.write(sep)
else:
error("datum not a number")
fp.write("\n")
else:
for ii in range(len(data)):
fp.write(prepend)
fp.write(format_str % (data[ii]))
fp.write("\n")
close_for_writing(fp)
if compressed:
status = os.system('gzip %s' % (file_name))
if status != 0:
error("gzip compress failed")
def __init__(self, time_list, mass_list, intensity_matrix):
"""
@summary: Initialize the IntensityMatrix data
@param time_list: Retention time values
@type time_list: ListType
@param mass_list: Binned mass values
@type mass_list: ListType
@param intensity_matrix: Binned intensity values per scan
@type intensity_matrix: ListType
@author: Andrew Isaac
"""
# sanity check
if not is_list(time_list) or not is_number(time_list[0]):
error("'time_list' must be a list of numbers")
if not is_list(mass_list) or not is_number(mass_list[0]):
error("'mass_list' must be a list of numbers")
if not is_list(intensity_matrix) or \
not is_list(intensity_matrix[0]) or \
not is_number(intensity_matrix[0][0]):
error("'intensity_matrix' must be a list, of a list, of numbers")
if not len(time_list) == len(intensity_matrix):
error("'time_list' is not the same length as 'intensity_matrix'")
if not len(mass_list) == len(intensity_matrix[0]):
error("'mass_list' is not the same size as 'intensity_matrix'"
" width")
self.__time_list = time_list
self.__mass_list = mass_list
self.__intensity_matrix = intensity_matrix
self.__min_mass = min(mass_list)
self.__max_mass = max(mass_list)
# Direct access for speed (DANGEROUS)
self.intensity_matrix = self.__intensity_matrix
# Try to include parallelism.
try:
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_ranks = comm.Get_size()
rank = comm.Get_rank()
M, N = len(intensity_matrix), len(intensity_matrix[0])
lrr = (rank*M/num_ranks, (rank + 1)*M/num_ranks)
lcr = (rank*N/num_ranks, (rank + 1)*N/num_ranks)
m, n = (lrr[1] - lrr[0], lcr[1] - lcr[0])
self.comm = comm
self.num_ranks = num_ranks
self.rank = rank
self.M = M
self.N = N
self.local_row_range = lrr
self.local_col_range = lcr
self.m = m
self.n = n
# If we can't import mpi4py then continue in serial.
except:
pass
def save_data(file_name, data, format_str="%.6f", prepend="", sep=" ",
compressed=False):
"""
@summary: Saves a list of numbers or a list of lists of numbers
to a file with specific formatting
@param file_name: Name of a file
@type: StringType
@param data: A list of numbers, or a list of lists
@type: ListType
@param format_str: A format string for individual entries
@type: StringType
@param prepend: A string, printed before each row
@type: StringType
@param sep: A string, printed after each number
@type: StringType
@param compressed: A boolean. If True, the output will be gzipped
@type: BooleanType
@return: none
@rtype: NoneType
@author: Vladimir Likic
"""
if not is_str(file_name):
error("'file_name' is not a string")
if not is_list(data):
error("'data' is not a list")
if not is_str(prepend):
error("'prepend' is not a string")
if not is_str(sep):
error("'sep' is not a string")
fp = open_for_writing(file_name)
# decide whether data is a vector or matrix
if is_number(data[0]):
for item in data:
if not is_number(item):
error("not all elements of the list are numbers")
data_is_matrix = 0
else:
for item in data:
if not is_list(item):
error("not all elements of the list are lists")
data_is_matrix = 1
if data_is_matrix:
for ii in range(len(data)):
fp.write(prepend)
for jj in range(len(data[ii])):
if is_number(data[ii][jj]):
fp.write(format_str % (data[ii][jj]))
if (jj<(len(data[ii])-1)): fp.write(sep)
else:
error("datum not a number")
fp.write("\n")
else:
for ii in range(len(data)):
fp.write(prepend)
fp.write(format_str % (data[ii]))
fp.write("\n")
close_for_writing(fp)
if compressed:
status = os.system('gzip %s' % (file_name))
if status != 0:
error("gzip compress failed")
