def write(self, filename=None):
"""Write array to xvg file *filename* in NXY format.
.. Note:: Only plain files working at the moment, not compressed.
"""
self._init_filename(filename)
with utilities.openany(self.real_filename, 'w') as xvg:
xvg.write("# xmgrace compatible NXY data file\n"
"# Written by gromacs.formats.XVG()\n")
xvg.write("# :columns: %r\n" % self.names)
for xyy in self.array.T:
xyy.tofile(xvg, sep=" ", format="%-8s") # quick and dirty ascii output...--no compression!
xvg.write('\n')
def write(self, filename=None):
"""Write array to xvg file *filename* in NXY format.
.. Note:: Only plain files working at the moment, not compressed.
"""
self._init_filename(filename)
with utilities.openany(self.real_filename, 'w') as xvg:
xvg.write("# xmgrace compatible NXY data file\n"
"# Written by gromacs.formats.XVG()\n")
xvg.write("# :columns: {0!r}\n".format(self.names))
for xyy in self.array.T:
xyy.tofile(xvg, sep=" ", format="%-8s") # quick and dirty ascii output...--no compression!
xvg.write('\n')
def parse(self, stride=None):
"""Read and cache the file as a numpy array.
Store every *stride* line of data; if ``None`` then the class default is used.
The array is returned with column-first indexing, i.e. for a data file with
columns X Y1 Y2 Y3 ... the array a will be a[0] = X, a[1] = Y1, ... .
"""
if stride is None:
stride = self.stride
self.corrupted_lineno = []
irow = 0 # count rows of data
# cannot use numpy.loadtxt() because xvg can have two types of 'comment' lines
with utilities.openany(self.real_filename) as xvg:
rows = []
ncol = None
for lineno,line in enumerate(xvg):
line = line.strip()
if len(line) == 0:
continue
if line.startswith("@ legend"):
if not "legend" in self.metadata: self.metadata["legend"] = []
self.metadata["legend"].append(line.split("legend ")[-1])
if line.startswith("@ s"):
name = line.split("legend ")[-1].replace('"','').strip()
self.names.append(name)
if line.startswith(('#', '@')) :
continue
if line.startswith('&'):
raise NotImplementedError('%s: Multi-data not supported, only simple NXY format.'
% self.real_filename)
# parse line as floats
try:
row = map(float, line.split())
except:
if self.permissive:
self.logger.warn("%s: SKIPPING unparsable line %d: %r",
self.real_filename, lineno+1, line)
self.corrupted_lineno.append(lineno+1)
continue
self.logger.error("%s: Cannot parse line %d: %r",
self.real_filename, lineno+1, line)
raise
# check for same number of columns as in previous step
if not ncol is None and len(row) != ncol:
if self.permissive:
self.logger.warn("%s: SKIPPING line %d with wrong number of columns: %r",
self.real_filename, lineno+1, line)
self.corrupted_lineno.append(lineno+1)
continue
errmsg = "%s: Wrong number of columns in line %d: %r" % (self.real_filename, lineno+1, line)
self.logger.error(errmsg)
raise IOError(errno.ENODATA, errmsg, self.real_filename)
# finally: a good line
if irow % stride == 0:
ncol = len(row)
rows.append(row)
irow += 1
try:
self.__array = numpy.array(rows).transpose() # cache result
except:
self.logger.error("%s: Failed reading XVG file, possibly data corrupted. "
"Check the last line of the file...", self.real_filename)
raise
finally:
del rows # try to clean up as well as possible as it can be massively big
def parse(self, stride=None):
"""Read and cache the file as a numpy array.
Store every *stride* line of data; if ``None`` then the class default is used.
The array is returned with column-first indexing, i.e. for a data file with
columns X Y1 Y2 Y3 ... the array a will be a[0] = X, a[1] = Y1, ... .
"""
if stride is None:
stride = self.stride
self.corrupted_lineno = []
irow = 0 # count rows of data
# cannot use numpy.loadtxt() because xvg can have two types of 'comment' lines
with utilities.openany(self.real_filename) as xvg:
rows = []
ncol = None
for lineno,line in enumerate(xvg):
line = line.strip()
if len(line) == 0:
continue
if "label" in line and "xaxis" in line:
self.xaxis = line.split('"')[-2]
if "label" in line and "yaxis" in line:
self.yaxis = line.split('"')[-2]
if line.startswith("@ legend"):
if not "legend" in self.metadata: self.metadata["legend"] = []
self.metadata["legend"].append(line.split("legend ")[-1])
if line.startswith("@ s") and "subtitle" not in line:
name = line.split("legend ")[-1].replace('"','').strip()
self.names.append(name)
if line.startswith(('#', '@')) :
continue
if line.startswith('&'):
raise NotImplementedError('{0!s}: Multi-data not supported, only simple NXY format.'.format(self.real_filename))
# parse line as floats
try:
row = map(float, line.split())
except:
if self.permissive:
self.logger.warn("%s: SKIPPING unparsable line %d: %r",
self.real_filename, lineno+1, line)
self.corrupted_lineno.append(lineno+1)
continue
self.logger.error("%s: Cannot parse line %d: %r",
self.real_filename, lineno+1, line)
raise
# check for same number of columns as in previous step
if ncol is not None and len(row) != ncol:
if self.permissive:
self.logger.warn("%s: SKIPPING line %d with wrong number of columns: %r",
self.real_filename, lineno+1, line)
self.corrupted_lineno.append(lineno+1)
continue
errmsg = "{0!s}: Wrong number of columns in line {1:d}: {2!r}".format(self.real_filename, lineno+1, line)
self.logger.error(errmsg)
raise IOError(errno.ENODATA, errmsg, self.real_filename)
# finally: a good line
if irow % stride == 0:
ncol = len(row)
rows.append(row)
irow += 1
try:
self.__array = numpy.array(rows).transpose() # cache result
except:
self.logger.error("%s: Failed reading XVG file, possibly data corrupted. "
"Check the last line of the file...", self.real_filename)
raise
finally:
del rows # try to clean up as well as possible as it can be massively big
