def readfile(self, filename):
"""
Reads in an ascii columned file
"""
self.titles = []
self.bigarray = None
self.parameters = parameters.parameters(filename=filename)
self.ncols = 0
self.nrows = 0
i = 0
# Check if this is a hdf file: magic number
with open(filename, "rb") as f:
magic = f.read(4)
# 1 2 3 4 bytes
if magic == b'\x89HDF':
print("Reading your columnfile in hdf format")
colfile_from_hdf(filename, obj=self)
return
with open(filename, "r") as f:
raw = f.readlines()
header = True
while header and i < len(raw):
if len(raw[i].lstrip()) == 0:
# skip blank lines
i += 1
continue
if raw[i][0] == "#":
# title line
if raw[i].find("=") > -1:
# key = value line
name, value = clean(raw[i][1:].split("="))
self.parameters.addpar(parameters.par(name, value))
else:
self.titles = raw[i][1:].split()
i += 1
else:
header = False
try:
row0 = [float(v) for v in raw[i].split()]
lastrow = [float(v) for v in raw[-1].split()]
if len(row0) == len(lastrow):
nrows = len(raw) - i
last = None
else:
nrows = len(raw) - i - 1 # skip the last row
last = -1
self.bigarray = np.zeros((len(row0), nrows), np.float)
for i, line in enumerate(raw[i:last]):
self.bigarray[:, i] = [float(v) for v in line.split()]
except:
raise Exception("Problem interpreting your colfile")
(self.ncols, self.nrows) = self.bigarray.shape
self.parameters.dumbtypecheck()
self.set_attributes()
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
import numpy
import logging
import math
import sys, os
from ImageD11 import transform, unitcell, columnfile
from ImageD11.parameters import par, parameters
PARAMETERS = [
par("omegasign", 1.0,
helpstring="Sign of the rotation about z " + \
"(normally +1 for right handed)",
vary=False,
can_vary=False),
par('z_center', 1024.0,
helpstring="Beam centre in vertical, pixels",
vary=True,
can_vary=True,
stepsize=1.0),
par('y_center', 1024.0,
helpstring="Beam centre in horizontal, pixels",
vary=True,
can_vary=True,
stepsize=1.0),
par('distance', 50000.0,
helpstring="sample detector distance, same units as pixel size",
vary=True,
def readfile(self, filename):
"""
Reads in an ascii columned file
"""
self.titles = []
self.bigarray = None
self.parameters = parameters.parameters(filename=filename)
self.ncols = 0
self.nrows = 0
i = 0
try:
raw = open(filename, "r").readlines()
except:
raise Exception("Cannot open %s for reading" % (filename))
header = True
while header and i < len(raw):
if len(raw[i].lstrip()) == 0:
# skip blank lines
i += 1
continue
if raw[i][0] == "#":
# title line
if raw[i].find("=") > -1:
# key = value line
name, value = clean(raw[i][1:].split("="))
self.parameters.addpar(parameters.par(name, value))
else:
self.titles = raw[i][1:].split()
i += 1
else:
header = False
try:
cc = [numpy.fromstring(v, sep=' ') for v in raw[i:]]
self.bigarray = numpy.array(cc).transpose()
except:
raise Exception("Non numeric data on all lines\n")
(self.ncols, self.nrows) = self.bigarray.shape
# data = []
# try:
# fileobj = open(filename,"r").readlines()
# except:
# raise Exception("Cannot open %s for reading"%(filename))
# for line in fileobj:
# i += 1
# if len(line.lstrip())==0:
# # skip blank lines
# continue
# if line[0] == "#":
# # title line
# if line.find("=") > -1:
# # key = value line
# name, value = clean(line[1:].split("="))
# self.parameters.addpar(
# parameters.par( name, value ) )
# else:
# self.titles = clean(line[1:].split())
# self.ncols = len(self.titles)
# continue
# # Assume a data line
# try:
# vals = [ float(v) for v in line.split() ]
# except:
# raise Exception("Non numeric data on line\n"+line)
# if len(vals) != self.ncols:
# raise Exception("Badly formatted column file\n"\
# "expecting %d columns, got %d\n"\
# " line %d in file %s"%
# (self.ncols, len(vals),
# i, self.filename))
# self.nrows += 1
# data.append(vals)
# self.bigarray = numpy.transpose(numpy.array(data))
# if self.nrows > 0:
# assert self.bigarray.shape == (self.ncols, self.nrows)
self.set_attributes()