h = []
# READ INPUT DATA FILE
# --------------------
if os.path.isdir(args.f):
print "using directory " + args.f
for f in os.listdir(args.f):
print "processing file " + f
if f.endswith(".log"):
print "ignoring file"
continue
fi = args.f.rstrip('/') + '/' + f
# READ INPUT DATA FILE
# --------------------
this_run_time, this_run_x, this_run_y, this_run_d, this_run_d_err, this_run_t, this_run_h = read_data_file(fi, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.nc:
this_run_x, this_run_y = correct_stage_positions(F_CALX, F_CALY, this_run_x, this_run_y)
# CORRECT FOR TEMPERATURE EXCURSIONS
# ----------------------------------
if args.nt:
this_run_d = correct_for_temperature(F_CORT, this_run_d, this_run_t)
TIME.append(np.asarray(this_run_time))
x.append(np.mean(this_run_x))
y.append(np.mean(this_run_y))
d.append(np.mean(this_run_d))
args.w = ([float(n) for n in args.w.split(',')])
run_data_x = []
run_data_y = []
run_data_d = []
run_data_d_err = []
for f in os.listdir(args.f):
print "processing file " + f
if f.endswith(".log"):
print "ignoring file"
continue
fi = args.f.rstrip('/') + '/' + f
# READ INPUT DATA FILE
# --------------------
this_time, x, y, d, d_err, t, h = read_data_file(fi, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.nc:
x, y = correct_stage_positions(F_CALX, F_CALY, x, y)
# CORRECT FOR TEMPERATURE EXCURSIONS
# ----------------------------------
if args.nt:
d = correct_for_temperature(F_CORT, d, t)
run_data_x.append(np.mean(x))
run_data_y.append(np.mean(y))
run_data_d.append(np.mean(d))
run_data_d_err.append(np.mean(d_err))
h = []
# READ INPUT DATA FILE
# --------------------
if os.path.isdir(args.f):
print "using directory " + args.f
for f in os.listdir(args.f):
print "processing file " + f
if f.endswith(".log"):
print "ignoring file"
continue
fi = args.f.rstrip('/') + '/' + f
# READ INPUT DATA FILE
# --------------------
this_run_time, this_run_x, this_run_y, this_run_d, this_run_d_err, this_run_t, this_run_h = read_data_file(
fi, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.nc:
this_run_x, this_run_y = correct_stage_positions(
F_CALX, F_CALY, this_run_x, this_run_y)
# CORRECT FOR TEMPERATURE EXCURSIONS
# ----------------------------------
if args.nt:
this_run_d = correct_for_temperature(F_CORT, this_run_d,
this_run_t)
TIME.append(np.asarray(this_run_time))
x.append(np.mean(this_run_x))
parser.add_argument(
'--tcal',
help="temperature at which to correct at (should be mid-range ish)",
action="store",
type=float,
default=24)
parser.add_argument('--p', help="make plots?", action="store_true")
args = parser.parse_args()
args.tr = ([float(T) for T in args.tr.split(',')])
print "processing file " + args.f
# READ INPUT DATA FILE
# --------------------
this_time, x, y, d, d_err, t, h = read_data_file(args.f, args.de, None)
c = np.polyfit(
[ti for ti in t if ti > args.tr[0] and ti < args.tr[1]],
[di
for di, ti in zip(d, t) if ti > args.tr[0] and ti < args.tr[1]], args.o)
# we correct for the position by finding how much by calibrating the measured distance to
# what it would be at a reference temperature of [t_cal]
d_cal = np.polyval(
c, args.tcal) # the calibration measurement at our reference temperature
offsets = np.polyval(
c, t
) - d_cal # the offsets that need to be applied for these measured temperatures to make them equivalent to being taken at the reference temperature
args.w = ([float(n) for n in args.w.split(',')])
run_data_x = []
run_data_y = []
run_data_d = []
run_data_d_err = []
for f in os.listdir(args.f):
print "processing file " + f
if f.endswith(".log"):
print "ignoring file"
continue
fi = args.f.rstrip('/') + '/' + f
# READ INPUT DATA FILE
# --------------------
this_time, x, y, d, d_err, t, h = read_data_file(fi, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.nc:
x, y = correct_stage_positions(F_CALX, F_CALY, x, y)
# CORRECT FOR TEMPERATURE EXCURSIONS
# ----------------------------------
if args.nt:
d = correct_for_temperature(F_CORT, d, t)
run_data_x.append(np.mean(x))
run_data_y.append(np.mean(y))
run_data_d.append(np.mean(d))
run_data_d_err.append(np.mean(d_err))
parser = argparse.ArgumentParser()
parser.add_argument('--fl', help="add file to list", action='append')
parser.add_argument('--de', help="maximum error in distance measurement", action="store", type=float, default=1.0)
parser.add_argument('--w', help="window, defaults to min/max of data (x1,x2,y1,y2)", action="store", type=str, default='25,210,285,285')
parser.add_argument('--ca', help="don't apply stage calibration files", action="store_false")
parser.add_argument('--cax', help="calibration file for x if stage calibration is to be applied", action="store", type=str, default='calibration_files/45855915_cal.dat')
parser.add_argument('--cay', help="calibration file for y if stage calibration is to be applied", action="store", type=str, default='calibration_files/45855916_cal.dat')
args = parser.parse_args()
args.w = ([float(n) for n in args.w.split(',')])
for f in args.fl:
# READ INPUT DATA FILE(S)
# -----------------------
x, y, d, de = read_data_file(f, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.ca:
x, y = correct_stage_positions(args.cax, args.cay, x, y)
c = np.polyfit(x, d, 1)
d_slope = np.polyval(c, x)
plt.plot(x, d-d_slope, label="y= " + f)
plt.legend()
plt.ylim([-50,50])
plt.show()
action="store",
type=str,
default='calibration_files/45855915_cal.dat')
parser.add_argument(
'--cay',
help="calibration file for y if stage calibration is to be applied",
action="store",
type=str,
default='calibration_files/45855916_cal.dat')
args = parser.parse_args()
args.w = ([float(n) for n in args.w.split(',')])
for f in args.fl:
# READ INPUT DATA FILE(S)
# -----------------------
x, y, d, de = read_data_file(f, args.de, args.w)
# CORRECT FOR NONLINEAR MOTION OF STAGES
# --------------------------------------
if args.ca:
x, y = correct_stage_positions(args.cax, args.cay, x, y)
c = np.polyfit(x, d, 1)
d_slope = np.polyval(c, x)
plt.plot(x, d - d_slope, label="y= " + f)
plt.legend()
plt.ylim([-50, 50])
plt.show()
parser = argparse.ArgumentParser()
parser.add_argument('--f', help="path to file", action="store", type=str)
parser.add_argument('--de', help="maximum error in distance measurement", action="store", type=float, default=1.0)
parser.add_argument('--o', help="order of fit", action="store", type=int, default=2)
parser.add_argument('--tr', help="CSV range of temperatures over which to fit", action="store", type=str, default='23,25')
parser.add_argument('--tcal', help="temperature at which to correct at (should be mid-range ish)", action="store", type=float, default=24)
parser.add_argument('--p', help="make plots?", action="store_true")
args = parser.parse_args()
args.tr = ([float(T) for T in args.tr.split(',')])
print "processing file " + args.f
# READ INPUT DATA FILE
# --------------------
this_time, x, y, d, d_err, t, h = read_data_file(args.f, args.de, None)
c = np.polyfit([ti for ti in t if ti>args.tr[0] and ti<args.tr[1]], [di for di, ti in zip(d, t) if ti>args.tr[0] and ti<args.tr[1]], args.o)
# we correct for the position by finding how much by calibrating the measured distance to
# what it would be at a reference temperature of [t_cal]
d_cal = np.polyval(c, args.tcal) # the calibration measurement at our reference temperature
offsets = np.polyval(c, t) - d_cal # the offsets that need to be applied for these measured temperatures to make them equivalent to being taken at the reference temperature
c2 = np.polyfit([ti for ti in t if ti>args.tr[0] and ti<args.tr[1]], [oi for oi, ti in zip(offsets, t) if ti>args.tr[0] and ti<args.tr[1]], args.o)
np.save("t_cor", c2)
if args.p:
plt.subplot(211)