def LoadMAGIKPSD(filename, path="", friendly_name="", collapse_y=True, auto_PolState=False, PolState='', flip=True, transpose=True, **kw):
"""
loads a data file into a MetaArray and returns that.
Checks to see if data being loaded is 2D; if not, quits
Need to rebin and regrid if the detector is moving...
"""
lookup = {"DOWN_DOWN":"_down_down", "UP_DOWN":"_up_down", "DOWN_UP":"_down_up", "UP_UP":"_up_up", "entry": ""}
if '.nxz' in filename:
file_obj = hzf.File(filename)
else:
# nexus
file_obj = h5py.File(os.path.join(path, filename))
#if not (len(file_obj.detector.counts.shape) == 2):
# not a 2D object!
# return
for entryname, entry in file_obj.items():
active_slice = slice(None, DETECTOR_ACTIVE[0], DETECTOR_ACTIVE[1])
counts_value = entry['DAS_logs']['areaDetector']['counts'].value[:, 1:DETECTOR_ACTIVE[0]+1, :DETECTOR_ACTIVE[1]]
dims = counts_value.shape
print dims
ndims = len(dims)
if auto_PolState:
PolState = lookup.get(entryname, "")
# force PolState to a regularized version:
if not PolState in lookup.values():
PolState = ''
#datalen = file_obj.detector.counts.shape[0]
if ndims == 2:
if DEBUG: print "2d"
ypixels = dims[0]
xpixels = dims[1]
elif ndims >= 3:
if DEBUG: print "3d"
frames = dims[0]
xpixels = dims[1]
ypixels = dims[2]
creation_story = "LoadMAGIKPSD('{fn}', path='{p}')".format(fn=filename, p=path, aPS=auto_PolState, PS=PolState)
# doesn't really matter; changing so that each keyword (whether it took the default value
# provided or not) will be defined
# if not PolState == '':
# creation_story += ", PolState='{0}'".format(PolState)
# creation_story += ")"
if ndims == 2: # one of the dimensions has been collapsed.
info = []
info.append({"name": "xpixel", "units": "pixels", "values": arange(xpixels) }) # reverse order
info.append({"name": "theta", "units": "degrees", "values": entry['DAS_logs']['sampleAngle']['softPosition'].value })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": dateutil.parser.parse(file_obj.attrs.get('file_time')), "friendly_name": friendly_name,
"CreationStory":creation_story, "path":path, "det_angle":entry['DAS_logs']['detectorAngle']['softPosition'].value}]
)
data_array = zeros((xpixels, ypixels, 4))
mon = entry['DAS_logs']['counter']['liveMonitor'].value
count_time = entry['DAS_logs']['counter']['liveTime'].value
if ndims == 2:
mon.shape = (1,) + mon.shape # broadcast the monitor over the other dimension
count_time.shape = (1,) + count_time.shape
counts = counts_value
if transpose == True: counts = counts.swapaxes(0,1)
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
#data_array[..., 0] = file_obj.detector.counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
data = MetaArray(data_array, dtype='float', info=info)
data.friendly_name = friendly_name # goes away on dumps/loads... just for initial object.
elif ndims == 3: # then it's an unsummed collection of detector shots. Should be one sample and detector angle per frame
if collapse_y == True:
info = []
info.append({"name": "xpixel", "units": "pixels", "values": arange(xpixels) }) # reverse order
info.append({"name": "theta", "units": "degrees", "values": entry['DAS_logs']['sampleAngle']['softPosition'].value })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": dateutil.parser.parse(file_obj.attrs.get('file_time')), "friendly_name": friendly_name,
"CreationStory":creation_story, "path":path, "det_angle":entry['DAS_logs']['detectorAngle']['softPosition'].value}]
)
data_array = zeros((xpixels, frames, 4))
mon = entry['DAS_logs']['counter']['liveMonitor'].value
count_time = entry['DAS_logs']['counter']['liveTime'].value
if ndims == 3:
mon.shape = (1,) + mon.shape # broadcast the monitor over the other dimension
count_time.shape = (1,) + count_time.shape
counts = numpy.sum(counts_value, axis=2)
if transpose == True: counts = counts.swapaxes(0,1)
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
#data_array[..., 0] = file_obj.detector.counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
data = MetaArray(data_array, dtype='float', info=info)
data.friendly_name = friendly_name # goes away on dumps/loads... just for initial object.
else: # make separate frames
infos = []
data = []
samp_angle = entry['DAS_logs']['sampleAngle']['softPosition'].value
if samp_angle.shape[0] == 1:
samp_angle = numpy.ones((frames,)) * samp_angle
det_angle = entry['DAS_logs']['detectorAngle']['softPosition'].value
if det_angle.shape[0] == 1:
det_angle = numpy.ones((frames,)) * det_angle
for i in range(frames):
samp_angle = entry['DAS_logs']['sampleAngle']['softPosition'].value[i]
det_angle = entry['DAS_logs']['detectorAngle']['softPosition'].value[i]
info = []
info.append({"name": "xpixel", "units": "pixels", "values": range(xpixels) })
info.append({"name": "ypixel", "units": "pixels", "values": range(ypixels) })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": entry['start_time'].value, "friendly_name": friendly_name,
"CreationStory":creation_story, "path":path, "samp_angle": samp_angle, "det_angle": det_angle}]
)
data_array = zeros((xpixels, ypixels, 4))
mon = entry['DAS_logs']['counter']['liveMonitor'].value[i]
count_time = entry['DAS_logs']['counter']['liveTime'].value[i]
counts = counts_value[i]
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
subdata = MetaArray(data_array, dtype='float', info=info)
subdata.friendly_name = friendly_name + ("_%d" % i) # goes away on dumps/loads... just for initial object.
data.append(subdata)
return data
def loadMAGIKPSD_helper(file_obj, name, path, collapse=True, collapse_axis='y', auto_PolState=False, PolState='', flip=True, transpose=True):
lookup = {"DOWN_DOWN":"_down_down", "UP_DOWN":"_up_down", "DOWN_UP":"_down_up", "UP_UP":"_up_up", "entry": ""}
#nx_entries = LoadMAGIKPSD.load_entries(name, fid, entries=entries)
#fid.close()
#if not (len(file_obj.detector.counts.shape) == 2):
# not a 2D object!
# return
for entryname, entry in file_obj.items():
active_slice = slice(None, DETECTOR_ACTIVE[0], DETECTOR_ACTIVE[1])
counts_value = entry['DAS_logs/areaDetector/counts'].value[:, 1:DETECTOR_ACTIVE[0]+1, :DETECTOR_ACTIVE[1]]
dims = counts_value.shape
ndims = len(dims)
if auto_PolState:
PolState = lookup.get(entryname, "")
# force PolState to a regularized version:
if not PolState in lookup.values():
PolState = ''
#datalen = file_obj.detector.counts.shape[0]
if ndims == 2:
if DEBUG: print "2d"
ypixels = dims[0]
xpixels = dims[1]
elif ndims >= 3:
if DEBUG: print "3d"
frames = dims[0]
xpixels = dims[1]
ypixels = dims[2]
# doesn't really matter; changing so that each keyword (whether it took the default value
# provided or not) will be defined
# if not PolState == '':
# creation_story += ", PolState='{0}'".format(PolState)
# creation_story += ")"
if ndims == 2: # one of the dimensions has been collapsed.
info = []
info.append({"name": "xpixel", "units": "pixels", "values": arange(xpixels) }) # reverse order
samp_angle = entry['DAS_logs/sampleAngle/softPosition'].value
det_angle = entry['DAS_logs/detectorAngle/softPosition'].value
if samp_angle.size > 1:
yaxis = entry['DAS_logs/sampleAngle/softPosition']
yaxisname = "theta"
elif det_angle.size > 1:
yaxis = entry['DAS_logs/detectorAngle/softPosition']
yaxisname = "det_angle"
else:
# need to find the one that's moving...
yaxis = entry['data/x']
yaxisname = yaxis.path
yaxisunits = yaxis.attrs['units']
yaxisvalues = yaxis.value
info.append({"name": yaxisname, "units": yaxisunits, "values": yaxisvalues})
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": entry['start_time'].value[0], "friendly_name": entry['DAS_logs/sample/name'].value[0],
"entry": entryname, "path":path, "det_angle":entry['DAS_logs/detectorAngle/softPosition'].value,
"theta": entry['DAS_logs/sampleAngle/softPosition'].value}]
)
data_array = zeros((xpixels, ypixels, 4))
mon = entry['DAS_logs']['counter']['liveMonitor'].value
count_time = entry['DAS_logs']['counter']['liveTime'].value
if ndims == 2:
mon.shape = (1,) + mon.shape # broadcast the monitor over the other dimension
count_time.shape = (1,) + count_time.shape
counts = counts_value
if transpose == True: counts = counts.swapaxes(0,1)
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
#data_array[..., 0] = file_obj.detector.counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
data = MetaArray(data_array, dtype='float', info=info)
data.friendly_name = name # goes away on dumps/loads... just for initial object.
ouput = [data]
elif ndims == 3: # then it's an unsummed collection of detector shots. Should be one sample and detector angle per frame
if collapse == True:
info = []
xaxis = "xpixel" if collapse_axis == 'y' else "ypixel"
xdim = xpixels if collapse_axis == 'y' else ypixels
xaxisvalues = arange(xdim)
info.append({"name": xaxis, "units": "pixels", "values": xaxisvalues }) # reverse order
samp_angle = entry['DAS_logs/sampleAngle/softPosition'].value
det_angle = entry['DAS_logs/detectorAngle/softPosition'].value
if samp_angle.size > 1:
yaxis = entry['DAS_logs/sampleAngle/softPosition']
yaxisname = "theta"
elif det_angle.size > 1:
yaxis = entry['DAS_logs/detectorAngle/softPosition']
yaxisname = "det_angle"
else:
# need to find the one that's moving...
yaxis = entry['data/x']
yaxisname = yaxis.path
yaxisunits = yaxis.attrs['units']
yaxisvalues = yaxis.value
info.append({"name": yaxisname, "units": yaxisunits, "values": yaxisvalues})
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "start_datetime": entry['start_time'].value[0], "path":path,
"det_angle": det_angle.tolist(),
"theta": samp_angle.tolist(),
"friendly_name": entry['DAS_logs/sample/name'].value[0], "entry": entryname}]
)
data_array = zeros((xdim, frames, 4))
mon = entry['DAS_logs']['counter']['liveMonitor'].value
count_time = entry['DAS_logs']['counter']['liveTime'].value
if ndims == 3:
mon.shape = (1,) + mon.shape # broadcast the monitor over the other dimension
count_time.shape = (1,) + count_time.shape
axis_to_sum = 2 if collapse_axis == 'y' else 1
counts = numpy.sum(counts_value, axis=axis_to_sum)
if transpose == True: counts = counts.swapaxes(0,1)
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
#data_array[..., 0] = file_obj.detector.counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
data = MetaArray(data_array, dtype='float', info=info)
data.friendly_name = name # goes away on dumps/loads... just for initial object.
output = [data]
else: # make separate frames
infos = []
data = []
samp_angle = entry['DAS_logs/sampleAngle/softPosition'].value.astype('float')
if samp_angle.shape[0] == 1:
samp_angle = numpy.ones((frames,)) * samp_angle
det_angle = entry['DAS_logs/detectorAngle/softPosition'].value.astype('float')
if det_angle.shape[0] == 1:
det_angle = numpy.ones((frames,)) * det_angle
count_time = entry['DAS_logs/counter/liveTime'].value
if count_time.shape[0] == 1:
count_time = numpy.ones((frames,)) * count_time
mon = entry['DAS_logs/counter/liveMonitor'].value
if mon.shape[0] == 1:
mon = numpy.ones((frames,)) * mon
for i in range(frames):
info = []
info.append({"name": "xpixel", "units": "pixels", "values": range(xpixels) })
info.append({"name": "ypixel", "units": "pixels", "values": range(ypixels) })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "start_datetime": entry['start_time'].value[0], "friendly_name": entry['DAS_logs/sample/name'].value[0],
"entry": entryname, "path":path, "samp_angle": samp_angle[i], "det_angle": det_angle[i]}]
)
data_array = zeros((xpixels, ypixels, 4))
counts = counts_value[i]
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
data_array[..., 1] = 1
data_array[..., 2] = mon[i]
data_array[..., 3] = count_time[i]
# data_array[:,:,4]... I wish!!! Have to do by hand.
subdata = MetaArray(data_array, dtype='float', info=info)
subdata.friendly_name = name + ("_%d" % i) # goes away on dumps/loads... just for initial object.
data.append(subdata)
output = data
return output
def LoadICPData(filename, path="", friendly_name="", auto_PolState=False, PolState='', flip=True, transpose=True, **kw):
"""
loads a data file into a MetaArray and returns that.
Checks to see if data being loaded is 2D; if not, quits
Need to rebin and regrid if the detector is moving...
"""
lookup = {"a":"_down_down", "b":"_up_down", "c":"_down_up", "d":"_up_up", "g": ""}
file_obj = load(os.path.join(path, filename), format='NCNR NG-1')
dims = file_obj.detector.counts.shape
ndims = len(dims)
#if not (len(file_obj.detector.counts.shape) == 2):
# not a 2D object!
# return
if auto_PolState:
key = friendly_name[-2:-1] # na1, ca1 etc. are --, nc1, cc1 are -+...
PolState = lookup.get(key, "")
# force PolState to a regularized version:
if not PolState in lookup.values():
PolState = ''
#datalen = file_obj.detector.counts.shape[0]
if ndims == 2:
if DEBUG: print "2d"
ypixels = file_obj.detector.counts.shape[0]
xpixels = file_obj.detector.counts.shape[1]
elif ndims >= 3:
if DEBUG: print "3d"
frames = file_obj.detector.counts.shape[0]
ypixels = file_obj.detector.counts.shape[1]
xpixels = file_obj.detector.counts.shape[2]
creation_story = "LoadICPData('{fn}', path='{p}', auto_PolState={aPS}, PolState='{PS}')".format(fn=filename, p=path, aPS=auto_PolState, PS=PolState)
# doesn't really matter; changing so that each keyword (whether it took the default value
# provided or not) will be defined
# if not PolState == '':
# creation_story += ", PolState='{0}'".format(PolState)
# creation_story += ")"
if ndims == 2: # one of the dimensions has been collapsed.
info = []
info.append({"name": "xpixel", "units": "pixels", "values": arange(xpixels) }) # reverse order
info.append({"name": "theta", "units": "degrees", "values": file_obj.sample.angle_x })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": file_obj.date, "friendly_name": friendly_name,
"CreationStory":creation_story, "path":path, "det_angle":file_obj.detector.angle_x}]
)
data_array = zeros((xpixels, ypixels, 4))
mon = file_obj.monitor.counts
count_time = file_obj.monitor.count_time
if ndims == 2:
mon.shape = (1,) + mon.shape # broadcast the monitor over the other dimension
count_time.shape = (1,) + count_time.shape
counts = file_obj.detector.counts
if transpose == True: counts = counts.swapaxes(0,1)
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
#data_array[..., 0] = file_obj.detector.counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
data = MetaArray(data_array, dtype='float', info=info)
data.friendly_name = friendly_name # goes away on dumps/loads... just for initial object.
elif ndims == 3: # then it's an unsummed collection of detector shots. Should be one sample and detector angle per frame
infos = []
data = []
for i in range(frames):
samp_angle = file_obj.sample.angle_x[i]
det_angle = file_obj.detector.angle_x[i]
info = []
info.append({"name": "xpixel", "units": "pixels", "values": range(xpixels) })
info.append({"name": "ypixel", "units": "pixels", "values": range(ypixels) })
info.extend([
{"name": "Measurements", "cols": [
{"name": "counts"},
{"name": "pixels"},
{"name": "monitor"},
{"name": "count_time"}]},
{"PolState": PolState, "filename": filename, "start_datetime": file_obj.date, "friendly_name": friendly_name,
"CreationStory":creation_story, "path":path, "samp_angle": samp_angle, "det_angle": det_angle}]
)
data_array = zeros((xpixels, ypixels, 4))
mon = file_obj.monitor.counts[i]
count_time = file_obj.monitor.count_time[i]
counts = file_obj.detector.counts[i]
if flip == True: counts = flipud(counts)
data_array[..., 0] = counts
data_array[..., 1] = 1
data_array[..., 2] = mon
data_array[..., 3] = count_time
# data_array[:,:,4]... I wish!!! Have to do by hand.
subdata = MetaArray(data_array, dtype='float', info=info)
subdata.friendly_name = friendly_name + ("_%d" % i) # goes away on dumps/loads... just for initial object.
data.append(subdata)
return data
