def parse(self, taggers=list()):
"""
Open the csv file and dump it in a tablib.Dataset object
"""
self.logger.info("Will parse input %(csv_path)s csv file" % {"csv_path": self.csv_path})
data = Dataset()
with open(self.csv_path, "rb") as csv_file:
google_contact = UnicodeReader(csv_file)
for row_num, row in enumerate(google_contact):
if row_num == 0:
data.headers = row
continue
gRow = GoogleContactRow(headers=data.headers, row=row)
gRow.standard_cleanup()
gRow.format_names()
tags = []
for tagger in taggers:
tags += getattr(gRow, tagger)()
tags = list(set(tags))
# Get the row index
index = format_index(gRow[data.headers.index("Name")])
# Empty index
# drop this row
if not index:
self.logger.info("Ignored row without index (%(row_num)d)" % {"row_num": row_num})
continue
# Duplicate?
if self.is_duplicate(index):
self.logger.info(
"Found duplicate row for %(name)s (num: %(row_num)d)" % {"name": index, "row_num": row_num}
)
# Drop this row
if self.drop:
self.logger.debug("Dropped duplicate row %(row_num)d" % {"row_num": row_num})
continue
# Merge this row
if self.merge:
row_dst = self.hash.index(index)
data[row_dst] = merge_lists(gRow, data[row_dst])
self.logger.debug(
"Merged duplicate row %(row_src)d with %(row_dst)d"
% {"row_src": row_num, "row_dst": row_dst}
)
continue
self.hash += (index,)
data.append(gRow, tags=tags)
self.logger.debug("row %d tags %s", row_num, tags)
self.data = data
self.logger.debug("File columns are:\n%s", "\n".join(self.data.headers))
def transpose(self): """Transpose a :class:`Dataset`, turning rows into columns and vice versa, returning a new ``Dataset`` instance. The first row of the original instance becomes the new header row.""" # Don't transpose if there is no data if not self: return _dset = Dataset() # The first element of the headers stays in the headers, # it is our "hinge" on which we rotate the data new_headers = [self.headers[0]] + self[self.headers[0]] _dset.headers = new_headers for column in self.headers: if column == self.headers[0]: # It's in the headers, so skip it continue # Adding the column name as now they're a regular column row_data = [column] + self[column] row_data = Row(row_data) _dset.append(row=row_data) return _dset
def as_tablib_dataset(report, parent_context):
render_context = _report(report, parent_context)
dataset = Dataset()
for element in render_context["elements"].values():
table = element["table"]
dataset.append_separator(element["title"])
for i, row in enumerate(table.as_values()):
dataset.append(row)
return dataset
def _prepare_table(string):
dataset = Dataset()
for i, line in enumerate(string.split('\n')[1:]):
if '====' in line or not line:
continue
row = line.split()
if i == 1:
dataset.headers = row
else:
dataset.append([numberfy(num) for num in row])
return dataset
def _prepare_cluters(string):
dataset = Dataset()
string = string.replace('PULSE HEIGHT',
'PULSE-HEIGHT').replace(' +/-', '_+/-')
for i, line in enumerate(string.split('\n')[3:]):
if '*****' in line or not line:
continue
line = line.split()
if i == 0:
dataset.headers = line
else:
dataset.append(
[numberfy(cell.replace('_', ' ')) for cell in line])
return dataset
def _prepare_table(string):
dataset = Dataset()
for i, line in enumerate(string.split('\n')[1:]):
if '*****' in line or not line:
continue
row = line.split()
if i == 1:
row[4] += ' ' + row[5]
dataset.headers = row[:5]
else:
dataset.append([numberfy(i) for i in row])
return dataset
def sort(self, col, reverse=False, include_tags=True):
"""Sort a :class:`Dataset` by a specific column, given string (for
header) or integer (for column index). The order can be reversed by
setting ``reverse`` to ``True``.
Returns a new :class:`Dataset` instance where columns have been
sorted.
"""
if isinstance(col, str) or isinstance(col, unicode):
if not self.headers:
raise HeadersNeeded
else:
if self.headers:
col = self.headers[col]
old_headers = self.headers[:]
if include_tags:
if len(self._tags_list) != self.height:
raise InvalidDimensions
else:
_dset = copy(self)
_dset.rpush_col(self._tags_list, header='tags')
tag_getter = itemgetter(self.width +1)
_dset._tags_list = []
_sorted = sorted(_dset.dict, key=itemgetter(col), reverse=reverse)
_dataset = Dataset(headers=self.headers)
for item in _sorted:
if self.headers:
tags = tag_getter(item).split(' ')
changed_row = Row([item[key] for key in old_headers], tags=tags)
else:
changed_row = item
_dataset.append(row=changed_row._row, tags=changed_row.tags, include_tags=True)
else:
_dset = copy(self)
_sorted = sorted(_dset.dict, key=itemgetter(col), reverse=reverse)
_dataset = Dataset(headers=self.headers)
for item in _sorted:
if self.headers:
row = [item[key] for key in self.headers]
else:
row = item
_dataset.append(row=row)
return _dataset
def _prepare_table(string):
result = []
for line in string.split('\n'):
if '*****' in line or not line:
continue
line = line.lstrip().strip('*').split('*')
row = []
for cell in line:
cell = cell.strip()
row.append(cell)
result.append(row)
dataset = Dataset()
dataset.headers = result[0]
for row in result[1:]:
dataset.append([numberfy(i) for i in row])
return dataset
def _prepare_clusters_str(self, data):
dataset = Dataset()
stringRep = data.replace('PULSE HEIGHT',
'PULSE-HEIGHT').replace(' +/-', '_+/-')
for i, line in enumerate(stringRep.split('\n')[3:]):
if '*****' in line or not line or 'GEANT' in line:
continue
if 'NO. PULSE-HEIGHT' not in line and '+/-' not in line:
continue
parts = line.split()
if i == 0:
dataset.headers = parts
else:
if '+/-' in line:
dataset.append(
[numberfy(cell.replace('_', ' ')) for cell in parts])
return dataset
def _prepare_table(string):
dataset = Dataset()
good = None
for i, line in enumerate(string.split('\n')[1:]):
if '====' in line or not line:
continue
row = line.split()
if i == 1:
dataset.headers = row
else:
if len(row) == len(dataset.headers):
good = line
dataset.append([numberfy(num) for num in row])
else:
print(good)
print(row)
return dataset
row_raw.append(number_of_decays + 1)
row_raw.append(momentum)
y1 = event.calorimeter.clusters.clusters[0].y.value
z1 = event.calorimeter.clusters.clusters[0].z.value
y2 = event.calorimeter.clusters.clusters[1].y.value
z2 = event.calorimeter.clusters.clusters[1].z.value
ph1 = event.calorimeter.clusters.clusters[0].pulse_height
ph2 = event.calorimeter.clusters.clusters[1].pulse_height
row_raw.append(y1)
row_raw.append(z1)
row_raw.append(ph1)
row_raw.append(y2)
row_raw.append(z2)
row_raw.append(ph2)
raw.append(row_raw)
number_of_decays += 1
with open(RAW_OUTPUT, 'wb') as f:
f.write(raw.export('xlsx'))
if (progress < 98):
print('Something went wrong. Please run the program again.')
else:
print('Execution completed.')
print(event_id, 'event(s) were simulated.')
print('There were', number_of_decays, 'interesting events out of',
event_id, 'events.')
dataset.headers = ('P', 'pulseheight', 'x', 'dx', 'y', 'dy', 'z', 'dz',
'ywidth', 'zwidth')
for event in events:
row = []
if len(event.clusters.clusters.clusters) is 1:
row.append(event.energy)
row.append(event.clusters.clusters.clusters[0].pulse_height)
row.append(event.clusters.clusters.clusters[0].x.value)
row.append(event.clusters.clusters.clusters[0].x.error)
row.append(event.clusters.clusters.clusters[0].y.value)
row.append(event.clusters.clusters.clusters[0].y.error)
row.append(event.clusters.clusters.clusters[0].z.value)
row.append(event.clusters.clusters.clusters[0].z.error)
row.append(event.clusters.clusters.clusters[0].ywidth)
row.append(event.clusters.clusters.clusters[0].zwidth)
dataset.append(row)
with open(EXEL_OUTPUT, 'wb') as f:
f.write(dataset.export('xls'))
elif particle is 'electron' or particle is 'muon':
events = parse(text)
dataset = Dataset()
dataset.headers = ('P', 'tandip', 'Kappa', 'd Kappa',
'Calorimeter Pulse Heights')
for event in events:
row = []
row.append(event.energy)
if len(event.tracks.tracks) is not 0:
if event.tracks.tracks[0].parameters.tandip is not None:
row.append(event.tracks.tracks[0].parameters.tandip)
else:
