def naget():
natype = request.args.get('natype')
message = {}
try:
start_val, start_unit = si_format(float(NA[natype].linfreq(
nabench[natype])[1]['START']),
precision=1).split(" ")
stop_val, stop_unit = si_format(float(NA[natype].linfreq(
nabench[natype])[1]['STOP']),
precision=1).split(" ")
stop_conversion = si_parse("1%s" % stop_unit) / si_parse(
"1%s" % start_unit) # equalizing both unit-range:
message['start-frequency'] = "%s %sHz" % (start_val, start_unit
) # start-frequency
message['stop-frequency'] = "%s %sHz" % (
float(stop_val) * stop_conversion, start_unit) # stop-frequency
message['step-points'] = int(NA[natype].sweep(
nabench[natype])[1]['POINTS']) - 1 # step-points in waveform
message['power'] = "%.1f dBm" % float(NA[natype].power(
nabench[natype])[1]['LEVEL']) # power (fixed unit)
message['ifb'] = si_format(
float(NA[natype].ifbw(nabench[natype])[1]['BANDWIDTH']),
precision=0) + "Hz" # ifb (adjusted by si_prefix)
message['s21'] = int('S21' in NA[natype].getrace(nabench[natype]))
except:
# raise
message = dict(status='%s is not connected' % natype)
return jsonify(message=message)
def nasetfreqrange():
natype = request.args.get('natype')
freqrange = waveform(request.args.get('freqrange'))
frequnit = request.args.get('frequnit').replace("Hz","")
NA[natype].sweep(nabench[natype], action=['Set', 'ON', freqrange.count])
fstart, fstop = si_parse(str(freqrange.data[0])+frequnit), si_parse(str(freqrange.data[-1])+frequnit)
NA[natype].sweep(nabench[natype], action=['Set', 'ON', freqrange.count])
NA[natype].linfreq(nabench[natype], action=['Set', fstart, fstop])
message = 'frequency: %s to %s' %(fstart, fstop)
return jsonify(message=message)
def resistance(self, r):
if type(r) is str:
self._resistance = si_parse(r)
else:
if r < 0:
raise ValueError('Invalid value provided for resistance')
self._resistance = r
def unit_converter(unit_added_string: str) -> float:
"""
convert unit formatted strings to floating numbers without any units
Arguments:
:param unit_added_string: the unit added number we want to convert to be unit free
Returns::
:return unit_in_float: the same number but in float without the units
Raises::
:raise TypeError: if trying to parse an unknown unit type
"""
custom_unit_ratio = {
"Ki": 1024,
"Mi": 1024 * 1024,
"Gi": 1024 * 1024 * 1024
}
try:
unit_in_float = float(si_parse(unit_added_string))
except AttributeError:
if unit_added_string[-2:] in custom_unit_ratio:
unit_in_float = float(unit_added_string[:-2]) * custom_unit_ratio[unit_added_string[-2:]]
else:
raise TypeError
return unit_in_float
def nasetifb():
natype = request.args.get('natype')
ifb = request.args.get('ifb')
ifbunit = request.args.get('ifbunit').replace("Hz","")
stat = NA[natype].ifbw(nabench[natype], action=['Set', si_parse(ifb + ifbunit)])
message = 'ifb: %s <%s>' %(stat[1], stat[0])
return jsonify(message=message)
async def change_frequency(self, frequency, params):
try:
print("FREQ", frequency)
frequency = si_parse(_.replace(frequency, "Hz", ""))
await self.put_frequency({"frequency": frequency}, params)
await self.update_board_info()
except Exception as e:
print("Error setting frequency")
print(e)
async def change_voltage(self, voltage, params):
try:
print("CHANGING :) VOLTAGE!!!")
# Convert payload from si_unit string to number
print("CALLING PSI PARSE:", voltage)
voltage = si_parse(_.replace(voltage, "V", ""))
print("ITS NOW: ", voltage)
await self.put_voltage({"voltage": voltage}, {})
await self.update_board_info()
except Exception as e:
print("Error setting voltage")
print(e)
def get_alloc_sizes(objdata):
sizes = []
with open(objdata, 'r') as f:
for line in f:
line = line.strip()
if line.startswith('<'):
continue
fields = re.split(' *\( *| *\) *| +', line)
sz_w_sfx = fields[2] + fields[3]
size = si_parse(sz_w_sfx[0:-1])
sizes.append(size)
return sizes
def on_edited_dataframe_sync(cell_renderer, itr, new_value, column,
df_py_dtypes, list_store, df_data):
"""
Handle the `'edited'` signal from a `Gtk.CellRenderer` to:
* Update the corresponding entry in the list store.
* Update the corresponding entry in the provided data frame instance.
The callback can be connected to the cell renderer as follows:
cell_renderer.connect('edited', on_edited_dataframe_sync, column,
list_store, df_py_dtypes, df_data)
where `column` is the `Gtk.TreeViewColumn` the cell renderer belongs to,
and `df_py_dtypes` and `list_store` are the return values from calling
`get_list_store` on the `df_data` data frame.
Args:
cell_renderer (Gtk.CellRenderer)
iter (str) : Gtk TreeView iterator
new_value (str) : New value resulting from edit operation.
column (Gtk.TreeViewColumn) : Column containing edited cell.
df_py_dtypes (pandas.DataFrame) : Data frame containing type
information for columns in tree view (and `list_store`).
list_store (Gtk.ListStore) : Model containing data bound to tree view.
df_data (pandas.DataFrame) : Data frame containing data in `list_store`.
Returns:
None
"""
# Extract name of column (name of TreeView column must match data frame
# column name).
column_name = column.get_name()
# Look up the list store column index and data type for column.
i, dtype = df_py_dtypes.ix[column_name]
# Update the list store with the new value.
if dtype == float:
value = si_parse(new_value)
elif dtype == bool:
value = not list_store[itr][i]
if value == list_store[itr][i]:
# Value has not changed.
return False
list_store[itr][i] = value
# Update the data frame with the new value.
df_data[column_name].values[int(itr)] = value
return True
def on_edited_dataframe_sync(cell_renderer, iter, new_value, column,
df_py_dtypes, list_store, df_data):
'''
Handle the `'edited'` signal from a `gtk.CellRenderer` to:
* Update the corresponding entry in the list store.
* Update the corresponding entry in the provided data frame instance.
The callback can be connected to the cell renderer as follows:
cell_renderer.connect('edited', on_edited_dataframe_sync, column,
list_store, df_py_dtypes, df_data)
where `column` is the `gtk.TreeViewColumn` the cell renderer belongs to,
and `df_py_dtypes` and `list_store` are the return values from calling
`get_list_store` on the `df_data` data frame.
Args:
cell_renderer (gtk.CellRenderer)
iter (str) : Gtk TreeView iterator
new_value (str) : New value resulting from edit operation.
column (gtk.TreeViewColumn) : Column containing edited cell.
df_py_dtypes (pandas.DataFrame) : Data frame containing type
information for columns in tree view (and `list_store`).
list_store (gtk.ListStore) : Model containing data bound to tree view.
df_data (pandas.DataFrame) : Data frame containing data in `list_store`.
Returns:
None
'''
# Extract name of column (name of TreeView column must match data frame
# column name).
column_name = column.get_name()
# Look up the list store column index and data type for column.
i, dtype = df_py_dtypes.ix[column_name]
# Update the list store with the new value.
if dtype == float:
value = si_parse(new_value)
elif dtype == bool:
value = not list_store[iter][i]
if value == list_store[iter][i]:
# Value has not changed.
return False
list_store[iter][i] = value
# Update the data frame with the new value.
df_data[column_name].values[int(iter)] = value
return True
def process_query(self, query):
# Try to infer and convert numerical shorthands to machine understandable format, e.g. 100M = 100*1,000,000
parsed_tokens = []
for token in word_tokenize(query):
try:
parsed_tokens.append(str(int(si_parse(token))))
except Exception as e:
parsed_tokens.append(token)
# Convert to lowercase
query_lower = ' '.join(parsed_tokens).lower()
return query_lower
def process_query(self, query):
# Try to infer and convert numerical shorthands to machine understandable format, e.g. 100M = 100*1,000,000
parsed_tokens = []
for token in word_tokenize(query):
try:
parsed_tokens.append(str(int(si_parse(token))))
except Exception as e:
parsed_tokens.append(token)
# Clean sentence of non-alphanumerical characters
query_processed = re.sub(r'[^A-Za-z0-9]+', ' ',
' '.join(parsed_tokens))
# Convert to lowercase
query_lower = query_processed.lower()
return query_lower
