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assert type(df) is pd.DataFrame
# Diagnose problems with the data formats that can be addressed in cleaning
# Get initial display settings
initial_max_cols = pd.get_option('display.max_columns')
initial_max_rows = pd.get_option('display.max_rows')
initial_width = pd.get_option('display.width')
# Reformat displays
pd.set_option('display.max_columns', display_max_cols)
pd.set_option('display.max_rows',None)
if display_width is not None:
pd.set_option('display.width',display_width)
# --------Values of data-----------
df_preview = _io.preview(df,preview_rows)
df_info = _io.get_info(df,verbose = True, max_cols = display_max_cols,
memory_usage = 'deep',null_counts = True)
dtypes = stats.dtypes_summary(df).apply(_io.format_row,args = [_utils.rows(df)],axis = 1)
potential_outliers = stats.df_outliers(df).dropna(axis = 1,how = 'all')
potential_outliers = potential_outliers if _utils.rows(potential_outliers) \
else None
# ----------Build lists------------
title_list = \
['Preview','Info',
'Data Types Summary','Potential Outliers']
info_list = \
[df_preview,df_info,
dtypes,potential_outliers]
error_list = [None,None,
None,'No potential outliers.']
# ----------Build output------------
output = ''
for title, value,error_text in zip(title_list,info_list,error_list):
if value is None:
value = ""{} skipped: {}"".format(title,error_text)
if str(value).endswith('\n'):
value = value[:-1]
output+='{}\n{}\n\n'.format(_io.title_line(title),value)
# ----------Send to file/print to console------------
# Potentially could change this to allow for output_safe to work with directories
print(output)
# Reset display settings
pd.set_option('display.max_columns', initial_max_cols)
pd.set_option('display.max_rows', initial_max_rows)
pd.set_option('display.width', initial_width)"
4180,"def cut_spectrum(sp, l0, lf):
""""""
Cuts spectrum given a wavelength interval, leaving origina intact
Args:
sp: Spectrum instance
l0: initial wavelength
lf: final wavelength
Returns:
Spectrum: cut spectrum
""""""
if l0 >= lf:
raise ValueError(""l0 must be lower than lf"")
idx0 = np.argmin(np.abs(sp.x - l0))
idx1 = np.argmin(np.abs(sp.x - lf))
out = copy.deepcopy(sp)
out.x = out.x[idx0:idx1]
out.y = out.y[idx0:idx1]
return out"
4181,"def remove_nongenerating_nonterminals(grammar, inplace=False):
# type: (Grammar, bool) -> Grammar
""""""
Remove nongenerating symbols from the grammar.
Nongenerating symbols are symbols, that don't generate sequence of terminals.
For example never ending recursion.
:param grammar: Grammar where to remove nongenerating symbols.
:param inplace: True if transformation should be performed in place. False by default.
:return: Grammar without nongenerating symbols.
""""""
# copy if required
if inplace is False:
grammar = copy(grammar)
# create working sets
generates = grammar.terminals.copy()
generates.add(EPSILON)
rules = grammar.rules.copy()
# iterate until the set doesn't change
while True:
# create set for the next iteration
additional = generates.copy()
# iterate over unprocessed rules
for rule in rules.copy():
rightPart = rule.right