def norm_zero_one(array, dim=None):
"""
normalizes a numpy array from 0 to 1 based in its extent
Args:
array (ndarray):
dim (int):
Returns:
ndarray:
CommandLine:
python -m utool.util_alg --test-norm_zero_one
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_alg import * # NOQA
>>> array = np.array([ 22, 1, 3, 2, 10, 42, ])
>>> dim = None
>>> array_norm = norm_zero_one(array, dim)
>>> result = np.array_str(array_norm, precision=3)
>>> print(result)
[ 0.512 0. 0.049 0.024 0.22 1. ]
"""
if not util_type.is_float(array):
array = array.astype(np.float32)
array_max = array.max(dim)
array_min = array.min(dim)
array_exnt = np.subtract(array_max, array_min)
array_norm = np.divide(np.subtract(array, array_min), array_exnt)
return array_norm
def num_fmt(num, max_digits=None):
r"""
Weird function. Not very well written. Very special case-y
Args:
num (int or float):
max_digits (int):
Returns:
str:
CommandLine:
python -m utool.util_num --test-num_fmt
Example:
>>> # DISABLE_DOCTEST
>>> from utool.util_num import * # NOQA
>>> # build test data
>>> num_list = [0, 0.0, 1.2, 1003232, 41431232., .0000000343, -.443243]
>>> max_digits = None
>>> # execute function
>>> result = [num_fmt(num, max_digits) for num in num_list]
>>> # verify results
>>> print(result)
['0', '0.0', '1.2', '1,003,232', '41431232.0', '0.0', '-0.443']
"""
if num is None:
return 'None'
def num_in_mag(num, mag):
return mag > num and num > (-1 * mag)
if max_digits is None:
# TODO: generalize
if num_in_mag(num, 1):
if num_in_mag(num, .1):
max_digits = 4
else:
max_digits = 3
else:
max_digits = 1
if util_type.is_float(num):
num_str = ('%.' + str(max_digits) + 'f') % num
# Handle trailing and leading zeros
num_str = num_str.rstrip('0').lstrip('0')
if num_str.startswith('.'):
num_str = '0' + num_str
if num_str.endswith('.'):
num_str = num_str + '0'
return num_str
elif util_type.is_int(num):
return int_comma_str(num)
else:
return '%r'
def num_fmt(num, max_digits=None):
r"""
Weird function. Not very well written. Very special case-y
Args:
num (int or float):
max_digits (int):
Returns:
str:
CommandLine:
python -m utool.util_num --test-num_fmt
Example:
>>> # DISABLE_DOCTEST
>>> from utool.util_num import * # NOQA
>>> # build test data
>>> num_list = [0, 0.0, 1.2, 1003232, 41431232., .0000000343, -.443243]
>>> max_digits = None
>>> # execute function
>>> result = [num_fmt(num, max_digits) for num in num_list]
>>> # verify results
>>> print(result)
['0', '0.0', '1.2', '1,003,232', '41431232.0', '0.0', '-0.443']
"""
if num is None:
return "None"
def num_in_mag(num, mag):
return mag > num and num > (-1 * mag)
if max_digits is None:
# TODO: generalize
if num_in_mag(num, 1):
if num_in_mag(num, 0.1):
max_digits = 4
else:
max_digits = 3
else:
max_digits = 1
if util_type.is_float(num):
num_str = ("%." + str(max_digits) + "f") % num
# Handle trailing and leading zeros
num_str = num_str.rstrip("0").lstrip("0")
if num_str.startswith("."):
num_str = "0" + num_str
if num_str.endswith("."):
num_str = num_str + "0"
return num_str
elif util_type.is_int(num):
return int_comma_str(num)
else:
return "%r"
def make_csv_table(column_list=[],
column_lbls=None,
header='',
column_type=None,
row_lbls=None,
transpose=False,
precision=2,
use_lbl_width=True,
comma_repl='<com>',
raw=False,
new=False,
standardize=False):
"""
Creates a csv table with aligned columns
make_csv_table
Args:
column_list (list):
column_lbls (None):
header (str):
column_type (None):
row_lbls (None):
transpose (bool):
Returns:
str: csv_text
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_csv import * # NOQA
>>> column_list = [[1, 2, 3], ['A', 'B', 'C']]
>>> column_lbls = ['num', 'alpha']
>>> header = '# Test CSV'
>>> column_type = (int, str)
>>> row_lbls = None
>>> transpose = False
>>> csv_text = make_csv_table(column_list, column_lbls, header, column_type, row_lbls, transpose)
>>> result = csv_text
>>> print(result)
# Test CSV
# num_rows=3
# num, alpha
1, A
2, B
3, C
"""
import utool as ut
assert comma_repl.find(',') == -1, 'comma_repl cannot contain a comma!'
if transpose:
column_lbls, row_lbls = row_lbls, column_lbls
column_list = list(map(list, zip(*column_list)))
if row_lbls is not None:
if isinstance(column_list, np.ndarray):
column_list = column_list.tolist()
if isinstance(row_lbls, np.ndarray):
row_lbls = row_lbls.tolist()
column_list = [row_lbls] + column_list
column_lbls = ['ROWLBL'] + list(map(six.text_type, column_lbls))
if column_type is not None:
column_type = [six.text_type] + column_type
if len(column_list) == 0:
print('[csv] No columns')
return header
column_len = [len(col) for col in column_list]
num_data = column_len[0]
if num_data == 0:
#print('[csv.make_csv_table()] No data. (header=%r)' % (header,))
return header
if any([num_data != clen for clen in column_len]):
print('[csv] column_lbls = %r ' % (column_lbls, ))
print('[csv] column_len = %r ' % (column_len, ))
print('[csv] inconsistent column lengths')
return header
if column_type is None:
column_type = list(map(type, ut.get_list_column(column_list, 0)))
#column_type = [type(col[0]) for col in column_list]
csv_rows = []
if new:
csv_rows.append(header)
elif not raw:
csv_rows.append(header)
if not standardize:
csv_rows.append('# num_rows=%r' % num_data)
column_maxlen = []
column_str_list = []
if column_lbls is None:
column_lbls = [''] * len(column_list)
def _toint(c):
if c is None:
return 'None'
try:
if np.isnan(c):
return 'nan'
except TypeError as ex:
print('------')
print('[csv] TypeError %r ' % ex)
print('[csv] _toint(c) failed')
print('[csv] c = %r ' % c)
print('[csv] type(c) = %r ' % type(c))
print('------')
raise
return ('%d') % int(c)
import uuid
textable_types = [uuid.UUID, six.text_type]
try:
if standardize:
def csv_format(r):
text = ut.repr2(r, precision=precision)
#text = six.text_type(r)
# Check if needs escape
escape_chars = ['"', ' ', ',']
if any([c in text for c in escape_chars]):
# escape quotes with quotes
text = text.replace('"', '""')
# encapsulate with quotes
text = '"' + text + '"'
return text
for col, lbl, coltype in zip(column_list, column_lbls,
column_type):
col_str = [csv_format(r) for r in col]
column_str_list.append(col_str)
pass
else:
# Loop over every column
for col, lbl, coltype in zip(column_list, column_lbls,
column_type):
# Loop over every row in the column (using list comprehension)
if coltype is list or util_type.is_list(coltype):
col_str = [
six.text_type(c).replace(',',
' ').replace('.', '<dot>')
for c in col
]
elif (coltype is float or util_type.is_float(coltype)
or coltype == np.float32
or util_type.is_valid_floattype(coltype)):
precision_fmtstr = '%.' + six.text_type(precision) + 'f'
col_str = [
'None' if r is None else precision_fmtstr % float(r)
for r in col
]
#col_ = [r if r is None else float(r) for r in col]
#col_str = [ut.repr2(r, precision=2) for r in col_]
elif coltype is int or util_type.is_int(
coltype) or coltype == np.int64:
col_str = [_toint(c) for c in (col)]
elif coltype in textable_types or util_type.is_str(coltype):
col_str = [
six.text_type(c).replace(',', comma_repl) for c in col
]
else:
print('[csv] is_unknown coltype=%r' % (coltype, ))
try:
col_str = [six.text_type(c) for c in (col)]
except UnicodeDecodeError:
try:
col_str = [ut.ensure_unicode(c) for c in (col)]
except Exception:
col_str = [repr(c) for c in (col)]
column_str_list.append(col_str)
for col_str, lbl in zip(column_str_list, column_lbls):
col_lens = [len(s) for s in (col_str)]
max_len = max(col_lens)
if use_lbl_width:
# The column label counts towards the column width
max_len = max(len(lbl), max_len)
column_maxlen.append(max_len)
except Exception as ex:
#ut.embed()
ut.printex(ex, keys=['col', 'lbl', 'coltype'])
raise
def _fmtfn(maxlen):
return ''.join(['%', six.text_type(maxlen + 2), 's'])
fmtstr = ','.join([_fmtfn(maxlen) for maxlen in column_maxlen])
try:
if new:
csv_rows.append('# ' + fmtstr % tuple(column_lbls))
elif not raw:
csv_rows.append('# ' + fmtstr % tuple(column_lbls))
#csv_rows.append('# ' + fmtstr % column_lbls)
except Exception as ex:
#print(len(column_list))
#ut.embed()
ut.printex(ex, keys=['fmtstr', 'column_lbls'])
raise
for row in zip(*column_str_list):
csv_rows.append(' ' + fmtstr % row)
csv_text = '\n'.join(csv_rows)
return csv_text
def make_csv_table(column_list=[], column_lbls=None, header='',
column_type=None, row_lbls=None, transpose=False,
precision=2, use_lbl_width=True, comma_repl='<comma>'):
"""
Creates a csv table with aligned columns
make_csv_table
Args:
column_list (list):
column_lbls (None):
header (str):
column_type (None):
row_lbls (None):
transpose (bool):
Returns:
str: csv_text
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_csv import * # NOQA
>>> column_list = [[1, 2, 3], ['A', 'B', 'C']]
>>> column_lbls = ['num', 'alpha']
>>> header = '# Test CSV'
>>> column_type = (int, str)
>>> row_lbls = None
>>> transpose = False
>>> csv_text = make_csv_table(column_list, column_lbls, header, column_type, row_lbls, transpose)
>>> result = csv_text
>>> print(result)
# Test CSV
# num_rows=3
# num, alpha
1, A
2, B
3, C
"""
import utool as ut
assert comma_repl.find(',') == -1, 'comma_repl cannot contain a comma!'
if transpose:
column_lbls, row_lbls = row_lbls, column_lbls
column_list = list(map(list, zip(*column_list)))
#import utool as ut
#ut.embed()
#column_lbls = row_lbls[0]
#row_list =
if row_lbls is not None:
if isinstance(column_list, np.ndarray):
column_list = column_list.tolist()
if isinstance(row_lbls, np.ndarray):
row_lbls = row_lbls.tolist()
column_list = [row_lbls] + column_list
column_lbls = ['ROWLBL'] + list(map(str, column_lbls))
if column_type is not None:
column_type = [str] + column_type
if len(column_list) == 0:
print('[csv] No columns')
return header
column_len = [len(col) for col in column_list]
num_data = column_len[0]
if num_data == 0:
#print('[csv.make_csv_table()] No data. (header=%r)' % (header,))
return header
if any([num_data != clen for clen in column_len]):
print('[csv] column_lbls = %r ' % (column_lbls,))
print('[csv] column_len = %r ' % (column_len,))
print('[csv] inconsistent column lengths')
return header
if column_type is None:
column_type = list(map(type, ut.get_list_column(column_list, 0)))
#column_type = [type(col[0]) for col in column_list]
csv_rows = []
csv_rows.append(header)
csv_rows.append('# num_rows=%r' % num_data)
column_maxlen = []
column_str_list = []
if column_lbls is None:
column_lbls = [''] * len(column_list)
def _toint(c):
if c is None:
return 'None'
try:
if np.isnan(c):
return 'nan'
except TypeError as ex:
print('------')
print('[csv] TypeError %r ' % ex)
print('[csv] _toint(c) failed')
print('[csv] c = %r ' % c)
print('[csv] type(c) = %r ' % type(c))
print('------')
raise
return ('%d') % int(c)
try:
# Loop over every column
for col, lbl, coltype in zip(column_list, column_lbls, column_type):
# Loop over every row in the column (using list comprehension)
if coltype is list or util_type.is_list(coltype):
#print('list')
#col_str = [str(c).replace(',', comma_repl).replace('.', '<dot>') for c in iter(col)]
col_str = [str(c).replace(',', ' ').replace('.', '<dot>') for c in col]
elif (coltype is float or
util_type.is_float(coltype) or
coltype == np.float32 or
util_type.is_valid_floattype(coltype)):
precision_fmtstr = '%.' + str(precision) + 'f'
col_str = ['None' if r is None else precision_fmtstr % float(r) for r in col]
elif coltype is int or util_type.is_int(coltype) or coltype == np.int64:
col_str = [_toint(c) for c in iter(col)]
elif coltype is str or coltype is unicode or util_type.is_str(coltype):
col_str = [str(c).replace(',', comma_repl) for c in col]
else:
print('[csv] is_unknown coltype=%r' % (coltype,))
col_str = [str(c) for c in iter(col)]
col_lens = [len(s) for s in iter(col_str)]
max_len = max(col_lens)
if use_lbl_width:
# The column label counts towards the column width
max_len = max(len(lbl), max_len)
column_maxlen.append(max_len)
column_str_list.append(col_str)
except Exception as ex:
#ut.embed()
ut.printex(ex, keys=['col', 'lbl', 'coltype'])
raise
_fmtfn = lambda maxlen: ''.join(['%', str(maxlen + 2), 's'])
fmtstr = ','.join([_fmtfn(maxlen) for maxlen in column_maxlen])
try:
csv_rows.append('# ' + fmtstr % tuple(column_lbls))
#csv_rows.append('# ' + fmtstr % column_lbls)
except Exception as ex:
#print(len(column_list))
#ut.embed()
ut.printex(ex, keys=['fmtstr', 'column_lbls'])
raise
for row in zip(*column_str_list):
csv_rows.append(' ' + fmtstr % row)
csv_text = '\n'.join(csv_rows)
return csv_text