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Mini Shell
Mini Shell
"""Prints type-coercion tables for the built-in NumPy types
"""
from __future__ import division, absolute_import, print_function
import numpy as np
# Generic object that can be added, but doesn't do anything else
class GenericObject(object):
def __init__(self, v):
self.v = v
def __add__(self, other):
return self
def __radd__(self, other):
return self
dtype = np.dtype('O')
def print_cancast_table(ntypes):
print('X', end=' ')
for char in ntypes:
print(char, end=' ')
print()
for row in ntypes:
print(row, end=' ')
for col in ntypes:
print(int(np.can_cast(row, col)), end=' ')
print()
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
print('+', end=' ')
for char in ntypes:
print(char, end=' ')
print()
for row in ntypes:
if row == 'O':
rowtype = GenericObject
else:
rowtype = np.obj2sctype(row)
print(row, end=' ')
for col in ntypes:
if col == 'O':
coltype = GenericObject
else:
coltype = np.obj2sctype(col)
try:
if firstarray:
rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
else:
rowvalue = rowtype(inputfirstvalue)
colvalue = coltype(inputsecondvalue)
if use_promote_types:
char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
else:
value = np.add(rowvalue, colvalue)
if isinstance(value, np.ndarray):
char = value.dtype.char
else:
char = np.dtype(type(value)).char
except ValueError:
char = '!'
except OverflowError:
char = '@'
except TypeError:
char = '#'
print(char, end=' ')
print()
print("can cast")
print_cancast_table(np.typecodes['All'])
print()
print("In these tables, ValueError is '!', OverflowError is '@', TypeError is '#'")
print()
print("scalar + scalar")
print_coercion_table(np.typecodes['All'], 0, 0, False)
print()
print("scalar + neg scalar")
print_coercion_table(np.typecodes['All'], 0, -1, False)
print()
print("array + scalar")
print_coercion_table(np.typecodes['All'], 0, 0, True)
print()
print("array + neg scalar")
print_coercion_table(np.typecodes['All'], 0, -1, True)
print()
print("promote_types")
print_coercion_table(np.typecodes['All'], 0, 0, False, True)
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