shesha.config.config_setter_utils Namespace Reference

Functions
def	enforce_int (n)
def	enforce_float (f)
def	enforce_or_cast_bool (b)
def	enforce_array (data, size, dtype=np.float32, scalar_expand=False)
def	enforce_arrayMultiDim (data, shape, dtype=np.float32)

Function Documentation

enforce_array()

def shesha.config.config_setter_utils.enforce_array	(		data,
			size,
			dtype = np.float32,
			scalar_expand = False
	)

Definition at line 66 of file config_setter_utils.py.

def enforce_array(data, size, dtype=np.float32, scalar_expand=False):
    # Scalar case
    if isinstance(data, (int, float, complex)):
        data = [data]
 
    # Singleton case
    if len(data) == 1:
        if scalar_expand or size == 1:
            return np.full(size, data[0], dtype=dtype)
        else:
            raise TypeError("This non-singleton array cannot " + \
                            "be initialized with a scalar.")
 
    if len(data) != size:
        raise TypeError("Input argument has wrong number of elements.")
    if isinstance(data, np.ndarray) and len(data.shape) > 1:
        raise TypeError("Multidimensional ndarray input is not allowed")
    if isinstance(data,
                  list) and not all([isinstance(x, (float, int, complex))
                                     for x in data]):
        raise TypeError("Input list may only contain numerical values.")
 
    # OK, now let's try it
    return np.array(data, dtype=dtype)
 
 

enforce_arrayMultiDim()

def shesha.config.config_setter_utils.enforce_arrayMultiDim	(		data,
			shape,
			dtype = np.float32
	)

Definition at line 92 of file config_setter_utils.py.

def enforce_arrayMultiDim(data, shape, dtype=np.float32):
    if not isinstance(data, np.ndarray):
        raise TypeError("Input argument must be a np.ndarray")
    else:
        doRaise = False
        if len(data.shape) != len(shape):
            doRaise = True
        for (i, j) in zip(data.shape, shape):
            if j != -1 and i != j:
                doRaise = True
        if doRaise:
            raise TypeError(
                    "Input has wrong dimensions, expect multi dimensional arrays")
 
    return np.array(data, dtype=dtype)

enforce_float()

def shesha.config.config_setter_utils.enforce_float

(

f

)

Definition at line 47 of file config_setter_utils.py.

def enforce_float(f):
    if not (isinstance(f, float) or isinstance(f, int)):
        raise TypeError("Value should be float.")
    return float(f)
 
 

enforce_int()

def shesha.config.config_setter_utils.enforce_int

(

n

)

Definition at line 41 of file config_setter_utils.py.

def enforce_int(n):
    if not isinstance(n, int):
        raise TypeError("Value should be integer.")
    return n
 
 

enforce_or_cast_bool()

def shesha.config.config_setter_utils.enforce_or_cast_bool

(

b

)

Definition at line 53 of file config_setter_utils.py.

def enforce_or_cast_bool(b):
    if isinstance(b, bool):
        return b
    if isinstance(b, (int, float)):
        if b == 0:
            return False
        elif b == 1:
            return True
        else:
            raise ValueError("Will not cast non 0/1 int or float to boolean.")
    raise TypeError("Will only cast int and float to booleans.")