This is a continuation of the question asked here: Exponential of large negative numbers. The reason I want to use decimal is that np.exp(-large_numbers) return 0.0. Using Eric's answer to this question: https://stackoverflow.com/a/7771210/6943476, I tried converting my np.array to decimal but I still get the data-type
numpy.ndarray.
Coding ability: Beginner
My final goal is to have a function return a damped sinusoid:
def waveform(mass_sm, amplitude, F, Q, phi, Time):
w = F/mass_sm
print type(Time)
Ntime = np.array(Time,dtype=np.dtype(decimal.Decimal))
priny type(Ntime)
return mass_sm * amplitude * np.sin(w * Ntime + phi) * np.exp(-w * Ntime/ (2 * Q))
It tried to debug the code by breaking down the return function into the sine, and then the exponential:
def waveform(mass_sm, amplitude, F, Q, phi, Time):
w = F/mass_sm
print type(Time)
Ntime = np.array(Time,dtype=np.dtype(decimal.Decimal))
priny type(Ntime)
return mass_sm * amplitude * np.sin(w * Ntime + phi)
Output:
<type 'numpy.ndarray'>
<type 'numpy.ndarray'>
AttributeError: 'float' object has no attribute 'sin'
For the exponential part, I get the (expected) error that:
AttributeError: 'float' object has no attribute 'exp'
I have also tried to convert the elements of my array to decimal by doing this:
Ntime = [decimal.Decimal(i) for i in Time]
This time, getting this error for sine:
TypeError: can't multiply sequence by non-int of type 'float'
and this error for exp:
TypeError: bad operand type for unary -: 'list'