Marc - 1 month ago 6

Python Question

Here is my code:

`import math`

import matplotlib.pyplot as plt

import scipy.integrate as integrate

import numpy as np

#variables

n = 50

#integral

denominator = integrate.quad(lambda S: math.exp(-10*S)*(10*S**n),0,300)

#function

S = np.linspace(0,300,0.01)

y_i = (np.exp(-10*S)*(10*S**n))/denominator[0]

plt.plot(S,y_i)

I realise it's a very simplistic question. I'm trying to integrate the denominator across 0 and 300, and then plot the function y_i with the definite integral as the denominator of y_i. However when I plot it, the graph shown appears empty, when I am expecting a probability distribution, peaking at 5.

Can anyone help?

Answer

Firstly, you need `plt.show()`

at the end of your code snippet. Secondly and more importantly, you misused `np.linspace`

. Run it in interactive mode gives:

```
>>> import numpy as np
>>> S = np.linspace(0,300,0.01)
>>> S
array([], dtype=float64)
```

According to the documentation , the third argument, if not specified by name, is taken as the number of samples to generate. In this case, none (or a more disturbing interpretation is that you only want 0.01 sample). If by that last `0.01`

in that line, you mean the step size, maybe you are looking for something like `S = np.linspace(0,300,int(300.0/0.01))`

or as **@kameranis** pointed out: `S = np.arange(0, 300, 0.01)`

.

Resulting figure: