| name | python-scicomp-pattern1-load-process-eng-data |
| description | Sub-skill of python-scientific-computing: Pattern 1: Load and Process Engineering Data (+2). |
| version | 1.0.0 |
| category | data |
| type | reference |
| scripts_exempt | true |
Pattern 1: Load and Process Engineering Data (+2)
Pattern 1: Load and Process Engineering Data
import numpy as np
data = np.loadtxt('../data/measurements.csv', delimiter=',', skiprows=1)
time = data[:, 0]
temperature = data[:, 1]
pressure = data[:, 2]
*See sub-skills for full details.*
```python
from scipy.optimize import fsolve
def system(vars):
x, y, z = vars
eq1 = x + y + z - 6
eq2 = 2*x - y + z - 1
eq3 = x + 2*y - z - 3
return [eq1, eq2, eq3]
solution = fsolve(system, [1, 1, 1])
Pattern 3: Curve Fitting
from scipy.optimize import curve_fit
def model(x, a, b, c):
return a * np.exp(-b * x) + c
params, covariance = curve_fit(model, x_data, y_data)
a_fit, b_fit, c_fit = params