# Logo

The logo for reliability can be created using the code below. The logo was generated using matplotlib version 3.3.3 and reliability version 0.5.5. The image produced requires subsequent cropping to remove surrounding white space.

```
from reliability.Distributions import Weibull_Distribution
import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(10, 4))
# blue distribution
x_blue_fill = np.linspace(0, 19, 1000)
blue_dist = Weibull_Distribution(alpha=5.5, beta=2, gamma=0.63)
y_blue_fill = blue_dist.PDF(linewidth=3, xvals=x_blue_fill, show_plot=False)
plt.fill_between(
x=x_blue_fill,
y1=np.zeros_like(y_blue_fill),
y2=y_blue_fill,
color="steelblue",
linewidth=0,
alpha=0.2,
)
blue_dist.PDF(linewidth=3, xvals=np.linspace(1.5, 19, 100))
# orange distribution
orange_dist = Weibull_Distribution(alpha=6, beta=3.3, gamma=8)
x_orange = np.linspace(0, 19, 1000)
orange_dist.PDF(linewidth=3, xvals=x_orange)
plt.plot([-4, orange_dist.gamma + 0.27], [0, 0], linewidth=5.5, color="darkorange")
# orange histogram
samples = orange_dist.random_samples(20000, seed=3)
plt.hist(
x=samples[samples < max(x_orange)],
density=True,
alpha=0.4,
color="darkorange",
bins=25,
edgecolor="k",
)
# text objects
plt.text(x=-4, y=0.005, s="RELIABILITY", size=70, fontname="Calibri")
plt.text(
x=-4,
y=-0.005,
va="top",
s="A Python library for reliability engineering",
size=34.85,
fontname="Calibri",
)
plt.xlim(-5, 20)
plt.title("")
plt.axis("off")
plt.tight_layout()
plt.show()
```

If you have any suggestions for future versions of this logo, please send them through by email to alpha.reliability@gmail.com