Once I failed DSA in my bachelor's degree and I never really understood Graphs and Path Finding but each year Advent of Code makes me try it once. Instead I used something easier than Dijkastra from scratch. Skimage have a way to find Minimum Cost Path

## Solution

```
import numpy as np
from skimage import graph
data,data1 = get_data(15)
data = np.array([int(i) for dt in data for i in dt ]).reshape(-1, len(data[0]))
data
data1 = np.array([int(i) for dt in data1 for i in dt ]).reshape(-1, len(data1[0]))
window = data1.copy()
rs,cs = window.shape
cost = graph.MCP(window, fully_connected=False)
cost.find_costs(starts = [(0,0)])
journey = [window[pos] for pos in cost.traceback((rs-1,cs-1))[1:]]
print(f"Part1: {sum(journey)}")
# 5times bigger
new_window = window.copy()
nrow = np.hstack([new_window, new_window+1, new_window+2, new_window+3, new_window+4])
new_window = np.vstack([nrow,nrow+1,nrow+2,nrow+3,nrow+4])
rs,cs = new_window.shape
new_window%=9
new_window[new_window==0]=9
cost = graph.MCP(new_window, fully_connected=False)
cost.find_costs(starts = [(0,0)])
journey = [new_window[pos] for pos in cost.traceback((rs-1,cs-1))[1:]]
print(f"Part2: {sum(journey)}")
```

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