# day 8

https://adventofcode.com/2019/day/8

```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.read_csv("input.txt", header=None, names=["c"])
input_string = df["c"].values[0]
s = list(range(150, 15150, 150))
def get_num(x, n=0):
return list(x).count(str(n))
def make_layer_array(x: str) -> np.array:
a = np.array([int(x) for x in list(x)])
return a.reshape(6, 25)
layers = list()
layer_num = 0
num_zeros = 100000000
i_p = 0
best_layer = 0
best_string = ""
for i in s:
if layer_num == 0:
A = make_layer_array(input_string[i_p:i])[..., np.newaxis]
else:
A = np.dstack((A, make_layer_array(input_string[i_p:i])[..., np.newaxis]))
layer_num += 1
if get_num(input_string[i_p:i]) < num_zeros:
num_zeros = get_num(input_string[i_p:i])
best_layer = layer_num
best_string = input_string[i_p:i]
i_p = i
result = get_num(best_string, n=1) * get_num(best_string, n=2)
print("part 1:", result)
# 0 is black, 1 is white, and 2 is transparent.
# 25 pixels wide and 6 pixels tall
R = np.zeros((6, 25))
for x in range(A.shape[0]):
for y in range(A.shape[1]):
for k in A[x, y, :]:
if k != 2:
R[x, y] = k
break
plt.matshow(R)
plt.savefig("result.png", bbox_inches="tight")
plt.close()
```

## Discussion (0)