Caroline.py - 3 months ago 7

Python Question

I am wanting to solve a systems of equations through linalg.solve(A, b) Solve a linear matrix equation, or system of linear scalar equations from scipy.org. Specifically, I have two dictionaries, dict1 and dict1, and I need to convert them to matrices in order to use the above script.

`food = ['fruits', 'vegetables', 'bread', 'meat']`

frequency = ['daily', 'rarely']

consumptions = {'fruits': {'daily': 6, 'rarely': 4}, 'vegetables': {'daily': 8, 'rarely': 6}, 'bread': {'daily': 2, 'rarely': 1}, 'meat': {'daily': 2, 'rarely': 1}}

dict1 = {}

for f in food: #type of food

for j in food:

dict2 = {}

total = 0.

for q in frequency:

dict2.update({q:(consumptions.get(j).get(q)*consumptions.get(f).get(q))})

key = f+'v'+j #comparing the different foods

dict1.update({key:dict2})

This gives me:

`{'breadvbread': {'daily': 4, 'rarely': 1},`

'breadvfruits': {'daily': 12, 'rarely': 4},

'breadvmeat': {'daily': 4, 'rarely': 1},

'breadvvegetables': {'daily': 16, 'rarely': 6},

'fruitsvbread': {'daily': 12, 'rarely': 4},

'fruitsvfruits': {'daily': 36, 'rarely': 16},

'fruitsvmeat': {'daily': 12, 'rarely': 4},

'fruitsvvegetables': {'daily': 48, 'rarely': 24},

'meatvbread': {'daily': 4, 'rarely': 1},

'meatvfruits': {'daily': 12, 'rarely': 4},

'meatvmeat': {'daily': 4, 'rarely': 1},

'meatvvegetables': {'daily': 16, 'rarely': 6},

'vegetablesvbread': {'daily': 16, 'rarely': 6},

'vegetablesvfruits': {'daily': 48, 'rarely': 24},

'vegetablesvmeat': {'daily': 16, 'rarely': 6},

'vegetablesvvegetables': {'daily': 64, 'rarely': 36}}

I would like to convert this into a 4 x 4 matrix since I am using 4 types of foods. I did not put dict2 as once I figure out how to convert to a matrix with one dictionary, I can do the other but if you need it, I can update.

I am new to Python and wanted to play around with dictionaries and the matrix solver :) . It was easy to do it with arrays, but now I want to see how to go about if I have dictionaries.

Answer

You can create a 4x4x2 numpy array from the dictionary using list comprehension:

```
import numpy as np
A = np.array([[[consumptions[x]["daily"]*consumptions[y]["daily"],
consumptions[x]["rarely"]*consumptions[y]["rarely"]]
for y in food]
for x in food])
```

This will give you:

```
array([[[36, 16],
[48, 24],
[12, 4],
[12, 4]],
[[48, 24],
[64, 36],
[16, 6],
[16, 6]],
[[12, 4],
[16, 6],
[ 4, 1],
[ 4, 1]],
[[12, 4],
[16, 6],
[ 4, 1],
[ 4, 1]]])
```

Then, to get a 4x4 matrix of the `daily`

values and the `rarely`

values separately, use numpy's advanced slicing:

```
daily = A[:, :, 0]
array([[36, 48, 12, 12],
[48, 64, 16, 16],
[12, 16, 4, 4],
[12, 16, 4, 4]])
```

If you want to make the meaning of these values more explicit, you can convert this to a pandas DataFrame:

```
import pandas as pd
pd.DataFrame(daily, columns=food, index=food)
fruits vegetables bread meat
fruits 36 48 12 12
vegetables 48 64 16 16
bread 12 16 4 4
meat 12 16 4 4
```