To solve Jason's problem, we need to determine how many bottles of sports drink and coconut water he should consume to meet his daily requirements of calcium, potassium, and magnesium while minimizing his cost. 

Let's denote:
- $x$ as the number of bottles of sports drink,
- $y$ as the number of bottles of coconut water.

The objective is to minimize the total cost, which can be represented as $5x + 3y$, since each bottle of sports drink costs $5 and each bottle of coconut water costs $3.

The constraints are:
1. Calcium: $x + 4y \geq 10$ (since sports drink contains 1 unit of calcium per bottle and coconut water contains 4 units of calcium per bottle),
2. Potassium: $2x + y \geq 15$ (since sports drink contains 2 units of potassium per bottle and coconut water contains 1 unit of potassium per bottle),
3. Magnesium: $3x + 2y \geq 13$ (since sports drink contains 3 units of magnesium per bottle and coconut water contains 2 units of magnesium per bottle).

We also know that Jason cannot drink a negative number of bottles, so $x \geq 0$ and $y \geq 0$.

Now, let's represent this problem using Gurobi in Python:

```python
from gurobipy import *

# Create a model
m = Model("Jason_Nutrition")

# Define variables
x = m.addVar(vtype=GRB.CONTINUOUS, name="sports_drink", lb=0)
y = m.addVar(vtype=GRB.CONTINUOUS, name="coconut_water", lb=0)

# Set objective function
m.setObjective(5*x + 3*y, GRB.MINIMIZE)

# Add constraints
m.addConstr(x + 4*y >= 10, "calcium")
m.addConstr(2*x + y >= 15, "potassium")
m.addConstr(3*x + 2*y >= 13, "magnesium")

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Sports drink bottles: {x.x}")
    print(f"Coconut water bottles: {y.x}")
    print(f"Total cost: ${5*x.x + 3*y.x:.2f}")
else:
    print("No optimal solution found")
```