Exercise 1i) Extending the ODEResult class 1p We will now implement a few helper methods in...
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Exercise 1i) Extending the ODEResult class 1p We will now implement a few helper methods in the ODEResult class that will make use of later. • Implement two methods num_states and num_timepoints as properties (using @property) on the ODEResult class, using the shape of solution array. From scipy.solve_ivp, the solution has a shape of (num_states, num_timepoints). • Implement a test called test_ODEResults that tests that if you create a ODEResults with a time array of length 3 and a solution array of shape (2, 3) then the num_states should be 2 and num_timepoints is 3. Hint - Creating an artificial solution You can create an artificial solution using e.g numpy.zeros import ode results = ode. ODEResult(time=np.array([0, 1, 2]), solution=n Exercise 1i) Extending the ODEResult class 1p We will now implement a few helper methods in the ODEResult class that will make use of later. • Implement two methods num_states and num_timepoints as properties (using @property) on the ODEResult class, using the shape of solution array. From scipy.solve_ivp, the solution has a shape of (num_states, num_timepoints). • Implement a test called test_ODEResults that tests that if you create a ODEResults with a time array of length 3 and a solution array of shape (2, 3) then the num_states should be 2 and num_timepoints is 3. Hint - Creating an artificial solution You can create an artificial solution using e.g numpy.zeros import ode results = ode.ODEResult(time=np.array([0, 1, 2]), solution=n Exercise 1i) Extending the ODEResult class 1p We will now implement a few helper methods in the ODEResult class that will make use of later. • Implement two methods num_states and num_timepoints as properties (using @property) on the ODEResult class, using the shape of solution array. From scipy.solve_ivp, the solution has a shape of (num_states, num_timepoints). • Implement a test called test_ODEResults that tests that if you create a ODEResults with a time array of length 3 and a solution array of shape (2, 3) then the num_states should be 2 and num_timepoints is 3. Hint - Creating an artificial solution You can create an artificial solution using e.g numpy.zeros import ode results = ode. ODEResult(time=np.array([0, 1, 2]), solution=n Exercise 1i) Extending the ODEResult class 1p We will now implement a few helper methods in the ODEResult class that will make use of later. • Implement two methods num_states and num_timepoints as properties (using @property) on the ODEResult class, using the shape of solution array. From scipy.solve_ivp, the solution has a shape of (num_states, num_timepoints). • Implement a test called test_ODEResults that tests that if you create a ODEResults with a time array of length 3 and a solution array of shape (2, 3) then the num_states should be 2 and num_timepoints is 3. Hint - Creating an artificial solution You can create an artificial solution using e.g numpy.zeros import ode results = ode.ODEResult(time=np.array([0, 1, 2]), solution=n
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Related Book For
Financial Accounting and Reporting a Global Perspective
ISBN: 978-1408076866
4th edition
Authors: Michel Lebas, Herve Stolowy, Yuan Ding
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