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kafanovd
requested changes
Nov 2, 2023
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| import numpy as np | ||
| from scipy.sparse import diags | ||
| from sklearn.linear_model import ElasticNet |
| from sklearn.linear_model import ElasticNet | ||
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| # set up grid points (# = Nz) | ||
| h = np.log(bound[1]/bound[0])/(Nz - 1) # equally spaced on logscale |
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| # construct C matrix from [1] | ||
| s_mesh, t_mesh = np.meshgrid(s, t) | ||
| C = np.exp(-t_mesh*s_mesh) |
| C *= h | ||
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| alpha = alpha1 + alpha2 | ||
| l1_ratio = alpha1/alpha |
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| # set up grid points (# = Nz) | ||
| h = np.log(bound[1]/bound[0])/(Nz - 1) # equally spaced on logscale | ||
| s = bound[0]*np.exp(np.arange(Nz)*h) # z (Nz by 1) |
Collaborator
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можно переменные обозвать терминами, чтобы более читабельно было
| Solution of argmin_x || Ax - b ||_2 | ||
| """ | ||
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| from scipy.optimize import nnls |
| C = np.exp(-t_mesh*z_mesh) | ||
| C[:, 0] /= 2. | ||
| C[:, -1] /= 2. | ||
| C *= h |
Collaborator
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```
h = np.log(bound[1]/bound[0])/(Nz - 1) # equally spaced on logscale
z = bound[0]*np.exp(np.arange(Nz)*h) # z (Nz by 1)
z_mesh, t_mesh = np.meshgrid(z, t)
C = np.exp(-t_mesh*z_mesh)
C[:, 0] /= 2.
C[:, -1] /= 2.
C *= h```
У тебя этот кусок используется много раз. Можно написать метод отдельный для него, чтобы не дублировать код
| from hp import hp | ||
| from read_file import read_file | ||
| from regopt import regopt | ||
| from interface import interface |
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| Bounds = 10.0**np.asarray(Bounds) | ||
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| t, C, T = read_file(interface.path, dt, proc = True)# time, transients, temperatures |
Collaborator
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коммент и пробелы убрать для proc
| self.path = os.getcwd() | ||
| self._update_files() | ||
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| def _update_files(self): |
Collaborator
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здесь тоже для всех методов типы и анотации
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