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Remove distutils for py3.12 compatibility #43

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May 27, 2024
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Remove distutils for py3.12 compatibility #43

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a7bc56b
Remove distutils for py3.12 compatibility
Thoemi09 Oct 16, 2023
16dd9d1
Remove numpy_compat.py
Thoemi09 Oct 16, 2023
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5 changes: 2 additions & 3 deletions python/triqs_tprf/hf_response.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,6 @@
import sys
import itertools
import numpy as np
from .numpy_compat import np_eigh

# ----------------------------------------------------------------------
class BaseResponse(object):
Expand Down Expand Up @@ -80,8 +79,8 @@ def _compute_drho_k_dop(self, op):
E_p = self.e_k.data.copy() + eps*op[None, ...]
E_m = self.e_k.data.copy() - eps*op[None, ...]

e_p, U_p = np_eigh(E_p)
e_m, U_m = np_eigh(E_m)
e_p, U_p = np.linalg.eigh(E_p)
e_m, U_m = np.linalg.eigh(E_m)

fermi = lambda e, beta: 1./(np.exp(beta * e) + 1)

Expand Down
7 changes: 3 additions & 4 deletions python/triqs_tprf/hf_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,6 @@
import sys
import itertools
import numpy as np
from .numpy_compat import np_eigvalsh, np_eigh

# ----------------------------------------------------------------------

Expand Down Expand Up @@ -155,7 +154,7 @@ def update_chemical_potential(self, N_target, mu0=None):
if mu0 is None:
mu0 = self.mu

e = np_eigvalsh(self.e_k_MF.data)
e = np.linalg.eigvalsh(self.e_k_MF.data)

fermi = lambda e : 1./(np.exp(self.beta * e) + 1)

Expand All @@ -173,7 +172,7 @@ def target_function(mu):
# ------------------------------------------------------------------
def update_momentum_density_matrix(self):

e, V = np_eigh(self.e_k_MF.data)
e, V = np.linalg.eigh(self.e_k_MF.data)
e -= self.mu

fermi = lambda e : 1./(np.exp(self.beta * e) + 1)
Expand All @@ -193,7 +192,7 @@ def update_density_matrix(self):
# ------------------------------------------------------------------
def update_non_int_free_energy(self):

e = np_eigvalsh(self.e_k_MF.data)
e = np.linalg.eigvalsh(self.e_k_MF.data)
e -= self.mu

self.Omega0 = -1./self.beta * np.sum( np.log(1. + np.exp(-self.beta*e)) )
Expand Down
4 changes: 1 addition & 3 deletions python/triqs_tprf/matrix_rpa.py
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Expand Up @@ -36,8 +36,6 @@
import itertools
import numpy as np

from triqs_tprf.numpy_compat import np_inv

# ----------------------------------------------------------------------
def tprf_order_to_matrix_rpa_order(tensor):
"""Bring the order used in tprf, i.e. c^+ccc^+ for susceptibilites
Expand Down Expand Up @@ -205,7 +203,7 @@ def matrix_rpa(chi0_matrix, u_matrix):

u_chi0 = np.einsum('...ij,...jk->...ik', chi0_matrix, u_matrix)

inverse_matrix = np_inv(np.eye(norb**2) - u_chi0)
inverse_matrix = np.linalg.inv(np.eye(norb**2) - u_chi0)

chi_rpa_matrix = np.einsum('...ij,...jk->...ik', inverse_matrix, chi0_matrix)

Expand Down
68 changes: 0 additions & 68 deletions python/triqs_tprf/numpy_compat.py
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42 changes: 20 additions & 22 deletions test/python/mean_field.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@

# ----------------------------------------------------------------------

from triqs_tprf.numpy_compat import is_numpy_newer_than
from triqs_tprf.lattice import lattice_dyson_g0_wk
from triqs_tprf.lattice import lindhard_chi00

Expand Down Expand Up @@ -151,27 +150,26 @@ def get_tb_model(t, U, n, m, mu=0., vanilla_tb=False):
# ----------------------------------------------------------------------
def test_fermi_distribution_derivative(verbose=False):

if is_numpy_newer_than('1.8.0'):
beta = 3.3
e = np.linspace(-5., 5., num=1000)
f = fermi_distribution(beta, e)
df = fermi_distribution_derivative(beta, e)

from scipy.interpolate import InterpolatedUnivariateSpline
sp = InterpolatedUnivariateSpline(e, f)
dsp = sp.derivative(1)
df_ref = dsp(e)

np.testing.assert_almost_equal(df, df_ref)

if verbose:
import matplotlib.pyplot as plt
plt.plot(e, f, label='f')
plt.plot(e, df, label='df')
plt.plot(e, df_ref, label='df_ref')
plt.legend()
plt.show()
exit()
beta = 3.3
e = np.linspace(-5., 5., num=1000)
f = fermi_distribution(beta, e)
df = fermi_distribution_derivative(beta, e)

from scipy.interpolate import InterpolatedUnivariateSpline
sp = InterpolatedUnivariateSpline(e, f)
dsp = sp.derivative(1)
df_ref = dsp(e)

np.testing.assert_almost_equal(df, df_ref)

if verbose:
import matplotlib.pyplot as plt
plt.plot(e, f, label='f')
plt.plot(e, df, label='df')
plt.plot(e, df_ref, label='df_ref')
plt.legend()
plt.show()
exit()

# ----------------------------------------------------------------------
def get_density_of_states(eps, t):
Expand Down
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