update user interface/circle ci fingerprint

.circleci/config.yml

@@ -1,93 +1,93 @@
-# Use the latest 2.1 version of CircleCI pipeline process engine.
-# See: https://circleci.com/docs/2.0/configuration-reference
-version: 2.1
-
-# Orbs are reusable packages of CircleCI configuration that you may share across projects, enabling you to create encapsulated, parameterized commands, jobs, and executors that can be used across multiple projects.
-# See: https://circleci.com/docs/2.0/orb-intro/
-orbs:
-  # The python orb contains a set of prepackaged CircleCI configuration you can use repeatedly in your configuration files
-  # Orb commands and jobs help you with common scripting around a language/tool
-  # so you dont have to copy and paste it everywhere.
-  # See the orb documentation here: https://circleci.com/developer/orbs/orb/circleci/python
-  python: circleci/[email protected]
-
-# Define a job to be invoked later in a workflow.
-# See: https://circleci.com/docs/2.0/configuration-reference/#jobs
-jobs:
-  build-and-test: # This is the name oAch the steps below will be executed - below will use a python 3.10.2 container
-    # Change the version below to your required version of python
-    docker:
-      - image: cimg/python:3.8
-    # Checkout the code as the first step. This is a dedicated CircleCI step.
-    # The python orb's install-packages step will install the dependencies from a Pipfile via Pipenv by default.
-    # Here we're making sure we use just use the system-wide pip. By default it uses the project root's requirements.txt.
-    # Then run your tests!
-    # CircleCI will report the results back to your VCS provider.
-    steps:
-      - checkout
-      - run:
-          name: install openblas
-          command: |
-              sudo apt-get update
-              sudo apt-get -y install libblas-dev liblapack-dev
-      - python/install-packages:
-          pkg-manager: pip
-          # app-dir: ~/project/package-directory/  # If you're requirements.txt isn't in the root directory.
-          # pip-dependency-file: test-requirements.txt  # if you have a different name for your requirements file, maybe one that combines your runtime and test requirements.
-      - run:
-          name: Run tests
-          # This assumes pytest is installed via the install-package step above
-          command: |
-              pytest --durations=0
-              pip install primme==3.2.*
-              pytest --durations=0 renormalizer/mps/tests/test_gs.py::test_multistate
-      - run:
-          name: Run examples
-          command: |
-              cd example; bash run.sh
-              cd ..
-      - run:
-          name: Build docs
-          command: cd doc; make html
-
-      - persist_to_workspace:
-          root: doc/
-          paths: html
-
-  # ref: https://circleci.com/blog/deploying-documentation-to-github-pages-with-continuous-integration/
-  docs-deploy:
-    docker:
-      - image: node:8.10.0
-    steps:
-      - checkout
-      - attach_workspace:
-          at: doc/
-      - run:
-          name: Disable jekyll builds
-          command: touch doc/html/.nojekyll
-      - run:
-          name: Install and configure dependencies
-          command: |
-            npm install -g --silent [email protected]
-            git config user.email "[email protected]"
-            git config user.name "liwt31"
-      - add_ssh_keys:
-          fingerprints:
-            - "cc:a3:29:5d:14:bb:bd:1b:e4:52:e2:c2:ac:e6:41:fa"
-      - run:
-          name: Deploy docs to gh-pages branch
-          command: gh-pages --dotfiles --message "[skip ci] Updates" --dist doc/html
-
-# Invoke jobs via workflows
-# See: https://circleci.com/docs/2.0/configuration-reference/#workflows
-workflows:
-  test: # This is the name of the workflow, feel free to change it to better match your workflow.
-    # Inside the workflow, you define the jobs you want to run.
-    jobs:
-      - build-and-test
-      - docs-deploy:
-          requires:
-            - build-and-test
-          filters:
-            branches:
+# Use the latest 2.1 version of CircleCI pipeline process engine.
+# See: https://circleci.com/docs/2.0/configuration-reference
+version: 2.1
+
+# Orbs are reusable packages of CircleCI configuration that you may share across projects, enabling you to create encapsulated, parameterized commands, jobs, and executors that can be used across multiple projects.
+# See: https://circleci.com/docs/2.0/orb-intro/
+orbs:
+  # The python orb contains a set of prepackaged CircleCI configuration you can use repeatedly in your configuration files
+  # Orb commands and jobs help you with common scripting around a language/tool
+  # so you dont have to copy and paste it everywhere.
+  # See the orb documentation here: https://circleci.com/developer/orbs/orb/circleci/python
+  python: circleci/[email protected]
+
+# Define a job to be invoked later in a workflow.
+# See: https://circleci.com/docs/2.0/configuration-reference/#jobs
+jobs:
+  build-and-test: # This is the name oAch the steps below will be executed - below will use a python 3.10.2 container
+    # Change the version below to your required version of python
+    docker:
+      - image: cimg/python:3.8
+    # Checkout the code as the first step. This is a dedicated CircleCI step.
+    # The python orb's install-packages step will install the dependencies from a Pipfile via Pipenv by default.
+    # Here we're making sure we use just use the system-wide pip. By default it uses the project root's requirements.txt.
+    # Then run your tests!
+    # CircleCI will report the results back to your VCS provider.
+    steps:
+      - checkout
+      - run:
+          name: install openblas
+          command: |
+              sudo apt-get update
+              sudo apt-get -y install libblas-dev liblapack-dev
+      - python/install-packages:
+          pkg-manager: pip
+          # app-dir: ~/project/package-directory/  # If you're requirements.txt isn't in the root directory.
+          # pip-dependency-file: test-requirements.txt  # if you have a different name for your requirements file, maybe one that combines your runtime and test requirements.
+      - run:
+          name: Run tests
+          # This assumes pytest is installed via the install-package step above
+          command: |
+              pytest --durations=0
+              pip install primme==3.2.*
+              pytest --durations=0 renormalizer/mps/tests/test_gs.py::test_multistate
+      - run:
+          name: Run examples
+          command: |
+              cd example; bash run.sh
+              cd ..
+      - run:
+          name: Build docs
+          command: cd doc; make html
+
+      - persist_to_workspace:
+          root: doc/
+          paths: html
+
+  # ref: https://circleci.com/blog/deploying-documentation-to-github-pages-with-continuous-integration/
+  docs-deploy:
+    docker:
+      - image: node:8.10.0
+    steps:
+      - checkout
+      - attach_workspace:
+          at: doc/
+      - run:
+          name: Disable jekyll builds
+          command: touch doc/html/.nojekyll
+      - run:
+          name: Install and configure dependencies
+          command: |
+            npm install -g --silent [email protected]
+            git config user.email "[email protected]"
+            git config user.name "liwt31"
+      - add_ssh_keys:
+          fingerprints:
+            - "e6:24:b4:ab:d5:82:2b:6a:b5:a9:17:71:99:6d:0f:53"
+      - run:
+          name: Deploy docs to gh-pages branch
+          command: gh-pages --dotfiles --message "[skip ci] Updates" --dist doc/html
+
+# Invoke jobs via workflows
+# See: https://circleci.com/docs/2.0/configuration-reference/#workflows
+workflows:
+  test: # This is the name of the workflow, feel free to change it to better match your workflow.
+    # Inside the workflow, you define the jobs you want to run.
+    jobs:
+      - build-and-test
+      - docs-deploy:
+          requires:
+            - build-and-test
+          filters:
+            branches:
               only: master

renormalizer/model/h_qc.py

@@ -39,28 +39,33 @@ def read_fcidump(fname, norb):
             else:
                 nuc = integral
 
-    nsorb = norb*2
+    sh, aseri = int_to_h(h, eri)
+
+    logger.info(f"nuclear repulsion: {nuc}")
+
+    return sh, aseri, nuc
+
+
+def int_to_h(h, eri):
+    nsorb = len(h) * 2
     seri = np.zeros((nsorb, nsorb, nsorb, nsorb))
-    sh = np.zeros((nsorb,nsorb))
-    for p, q, r, s in itertools.product(range(nsorb),repeat=4):
-    # a_p^\dagger a_q^\dagger a_r a_s
+    sh = np.zeros((nsorb, nsorb))
+    for p, q, r, s in itertools.product(range(nsorb), repeat=4):
+        # a_p^\dagger a_q^\dagger a_r a_s
         if p % 2 == s % 2 and q % 2 == r % 2:
-            seri[p,q,r,s] = eri[p//2,s//2,q//2,r//2] 
-    
-    for q, s in itertools.product(range(nsorb),repeat=2):
+            seri[p, q, r, s] = eri[p // 2, s // 2, q // 2, r // 2]
+
+    for q, s in itertools.product(range(nsorb), repeat=2):
         if q % 2 == s % 2:
-            sh[q,s] = h[q//2,s//2]
-    
+            sh[q, s] = h[q // 2, s // 2]
+
     aseri = np.zeros((nsorb, nsorb, nsorb, nsorb))
-    for q, s in itertools.product(range(nsorb),repeat=2):
+    for q, s in itertools.product(range(nsorb), repeat=2):
         for p, r in itertools.product(range(q), range(s)):
-            #aseri[p,q,r,s] = seri[p,q,r,s] - seri[q,p,r,s]
-            aseri[p,q,r,s] = seri[p,q,r,s] - seri[p,q,s,r]
-
-    logger.info(f"nuclear repulsion: {nuc}")
-
-    return sh, aseri, nuc
-
+            # aseri[p,q,r,s] = seri[p,q,r,s] - seri[q,p,r,s]
+            aseri[p, q, r, s] = seri[p, q, r, s] - seri[p, q, s, r]
+
+    return sh, aseri
 
 def qc_model(h1e, h2e):
     """

renormalizer/mps/gs.py

@@ -86,11 +86,11 @@ def optimize_mps(mps: Mps, mpo: Mpo, omega: float = None) -> Tuple[List, Mps]:
 
     # ensure that mps is left or right-canonical
     # TODO: start from a mix-canonical MPS
-    if mps.is_left_canon:
-        mps.ensure_right_canon()
+    if mps.is_left_canonical:
+        mps.ensure_right_canonical()
         env = "R"
     else:
-        mps.ensure_left_canon()
+        mps.ensure_left_canonical()
         env = "L"
 
     # construct the environment matrix
@@ -135,10 +135,10 @@ def optimize_mps(mps: Mps, mpo: Mpo, omega: float = None) -> Tuple[List, Mps]:
     assert res_mps is not None
     # remove the redundant basis near the edge
     if mps.optimize_config.nroots == 1:
-        res_mps = res_mps.normalize("mps_only").ensure_left_canon().canonicalise()
+        res_mps = res_mps.normalize("mps_only").ensure_left_canonical().canonicalise()
         logger.info(f"{res_mps}")
     else:
-        res_mps = [mp.normalize("mps_only").ensure_left_canon().canonicalise() for mp in res_mps]
+        res_mps = [mp.normalize("mps_only").ensure_left_canonical().canonicalise() for mp in res_mps]
         logger.info(f"{res_mps[0]}")
     return macro_iteration_result, res_mps
 

renormalizer/mps/mp.py

@@ -110,14 +110,19 @@ def bond_dims(self) -> List:
         # return a list so that the logging result is more pretty
         return bond_dims
 
+
+    vbond_list = vbond_dims = bond_list = bond_dims
+
     @property
     def bond_dims_mean(self) -> int:
         return int(round(np.mean(self.bond_dims)))
 
     @property
-    def pbond_list(self):
+    def pbond_dims(self):
         return self.model.pbond_list
 
+    pbond_list = pbond_dims
+
     def build_empty_qn(self):
         self.qntot = 0
         # set qnidx to the right to be consistent with most MPS/MPO setups
@@ -171,20 +176,20 @@ def check_right_canonical(self, rtol=1e-5, atol=1e-8):
         return True
 
     @property
-    def is_left_canon(self):
+    def is_left_canonical(self):
         """
         check the qn center in the L-canonical structure
         """
         return self.qnidx == self.site_num - 1
 
     @property
-    def is_right_canon(self):
+    def is_right_canonical(self):
         """
         check the qn center in the R-canonical structure
         """
         return self.qnidx == 0
 
-    def ensure_left_canon(self, rtol=1e-5, atol=1e-8):
+    def ensure_left_canonical(self, rtol=1e-5, atol=1e-8):
         if self.to_right or self.qnidx != self.site_num-1 or \
                 (not self.check_left_canonical(rtol, atol)):
             self.move_qnidx(0)
@@ -193,7 +198,7 @@ def ensure_left_canon(self, rtol=1e-5, atol=1e-8):
         else:
             return self
 
-    def ensure_right_canon(self, rtol=1e-5, atol=1e-8):
+    def ensure_right_canonical(self, rtol=1e-5, atol=1e-8):
         if (not self.to_right) or self.qnidx != 0 or \
                 (not self.check_right_canonical(rtol, atol)):
             self.move_qnidx(self.site_num - 1)
@@ -437,7 +442,7 @@ def compress(self, temp_m_trunc=None, ret_s=False):
         if not self.is_mpo:
             # ensure mps is canonicalised. This is time consuming.
             # to disable this, run python as `python -O`
-            if self.is_left_canon:
+            if self.is_left_canonical:
                 assert self.check_left_canonical()
             else:
                 assert self.check_right_canonical()
@@ -513,7 +518,7 @@ def variational_compress(self, mpo=None, guess=None):
             # the attributes of guess would be the same as self
             guess = compressed_mpo.apply(compressed_mps)
         mps = guess
-        mps.ensure_left_canon()
+        mps.ensure_left_canonical()
         logger.info(f"initial guess bond dims: {mps.bond_dims}")
 
         procedure = mps.compress_config.vprocedure
@@ -1022,9 +1027,6 @@ def total_bytes(self):
     def _get_sigmaqn(self, idx):
         raise NotImplementedError
 
-    def set_threshold(self, val):
-        self.compress_config.threshold = val
-
     def __eq__(self, other):
         for m1, m2 in zip(self, other):
             if not allclose(m1, m2):

renormalizer/mps/mpo.py

@@ -482,5 +482,3 @@ def from_mp(cls, model, mp):
             mpo.append(mt)
         mpo.build_empty_qn()
         return mpo
-
-

renormalizer/mps/mps.py

@@ -914,7 +914,7 @@ def mpo_t(t, *args, **kwargs):
 
         # only not canonicalise when force_ovlp=True and to_right=False
         if not (self.evolve_config.force_ovlp and not self.to_right):
-            self.ensure_left_canon()
+            self.ensure_left_canonical()
 
         # `self` should not be modified during the evolution
         if imag_time:
@@ -1119,7 +1119,7 @@ def _evolve_tdvp_mu_cmf(self, mpo, evolve_dt) -> "Mps":
         else:
             coef = 1j
 
-        self.ensure_left_canon()
+        self.ensure_left_canonical()
 
         # `self` should not be modified during the evolution
         # mps: the mps to return
@@ -1683,7 +1683,7 @@ def calc_bond_entropy(self) -> np.ndarray:
         # Make sure that the bond entropy is from the left to the right and not
         # destroy the original mps
         mps = self.copy()
-        mps.ensure_right_canon()
+        mps.ensure_right_canonical()
         _, s_list = mps.compress(temp_m_trunc=np.inf, ret_s=True)
         return np.array([calc_vn_entropy(sigma ** 2) for sigma in s_list])
 

renormalizer/mps/tda.py

@@ -88,7 +88,7 @@ def kernel(self, restart=False, include_psi0=False):
 
         if not restart:
             # make sure that M is not redundant near the edge
-            mps = self.mps.ensure_right_canon().canonicalise().normalize("mps_and_coeff").canonicalise()
+            mps = self.mps.ensure_right_canonical().canonicalise().normalize("mps_and_coeff").canonicalise()
             logger.debug(f"reference mps shape, {mps}")
             mps_r_cano = mps.copy()
             assert mps.to_right