Merge branch 'dev'

# Conflicts:
#	pyproject.toml

.github/workflows/test.yaml

@@ -10,6 +10,7 @@ on:
       - main
       - auto_test
       - dev
+      - dev_1.0_grammar
   pull_request:
     branches:
       - main
@@ -22,22 +23,22 @@ jobs:
   test:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-python@v2
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v3
         with:
-          python-version: 3.7
+          python-version: 3.9
       - name: Install poetry
         uses: abatilo/[email protected]
         with:
           poetry-version: 1.1.12
       - name: Install dependencies
         run: |
-          poetry install --no-dev
+          poetry update --no-dev
           poetry run python -m pip install pytest-cov
       - name: Run tests
         run: |
           cd tests
-          poetry run python -m pytest --cov=../glyles/ --cov-report=xml -m "not todo and not slow"
+          poetry run python -m pytest --cov=../glyles/ --cov-report=xml -m "not todo"
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:

examples/filtering.ipynb

@@ -467,4 +467,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}

examples/visualization.ipynb

@@ -77,45 +77,6 @@
     "Image(glycan.save_dot(\"files/viz_2.dot\", horizontal=True).create_png())"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "## SNFG Visualization\n",
-    "\n",
-    "GlyLES can also be used to visualize glycans using the symbols from the SNFG standard.\n",
-    "\n",
-    "To better fit the visualization to your needs, there are some parameter, you can tune to adapt the visualization to your needs. This includes width and height of the whole image, border-size of the symbols, and line width of the edges between the symbols."
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "<PIL.Image.Image image mode=RGB size=1500x450>",
-      "image/png": "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\n"
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "display(glycan.create_snfg_img(\"files/viz_snfg.png\", width=300, height=100))"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
-  },
   {
    "cell_type": "markdown",
    "source": [
@@ -182,4 +143,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
+}

glyles/__main__.py

@@ -1,10 +1,9 @@
 import os
 import sys
 import argparse
-import pkg_resources
-
 
 from glyles import convert
+from glyles.version import __version__
 
 
 def parse_args(args):
@@ -40,7 +39,7 @@ def parse_args(args):
         "-v",
         "--version",
         action="version",
-        version=f"%(prog)s {pkg_resources.get_distribution('glyles').version}"
+        version=f"%(prog)s {__version__}"
     )
     return vars(parser.parse_args(args))
 

glyles/glycans/factory/factory.py

@@ -5,6 +5,9 @@
 from glyles.glycans.utils import Config, Enantiomer, Lactole
 from glyles.grammar.GlycanLexer import GlycanLexer
 
+if not hasattr(GlycanLexer, "MOD"):
+    GlycanLexer.MOD = GlycanLexer.QMARK + 1
+
 
 class MonomerFactory:
     """

glyles/glycans/factory/factory_o.py

@@ -204,7 +204,7 @@ def check_for_acid(start, structure, adjacency, a_type):
     Returns:
         bool flag indicating if the carbon atom has an acid group
     """
-    oxys = [int(x) for x in np.where((adjacency[start] != 0) & (a_type == 8))[0]]
+    oxys = [int(x) for x in np.where(np.array(adjacency[start] != 0) & (a_type == 8))[0]]
     if len(oxys) != 2:
         return False
     if (structure.GetBondBetweenAtoms(int(start), oxys[0]).GetBondType() == BondType.SINGLE and
@@ -216,7 +216,7 @@ def check_for_acid(start, structure, adjacency, a_type):
 
 
 def check_for_co_double(carbon, structure, adjacency, a_type):
-    oxys = [int(x) for x in np.where((adjacency[carbon] != 0) & (a_type == 8))[0]]
+    oxys = [int(x) for x in np.where(np.array(adjacency[carbon] != 0) & (a_type == 8))[0]]
     return sum(structure.GetBondBetweenAtoms(int(carbon), o).GetBondType() == BondType.DOUBLE for o in oxys) == 1
 
 
@@ -232,4 +232,4 @@ def check_for_aldehyd(start, adjacency, a_type):
     Returns:
         bool flag indicating if the carbon atom has an aldehyd group
     """
-    return len(np.where((adjacency[start] == 1) & (a_type == 8))[0]) != 0
+    return len(np.where(np.array(adjacency[start] == 1) & (a_type == 8))[0]) != 0

glyles/glycans/mono/enum_c.py

@@ -24,8 +24,8 @@ def enumerate_carbon(monomer):
 
     # then iterate over all those carbons and enumerate them beginning at C1
     for c_id in range(1, next_c_id):
-        c_index = int(np.where(monomer.x[:, 1] == c_id)[0])
-        candidates = np.where((monomer.adjacency[c_index, :] != 0) & (monomer.x[:, 1] == 0))[0]
+        c_index = np.where(monomer.x[:, 1] == c_id)[0].item()
+        candidates = np.where(np.array(monomer.adjacency[c_index, :] != 0) & (monomer.x[:, 1] == 0))[0]
         if candidates.size != 0:
             for candidate in list(candidates):
                 if sum(monomer.adjacency[candidate, :]) > 1:
@@ -51,7 +51,7 @@ def enumerate_side_chain(monomer, parent, atom, next_c_id):
         next_c_id += 1
 
     # identify children
-    candidates = np.where((monomer.adjacency[atom, :] != 0) & (monomer.x[:, 1] == 0))[0].tolist()
+    candidates = np.where(np.array(monomer.adjacency[atom, :] != 0) & (monomer.x[:, 1] == 0))[0].tolist()
     if parent in candidates:
         candidates.remove(parent)
 
@@ -85,10 +85,10 @@ def enumerate_c_atoms(monomer, c_atoms, ringo):
             stack = stack[:-1]
             c_tree.add_node(c_id, p_id)
 
-            children = np.where((monomer.adjacency[c_id, :] == 1) & (monomer.x[:, 0] == 6) & (monomer.x[:, 3] == 1))[0]
+            children = np.where(np.array(monomer.adjacency[c_id, :] == 1) & (monomer.x[:, 0] == 6) & (monomer.x[:, 3] == 1))[0]
             for c in children:
-                if int(c) not in c_tree.nodes:
-                    stack.append((c_id, int(c)))
+                if c.item() not in c_tree.nodes:
+                    stack.append((c_id, c.item()))
 
         # find the deepest node and rehang the tree to this node
         deepest_id, _ = c_tree.deepest_node()
@@ -100,14 +100,9 @@ def enumerate_c_atoms(monomer, c_atoms, ringo):
         start, end = longest_c_chain[0], longest_c_chain[-1]
 
         # check conditions
-        """start_o_conn, end_o_conn = \
-            np.argwhere((monomer.adjacency[start, :] == 1) & np.in1d(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1) &
-                        (monomer.x[:, 3] == 1)).squeeze().size > 0, \
-            np.argwhere((monomer.adjacency[end, :] == 1) & np.in1d(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1) &
-                        (monomer.x[:, 3] == 1)).squeeze().size > 0"""
-        start_o_conn = np.argwhere((monomer.adjacency[start, :] == 1) & np.in1d(monomer.x[:, 0], [7, 8]) &
+        start_o_conn = np.argwhere(np.array(monomer.adjacency[start, :] == 1) & np.isin(monomer.x[:, 0], [7, 8]) &
                                    (monomer.x[:, 2] != 1)).squeeze().size > 0
-        end_o_conn = np.argwhere((monomer.adjacency[end, :] == 1) & np.in1d(monomer.x[:, 0], [7, 8]) &
+        end_o_conn = np.argwhere(np.array(monomer.adjacency[end, :] == 1) & np.isin(monomer.x[:, 0], [7, 8]) &
                                  (monomer.x[:, 2] != 1)).squeeze().size > 0
 
         # decide on c1
@@ -168,19 +163,19 @@ def equidistant(monomer, start, end):
         Bool indicating that the start id is the C1 atom
     """
     # determine first carbon atom in the ring
-    c_start_candidates = np.where((monomer.adjacency[start, :] == 1) &
+    c_start_candidates = np.where(np.array(monomer.adjacency[start, :] == 1) &
                                   (monomer.x[:, 0] == 6) & (monomer.x[:, 2] & 0b1))[0]
-    c_end_candidates = np.where((monomer.adjacency[end, :] == 1) & (monomer.x[:, 0] == 6) & (monomer.x[:, 2] & 0b1))[0]
+    c_end_candidates = np.where(np.array(monomer.adjacency[end, :] == 1) & (monomer.x[:, 0] == 6) & (monomer.x[:, 2] & 0b1))[0]
 
     if c_start_candidates.size == 1 and c_end_candidates.size == 1:
-        start_ring_c = int(c_start_candidates)
-        end_ring_c = int(c_end_candidates)
+        start_ring_c = c_start_candidates.item()
+        end_ring_c = c_end_candidates.item()
 
         # check if those ring carbons have an attached oxygen
-        start_ring_c_o_candidates = np.where((monomer.adjacency[start_ring_c, :] == 1) &
-                                             np.in1d(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1))[0]
-        end_ring_c_o_candidates = np.where((monomer.adjacency[end_ring_c, :] == 1) &
-                                           np.in1d(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1))[0]
+        start_ring_c_o_candidates = np.where(np.array(monomer.adjacency[start_ring_c, :] == 1) &
+                                             np.isin(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1))[0]
+        end_ring_c_o_candidates = np.where(np.array(monomer.adjacency[end_ring_c, :] == 1) &
+                                           np.isin(monomer.x[:, 0], [7, 8]) & (monomer.x[:, 2] != 1))[0]
 
         if start_ring_c_o_candidates.size == 1 and end_ring_c_o_candidates.size == 1:
             raise UnreachableError("C1 atom cannot be detected")