Merge branch 'main' of https://github.com/tahiri-lab/aPhyloGeo

aphylogeo/alignement.py

@@ -176,20 +176,20 @@ def align(self) -> Alignment:
             self.centroidSeq = self.sequences.pop(self.centroidKey)
             self.aligned = self.alignSequencesWithPairwise()
             if Params.fit_method == "1":
-                self.heuristicMSA = self.starAlignement()
+                heuristicMSA = self.starAlignement()
             elif Params.fit_method == "2":
-                self.heuristicMSA = self.narrowFitPairwise()
+                heuristicMSA = self.narrowFitPairwise()
 
         elif Params.alignment_method == "2":
-            self.heuristicMSA = self.muscleAlign()
+            heuristicMSA = self.muscleAlign()
         elif Params.alignment_method == "3":
-            self.heuristicMSA = self.clustalAlign()
+            heuristicMSA = self.clustalAlign()
         elif Params.alignment_method == "4":
-            self.heuristicMSA = self.mafftAlign()
+            heuristicMSA = self.mafftAlign()
         else:
             raise ValueError("Invalid alignment method")
         [os.remove(file) for file in glob.glob("bin/tmp/*.fasta")]  # Remove temp fasta files
-        self.windowed = self.slidingWindow()
+        self.windowed = self.slidingWindow(heuristicMSA)
         self.msa = self.makeMSA()
         self.alignment = Alignment(Params.alignment_method, self.msa)
         return self.alignment
@@ -707,7 +707,7 @@ def insertDash(self, dict, pos, keyList):
             dict[k] = s
         return dict
 
-    def slidingWindow(self, optimized=True):
+    def slidingWindow(self, heuristicMSA, optimized=True):
         """
         Method that slices all the sequences in a dictionary to a specific window (substring)
 
@@ -734,9 +734,9 @@ def slidingWindow(self, optimized=True):
         step = Params.window_size
 
         windowed_alignment = dict()
-        seq_len = max([len(h) for h in self.heuristicMSA.values()])
+        seq_len = max([len(h) for h in heuristicMSA.values()])
 
-        paddedMSA = {key: str(val).ljust(seq_len, "-") for key, val in self.heuristicMSA.items()}
+        paddedMSA = {key: str(val).ljust(seq_len, "-") for key, val in heuristicMSA.items()}
 
         if optimized:
             for i in range(0, seq_len, step):

aphylogeo/utils.py

@@ -178,58 +178,6 @@ def euclideanDist(tree1, tree2):
     return ed
 
 
-# G.M. Commented tree section out because it was not used
-# def drawTreesmake(trees, p):
-#     """
-#     Function that will draw the trees for each climatic variable.
-#     The DistanceTreeConstructor object is transformed to Newick format and
-#     loaded as a toytree MulTitree object. Some stylings are applied and the
-#     resulting trees are drawed into a .pdf in the viz/ dir.
-
-#     Args:
-#         trees (Dictionnary of DistanceTreeConstructor object with climatic
-#         variable for keys)
-#         p (Params object)
-
-#     """
-#     treesNewick = {}
-#     toytrees = []
-
-
-#     for k, v in trees.items():
-#         treesNewick[k] = v.format("newick")
-#         ttree = toytree.tree(treesNewick[k], tree_format=1)
-#         toytrees.append(ttree)
-#     mtree = toytree.mtree(toytrees)
-
-#     # Setting up the stylings for nodes
-#     for tree in mtree.treelist:
-#         tree.style.edge_align_style = {"stroke": "black", "stroke-width": 1}
-#         for node in tree.treenode.traverse():
-#             if node.is_leaf():
-#                 node.add_feature("color", toytree.colors[7])
-#             else:
-#                 node.add_feature("color", toytree.colors[1])
-#     colors = tree.get_node_values("color", show_root=1, show_tips=1)
-
-#     # Draw the climatic trees
-#     canvas, axes, mark = mtree.draw(
-#         nrows=round(len(mtree) / 5),
-#         ncols=len(mtree),
-#         height=400,
-#         width=1000,
-#         node_sizes=8,
-#         node_colors=colors,
-#         tip_labels_align=True,
-#     )
-
-#     for i in range(len(mtree)):
-#         randColor = "#%03x" % random.randint(0, 0xFFF)
-#         axes[i].text(0, mtree.ntips, p.names[i + 1], style={"fill": randColor, "font-size": "10px", "font-weight": "bold"})
-
-#     toyplot.pdf.render(canvas, "../viz/climactic_trees.pdf")
-
-
 def createTree(dm):
     """
     Create a dna tree from content coming from a fasta file.

tests/test_climatic.py

@@ -20,7 +20,7 @@ def climaticTreesSetup():
         climaticTrees (dict): A dictionary containing the climatic trees.
     """
     p = Params(os.path.join(os.path.dirname(__file__), "params_very_small.yaml"))
-    return utils.climaticPipeline(pd.read_csv(p.file_name), p.names)
+    return utils.climaticPipeline(pd.read_csv(p.file_name))
 
 
 def test_climaticPipeline():

tests/test_genetic.py

@@ -13,7 +13,6 @@
 
 current_file = os.path.dirname(__file__)
 
-
 class TestGenetic:
     def setup_class(self):
         """
@@ -37,7 +36,9 @@ def setup_class(self):
             params_very_small.bootstrapAmount,
             params_very_small.alignment_method,
             params_very_small.reference_gene_file,
-            params_very_small.distance_method,
+            params_very_small.fit_method,
+            params_very_small.rate_similarity,
+            params_very_small.method_similarity
         )
         very_small.align()
         self.alignementSetup = [very_small]  # , small]
@@ -50,10 +51,9 @@ def test_centroidKey(self):
 
         print("Begin test_centroidKey...")
 
-        for alignement, p in zip(self.alignementSetup, self.paramSetup):
-            test_case = p.reference_gene_filename[0:-6]
+        for alignement in self.alignementSetup:
             actual_centroid = alignement.centroidKey
-            filename = Path(current_file + "/testFiles/getSequenceCentroid/" + test_case)
+            filename = current_file + "/testFiles/getSequenceCentroid/seq very small"
 
             with open(filename, "r") as expected_file:
                 expected_centroid = expected_file.read()
@@ -66,7 +66,7 @@ def test_aligned(self):
 
         print("Begin test_aligned...")
 
-        for alignement, p in zip(self.alignementSetup, self.paramSetup):
+        for alignement in self.alignementSetup:
             aligned = alignement.aligned
 
             for key in aligned.keys():
@@ -80,8 +80,8 @@ def test_heuristicMSA(self):
 
         print("Begin test_heuristicMSA...")
 
-        for alignement, p in zip(self.alignementSetup, self.paramSetup):
-            starAlignement = alignement.heuristicMSA
+        for alignement in self.alignementSetup:
+            starAlignement = alignement.starAlignement()
             expected = AlignSequences.fileToDict(current_file + "/testFiles/starAlignement/seq very small", ".fasta")
             assert starAlignement == expected
 
@@ -92,7 +92,7 @@ def test_windowed(self):
 
         print("Begin test_windowed...")
 
-        for alignement, p in zip(self.alignementSetup, self.paramSetup):
+        for alignement in self.alignementSetup:
             windowed = alignement.windowed
 
             for key in windowed.keys():
@@ -106,7 +106,7 @@ def test_msaSet(self):
 
         print("Begin test_msaSet...")
 
-        for alignement, p in zip(self.alignementSetup, self.paramSetup):
+        for alignement in self.alignementSetup:
             msa = alignement.msa
 
             for key in msa.keys():