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67
src/python/hierarchy
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67
src/python/hierarchy
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graph "Hierarchy Sars-Cov-2" {
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node [shape=plaintext]
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"Japan,Hong Kong" -- Japan
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"Japan,Hong Kong" -- "Hong Kong"
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"Japan,Hong Kong,Brazil" -- "Japan,Hong Kong"
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"Japan,Hong Kong,Brazil" -- Brazil
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"Japan,Hong Kong,Brazil,South Korea" -- "Japan,Hong Kong,Brazil"
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"Japan,Hong Kong,Brazil,South Korea" -- "South Korea"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan" -- "Japan,Hong Kong,Brazil,South Korea"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan" -- Pakistan
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam" -- "Japan,Hong Kong,Brazil,South Korea,Pakistan"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam" -- "Viet Nam"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden" -- "Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden" -- Sweden
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan" -- "Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden"
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"Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan" -- Taiwan
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"South Africa,Greece" -- "South Africa"
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"South Africa,Greece" -- Greece
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"Malaysia,Thailand" -- Malaysia
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"Malaysia,Thailand" -- Thailand
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan" -- "South Africa,Greece"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan" -- "Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland" -- Finland
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"Spain,Colombia" -- Spain
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"Spain,Colombia" -- Colombia
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France" -- France
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"India,Nepal" -- India
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"India,Nepal" -- Nepal
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey" -- Turkey
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel" -- Israel
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel"
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"South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown" -- Unknown
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"India,Nepal,Peru" -- "India,Nepal"
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"India,Nepal,Peru" -- Peru
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"India,Nepal,Peru,China" -- "India,Nepal,Peru"
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"India,Nepal,Peru,China" -- China
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown" -- "India,Nepal,Peru,China"
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown" -- "South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown"
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA" -- "India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown"
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA" -- USA
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia" -- "India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA"
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia" -- "Spain,Colombia"
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"Nigeria,Australia" -- Nigeria
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"Nigeria,Australia" -- Australia
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"Malaysia,Thailand,Italy" -- "Malaysia,Thailand"
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"Malaysia,Thailand,Italy" -- Italy
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"Malaysia,Thailand,Italy,Iran" -- "Malaysia,Thailand,Italy"
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"Malaysia,Thailand,Italy,Iran" -- Iran
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"Malaysia,Thailand,Italy,Iran,Philippines" -- "Malaysia,Thailand,Italy,Iran"
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"Malaysia,Thailand,Italy,Iran,Philippines" -- Philippines
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"Nigeria,Australia,Tunisia" -- "Nigeria,Australia"
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"Nigeria,Australia,Tunisia" -- Tunisia
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines" -- "Nigeria,Australia,Tunisia"
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines" -- "Malaysia,Thailand,Italy,Iran,Philippines"
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq" -- "Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines"
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq" -- Iraq
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia,Serbia" -- "India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia"
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"India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia,Serbia" -- Serbia
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq,Belgium" -- "Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq"
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq,Belgium" -- Belgium
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq,Belgium,India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia,Serbia" -- "Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq,Belgium"
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"Nigeria,Australia,Tunisia,Malaysia,Thailand,Italy,Iran,Philippines,Iraq,Belgium,India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia,Serbia" -- "India,Nepal,Peru,China,South Africa,Greece,Japan,Hong Kong,Brazil,South Korea,Pakistan,Viet Nam,Sweden,Taiwan,Finland,France,Turkey,Israel,Unknown,USA,Spain,Colombia,Serbia"
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}
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BIN
src/python/hierarchy.png
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BIN
src/python/hierarchy.png
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After Width: | Height: | Size: 292 KiB |
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@ -18,11 +18,12 @@ def main():
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csv_table = CsvTable(csv_path).group_countries_by_median_length()
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ids = csv_table.values('Accession')
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fasta_map = FastaMap(fasta_path).filter(lambda item: item[0] in ids)
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csv_table = csv_table.dict_by_id()
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print("Files processing finished!")
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labels = csv_table.dict_of('Accession', 'Geo_Location')
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print("\nBuilding hierarchy...")
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fasta_map.build_hierarchy(csv_table)
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fasta_map.build_hierarchy(labels)
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print("Done!")
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@ -49,6 +49,12 @@ class CsvTable:
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"""
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return [row[column] for row in self]
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def dict_of(self, key, value):
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try:
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return dict(zip(self.values(key), self.values(value)))
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except:
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print("KeyError")
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def group_countries_by_median_length(self):
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"""
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Filters the csv by country for average length's
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@ -72,9 +78,6 @@ class CsvTable:
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else "Unknown"
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return row
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def dict_by_id(self):
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return {elem["Accession"]: elem for elem in self._table}
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@staticmethod
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def __read(file_path: str) -> List[Dict]:
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"""
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@ -47,16 +47,14 @@ class FastaMap:
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"""
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return FastaMap(filter(function, self))
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def build_hierarchy(self, by_id=None) -> None:
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def build_hierarchy(self, labels):
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"""
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The function that is in charge of the comparison and the hierarchy of the samples
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:return None:
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"""
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if by_id is None:
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by_id = {}
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comparisons = self._compare_all_samples(by_id)
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comparisons = self._compare_all_samples()
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table = self._to_dict(comparisons)
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tree = HierarchyTree()
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tree = HierarchyTree(labels)
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while len(table) > 1:
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closest_pair = self.__find_closest_pair(table)
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@ -80,7 +78,7 @@ class FastaMap:
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data[rna_id] = rna if len(rna) < 1000 else rna[:1000]
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return data
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def _compare_all_samples(self, csv_table):
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def _compare_all_samples(self):
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# Calculate the number of threads that can be
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# used in order to speed up the comparisons
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max_length = max(map(len, self.__data.values()))
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@ -94,9 +92,6 @@ class FastaMap:
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for i in range(len(ids) - 1)
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for j in range(i + 1, len(ids))]
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comparisons = sq.par_compare(to_compare, self.__data, str(threads))
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if csv_table:
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comparisons = [(csv_table[id1]["Geo_Location"], csv_table[id2]["Geo_Location"], result)
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for id1, id2, result in comparisons]
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print(
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f"Comparisons performed in {time.time() - start_time:.3f} seconds!")
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return comparisons
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@ -2,15 +2,21 @@ from graphviz import Graph
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class HierarchyTree:
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def __init__(self):
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self.__dot = Graph("Hierarchy Sars-Cov-2", format='svg')
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def __init__(self, labels):
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self.__dot = Graph("Hierarchy Sars-Cov-2", format='png',
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node_attr={'shape': 'plaintext'})
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self.__labels = labels
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def add_relation(self, pair):
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node1, node2 = tuple(map(lambda x: str(x).translate(
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str.maketrans({'(': '', ')': '', "'": ''})), pair))
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new_node = f"{node1}, {node2}"
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self.__dot.edge(node1, new_node)
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self.__dot.edge(node2, new_node)
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node1, node2 = tuple(map(self.__transform, pair))
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new_node = f"{node1},{node2}"
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self.__dot.edge(new_node, node1)
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self.__dot.edge(new_node, node2)
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def show(self):
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self.__dot.render("hierarchy")
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def __transform(self, value):
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value = str(value).translate(
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str.maketrans({'(': '', ')': '', "'": ''}))
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return ','.join(map(lambda x: self.__labels[x.strip()], value.split(',')))
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