Ejemplos de generate_matrix en Python

Ejemplo n.º 1

def run():
    output = open(sys.argv[1], 'w')
    writer = DictWriter(output, fieldnames=['uid', 'data'])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        data = fetch_user_location_logs(uid, db)
        locations = merge_locations(data)
        matrix = generate_matrix(locations)
        semantic_data = fetch_semantic_data(list(matrix.keys()))
        semantic_dict = {}
        for row in semantic_data:
            semantic_dict[row['location']] = clean_tags(row['tags'], 5)
        tag_matrix = {}
        for location, proba in list(matrix.items()):
            tag_dict = semantic_dict[location]
            tag_weight = sum(v for v in list(tag_dict.values()))
            if tag_weight == 0:
                continue
            for tag, cnt in list(tag_dict.items()):
                tag_matrix.setdefault(tag, [0] * 48)
                for i in range(48):
                    tag_matrix[tag][i] += (proba[i] * cnt +
                                           0.001) / (tag_weight + 0.001)
        writer.writerow({'uid': uid, 'data': json.dumps(tag_matrix)})
    output.close()

Ejemplo n.º 2

Archivo: batch_tag_matrix.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def run():
    output = open(sys.argv[1], 'w')
    writer = DictWriter(output, fieldnames=['uid', 'data'])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        data = fetch_user_location_logs(uid, db)
        locations = merge_locations(data)
        matrix = generate_matrix(locations)
        semantic_data = fetch_semantic_data(list(matrix.keys()))
        semantic_dict = {}
        for row in semantic_data:
            semantic_dict[row['location']] = clean_tags(row['tags'], 5)
        tag_matrix = {}
        for location, proba in list(matrix.items()):
            tag_dict = semantic_dict[location]
            tag_weight = sum(v for v in list(tag_dict.values()))
            if tag_weight == 0:
                continue
            for tag, cnt in list(tag_dict.items()):
                tag_matrix.setdefault(tag, [0] * 48)
                for i in range(48):
                    tag_matrix[tag][i] += (proba[i] * cnt + 0.001) / (tag_weight + 0.001)
        writer.writerow({
            'uid': uid,
            'data': json.dumps(tag_matrix)
        })
    output.close()

Ejemplo n.º 3

Archivo: batch_business_matrix.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def run():
    output = open(sys.argv[1], 'w')
    writer = DictWriter(output, fieldnames=['uid', 'data'])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        locations = area_by_uid_stop(uid, db, get_business_logs)
        matrix = generate_matrix(locations)
        writer.writerow({'uid': uid, 'data': json.dumps(matrix)})
    output.close()

Ejemplo n.º 4

Archivo: batch_location_matrix.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def run():
    output = open(sys.argv[1], "w")
    writer = DictWriter(output, fieldnames=["uid", "data"])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        logs = fetch_user_location_logs(uid, db)
        locations = merge_locations(logs)
        matrix = generate_matrix(locations)
        writer.writerow({"uid": uid, "data": json.dumps(matrix)})
    output.close()

Ejemplo n.º 5

Archivo: batch_location_matrix.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def run():
    output = open(sys.argv[1], 'w')
    writer = DictWriter(output, fieldnames=['uid', 'data'])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        logs = fetch_user_location_logs(uid, db)
        locations = merge_locations(logs)
        matrix = generate_matrix(locations)
        writer.writerow({'uid': uid, 'data': json.dumps(matrix)})
    output.close()

Ejemplo n.º 6

Archivo: batch_business_matrix.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def run():
    output = open(sys.argv[1], 'w')
    writer = DictWriter(output, fieldnames=['uid', 'data'])
    writer.writeheader()
    db = DB(dbconfig)

    for uid in fetch_users(db):
        locations = area_by_uid_stop(uid, db, get_business_logs)
        matrix = generate_matrix(locations)
        writer.writerow({
            'uid': uid,
            'data': json.dumps(matrix)
        })
    output.close()

Ejemplo n.º 7

Archivo: periodic_probability_matrix_test.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

    def test_generate_matrix(self):
        data = [
            {
                "date": "01",
                "locations": [
                    {
                        "duration": 423.26666666666665,
                        "start_time": "20131201001835",
                        "end_time": "20131201072151",
                        "location": "116.21832 40.02880"
                    },
                    {
                        "duration": 513.2166666666667,
                        "start_time": "20131201095115",
                        "end_time": "20131201182428",
                        "location": "116.35075 39.92321"
                    },
                    {
                        "duration": 241.7,
                        "start_time": "20131201194838",
                        "end_time": "20131201235020",
                        "location": "116.21863 40.01969"
                    }
                ]
            },
            {
                "date": "02",
                "locations": [
                    {
                        "duration": 442.23333333333335,
                        "start_time": "20131202000048",
                        "end_time": "20131202072302",
                        "location": "116.21863 40.01969"
                    },
                    {
                        "duration": 602.3333333333334,
                        "start_time": "20131202091812",
                        "end_time": "20131202192032",
                        "location": "116.34819 39.92131"
                    }
                ]
            }
        ]

        expected = {'116.35075 39.92321': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], '116.34819 39.92131': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0], '116.21832 40.02880': [0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], '116.21863 40.01969': [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]}
        returned = ppm.generate_matrix(data)
        self.assertEqual(returned, expected)

Ejemplo n.º 8

Archivo: app.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def tag_proba_matrix(uid):
    locations = _location_by_uid_stop(uid)
    matrix = generate_matrix(locations)
    semantic_data = fetch_semantic_data(list(matrix.keys()))
    semantic_dict = {}
    for row in semantic_data:
        semantic_dict[row['location']] = clean_tags(row['tags'], 5)
    tag_matrix = {}
    for location, proba in list(matrix.items()):
        tag_dict = semantic_dict[location]
        tag_weight = sum(v for v in list(tag_dict.values()))
        if tag_weight == 0:
            continue
        for tag, cnt in list(tag_dict.items()):
            tag_matrix.setdefault(tag, [0] * 48)
            for i in range(48):
                tag_matrix[tag][i] += (proba[i] * cnt + 0.001) / (tag_weight + 0.001)

    return make_response(dumps(tag_matrix))

Ejemplo n.º 9

Archivo: app.py Proyecto: PKU-Dragon-Team/bmdv-py3

def tag_proba_matrix(uid):
    locations = _location_by_uid_stop(uid)
    matrix = generate_matrix(locations)
    semantic_data = fetch_semantic_data(list(matrix.keys()))
    semantic_dict = {}
    for row in semantic_data:
        semantic_dict[row['location']] = clean_tags(row['tags'], 5)
    tag_matrix = {}
    for location, proba in list(matrix.items()):
        tag_dict = semantic_dict[location]
        tag_weight = sum(v for v in list(tag_dict.values()))
        if tag_weight == 0:
            continue
        for tag, cnt in list(tag_dict.items()):
            tag_matrix.setdefault(tag, [0] * 48)
            for i in range(48):
                tag_matrix[tag][i] += (proba[i] * cnt + 0.001) / (tag_weight + 0.001)

    return make_response(dumps(tag_matrix))

Ejemplo n.º 10

Archivo: app.py Proyecto: PKU-Dragon-Team/bmdv-py3

def most_proba_locations_holiday(uid):
    locations = _location_by_uid_stop_holiday(uid)
    matrix = generate_matrix(locations)
    most_proba_locations = pretty_print_most_proba_locations(get_most_proba_locations(matrix))
    return make_response(dumps(most_proba_locations))

Ejemplo n.º 11

Archivo: app.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def most_proba_locations_holiday(uid):
    locations = _location_by_uid_stop_holiday(uid)
    matrix = generate_matrix(locations)
    most_proba_locations = pretty_print_most_proba_locations(get_most_proba_locations(matrix))
    return make_response(dumps(most_proba_locations))

Ejemplo n.º 12

Archivo: app.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def proba_matrix_workday(uid):
    locations = _location_by_uid_stop_workday(uid)
    return make_response(dumps(generate_matrix(locations)))

Ejemplo n.º 13

Archivo: app.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def district_proba_matrix(uid):
    locations = area_by_uid_stop(uid, area_func=fetch_uid_district_data)
    return make_response(dumps(generate_matrix(locations)))

Ejemplo n.º 14

Archivo: app.py Proyecto: helloWorldRankProgrammer/back-mobile-data-visualization

def semantic_proba_matrix(uid):
    locations = area_by_uid_stop(uid, area_func=fetch_uid_business_data)
    return make_response(dumps(generate_matrix(locations)))

Ejemplo n.º 15

Archivo: app.py Proyecto: PKU-Dragon-Team/bmdv-py3

def proba_matrix_workday(uid):
    locations = _location_by_uid_stop_workday(uid)
    return make_response(dumps(generate_matrix(locations)))

Ejemplo n.º 16

Archivo: app.py Proyecto: PKU-Dragon-Team/bmdv-py3

def district_proba_matrix(uid):
    locations = area_by_uid_stop(uid, area_func=fetch_uid_district_data)
    return make_response(dumps(generate_matrix(locations)))

Ejemplo n.º 17

Archivo: app.py Proyecto: PKU-Dragon-Team/bmdv-py3

def semantic_proba_matrix(uid):
    locations = area_by_uid_stop(uid, area_func=fetch_uid_business_data)
    return make_response(dumps(generate_matrix(locations)))