嘿家伙所以我试图在python中重写以下matlab代码:
repmat(points, 1, length(points)) - repmat(points', length(points),1);
points 是一个包含几个点的弧度值的数组.
上面的代码给我一个像这样的矩阵输出:
0 1 2 0 1 2 0 1 2
-1 0 1 -1 0 1 -1 0 1
-2 -1 0 -2 -1 0 -2 -1 0
0 1 2 0 1 2 0 1 2
-1 0 1 -1 0 1 -1 0 1
-2 -1 0 -2 -1 0 -2 -1 0
0 1 2 0 1 2 0 1 2
-1 0 1 -1 0 1 -1 …我正在尝试使用 docker 容器设置单个 Kafka 代理，并且我正在使用此处的图像。目标是在 docker 中运行 Kafka 代理，并从主机运行生产者/消费者。
在配置KAFKA_LISTENERS和KAFKA_ADVERTISED_LISTENERS属性时，我意识到如果以下配置到位，我将无法检索代理元数据
KAFKA_BROKER_ID: 0
KAFKA_INTER_BROKER_LISTENER_NAME: INTERNAL
KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: INTERNAL:PLAINTEXT,EXTERNAL:PLAINTEXT
# KAFKA_ADVERTISED_LISTENERS must be EQUAL or SUBSET of KAFKA_LISTENERS
KAFKA_LISTENERS: INTERNAL://kafka0:29092, EXTERNAL://localhost:9092
# INTERNAL://kafka0:29092 is specified because of the KAFKA_INTER_BROKER_LISTENER_NAME configuration.
KAFKA_ADVERTISED_LISTENERS: INTERNAL://kafka0:29092, EXTERNAL://localhost:9092
KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'false'
KAFKA_MESSAGE_MAX_BYTES: '200000'
> kafkacat -b localhost:9092 -L
ERROR: Failed to acquire metadata: Local: Broker transport failure
但是在配置中替换EXTERNAL://localhost:9092为EXTERNAL://kafka0:9092或EXTERNAL://:9092（默认接口）修复了它。KAFKA_LISTENERS
>kafkacat -b localhost:9092 -L
Metadata …我希望对几个时间戳（以分钟为单位）进行聚类。所以到目前为止我所做的是：
1) 将点转换为弧度
#points containing time value in minutes
points = [100, 200, 600, 659, 700]
def convert_to_radian(x):
return((x / (24 * 60)) * 2 * pi)
rad_function = np.vectorize(convert_to_radian)
points_rad = rad_function(points)
2) 生成距离矩阵
#generate distance matrix from each point
dist = points_rad[None,:] - points_rad[:, None]
3）分配每个点的最短距离
dist[((dist > pi) & (dist <= (2*pi)))] = dist[((dist > pi) & (dist <= (2*pi)))] -(2*pi)
dist[((dist > (-2*pi)) & (dist <= (-1*pi)))] = dist[((dist > (-2*pi)) & (dist <= (-1*pi)))] + …numpy ×2
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