python import numpy as np # 示例数据 data = np.array([1.0, 2.0, np.nan, np.inf]) # 替换NaN和Inf data_cleaned = np.where(np.isfinite(data), data, np.nan_to_num(data)) # 现在可以尝试安全地转换 # 注意:转换NaN到整数可能仍然需要特殊处理 #
(graphtype.convert_np_to_tensor(dataset.input_data[0])) pred = dataset.denormalize(graph.grid_node_feat.numpy()) pred = graph.grid_node_outputs_to_prediction(pred, dataset.targets_template) tgt = graph.grid_node_outputs_to_prediction(dataset.target_data[0], dataset.targets_template) pred ...
TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe' 求解决方法,已经尝试强制转换了,还是存在错误。 原因是调用 seaborn 的 sns.jointplot(x='murder', y='burglary', data=data,kind="reg") 中,加入 kind 的类型就会报错。 2020-04-04 更新 QwQ ...
v = ['93.89', '89.89', '87.17', '90.57', '88.92', '90.46']*30 ExpMovingAverage(v,10) TypeError: Cannot cast array data from dtype('float64') to dtype('<U32') according to the rule 'safe' and ExpMovingAverage(list(map(float,v)),10) array([89.6938941 , 89.6938941 , 89.6938941...
iaa.Sequential(children=None,# Augmenter集合random_order=False,# 是否对每个batch使用不同顺序的Augmenter listname=None, deterministic=False, random_state=None)# 构建处理序列aug_seq = iaa.Sequential([ iaa.Affine(rotate=(-25,25)), iaa.AdditiveGaussianNoise(scale=(10,60)), ...
bytearray(b'ayz') 將1D/bytes 轉換為 3D/ints 轉換為 1D/signed char: >>>importstruct>>>buf = struct.pack("i"*12, *list(range(12)))>>>x = memoryview(buf)>>>y = x.cast('i', shape=[2,2,3])>>>y.tolist() [[[0,1,2], [3,4,5]], [[6,7,8], [9,10,11]]]>>...
这是从https://google-deepmind/graphcast复现的项目。由https://github.com/sfsun67改写和调试。 AutoDL 是国内的一家云计算平台,网址是https://www.autodl.com 应该有类似的文件结构,这里的数据由 Google Cloud Bucket (https://console.cloud.google.com/storage/browser/dm_graphcast提供。模型权重、标准化统...
(collection_name=collection_name, schema=schema, index_params=index_params) >>> >>> client.list_indexes(collection_name) ['my_vector', 'json_index'] >>> >>> >>> client.describe_index(collection_name, "json_index") {'json_cast_type': 'invalid', 'json_path': "my_json['a']['b...
nb_samples += inputs_length# 将标签添加到 arr_labels 列表中arr_labels += labels.squeeze(1).data.cpu().numpy().tolist()# 将 inputs 和 labels 转换为 float 类型inputs = inputs.float() labels = labels.float()# 如果 CUDA 可用,则将 inputs 和 labels 移动到 GPU 上iftorch.cuda.is_av...
List[int], tstep: int = 1, n_tsteps: int = 1, patch_size: int = None, n_samples_per_year: int = None, stats_dir: str = None, **kwargs, ): self.data_dir = Path(to_absolute_path(data_dir)) self.chans = chans self...