如何在Holoviews中使用HoloMap查看二维数组切片(Python 3.5.1)

Question

我最近发现 holoviews 并且 hv.Image 方法是 plt.image 的一个很好的替代方法。有一个非常酷的功能叫做 hv.HoloMap，它允许输入一个函数并在函数内调整参数以交互方式查看生成的二维数组。我尝试按照一些启动 HoloMap 对象和替代 dynamicMap 对象的示例进行操作，但无法使其与我的数据一起使用。 (http://holoviews.org/Tutorials/Showcase.html)

在我的真实数据集中，我将拥有 3D 数组，并且我想沿着一个轴（在本例中为 z）进行切片，我可以在其中以交互方式查看生成的切片。我在下面用 numpy 和 xarray 做了一个基本示例：

如何使用我的 hv.HoloMap（或 hv.dynamicMap）对象构建我的基本函数 image_slice（遍历 z 维度）查看我的 3D DataArray 的 2D 切片？

import xarray as xr
import numpy as np
import holoviews as hv; hv.notebook_extension()


#Building 2D Array (X & Y)
dist = np.linspace(-0.5,0.5,202)   # Linear spatial sampling
XY,YX = np.meshgrid(dist, dist)

#Add along 3rd Dimension
Z_list = []
for i in range(10):
    Z_list.append(xr.DataArray(XY*i,dims=["x","y"]))

#Concat list of 2D Arrays into a 3D Array
DA_3D = xr.concat(Z_list,dim="z")
# DA_3D.shape 
# (10, 202, 202)

def image_slice(DA_var,k):
    return(hv.Image(DA_var[k,:,:].values))

#http://holoviews.org/Tutorials/Showcase.html Interactive Exploration w/ Circular Wave example
keys = [(DA_3D,k) for k in range(10)] #Every combination
items = [(k, image_slice(*k)) for k in keys] 
# visual_slice = hv.HoloMap(items)
# TypeError: unhashable type: 'DataArray


dmap = hv.DynamicMap(slice_image, kdims=[hv.Dimension('z_axis',range=(0, 10))])
# dmap
# TypeError: slice_image() missing 1 required positional argument: 'k'
# Which makes perfect sense because the first argument is the DataArray object but I don't know how to input that into this type of object since `hv.Dimension` requires a range

我用Python 3.5.1和Holoviews Version((1, 4, 3),

Answer 1

首先感谢您的关注，我是 HoloViews 的作者之一。了解 HoloMap 和 DynamicMap.

之间的区别很重要

HoloMap 很像一本字典，您用（键，值）对填充它，然后您可以使用小部件探索该数据的可视化。 DynamicMap 在您构造它时不包含任何项目，而是定义一个回调函数，当小部件（或您）请求特定键时该回调函数会被评估。这意味着您可以在动态维度上定义连续范围或离散样本列表，让您探索比 HoloMap 更大的空间。

以你的例子为例，你可以通过以下方式构建HoloMap和DynamicMap：

import xarray as xr
import numpy as np
import holoviews as hv; 
hv.notebook_extension()

#Building 2D Array (X & Y)
dist = np.linspace(-0.5,0.5,202)   # Linear spatial sampling
XY,YX = np.meshgrid(dist, dist)

#Add along 3rd Dimension
Z_list = []
for i in range(10):
    Z_list.append(xr.DataArray(XY*i,dims=["x","y"]))

#Concat list of 2D Arrays into a 3D Array
DA_3D = xr.concat(Z_list,dim="z")
# DA_3D.shape 
# (10, 202, 202)

def image_slice(k):
    return(hv.Image(DA_3D[k,:,:].values))

keys = list(range(10))

# Construct a HoloMap by evaluating the function over all the keys
hmap = hv.HoloMap([(k, image_slice(k)) for k in keys], kdims=['z_axis'])

# Construct a DynamicMap by defining the sampling on the Dimension
dmap = hv.DynamicMap(image_slice, kdims=[hv.Dimension('z_axis', values=keys)])

如果您还有其他问题，可以加入我们 Gitter。请注意，我们正计划将 xarray 与 HoloViews 正确集成，因此您无需手动定义 HoloMap/DynamicMap 来探索多维数组。

如何在Holoviews中使用HoloMap查看二维数组切片(Python 3.5.1)

How to use HoloMap in Holoviews to view 2D Array slices (Python 3.5.1)

python

arrays

image

numpy

holoviews