如何使用虹膜模块绘制大气的垂直剖面以及地形? [英] How to plot a vertical section of the atmosphere along with the topography using the Iris module?
问题描述
我有一个netcdf，其风速处于模型级别.在同一netcdf上，我具有每个模型级别的高度.我将netcdf转换为一个立方体，因此每个级别的高度都变成了辅助坐标.我想绘制一个横截面(经度x经度)，并希望模型级别遵循地形.我尝试使用Iris模块文档示例( https://scitools.org.uk/iris/docs/latest/examples/General/cross_section.html )，但无法正常工作.
I have a netcdf with wind speed at model levels. On the same netcdf I have the altitude of each model level. I converted netcdf to a cube, so the altitude of each level became an auxiliary coordinate. I would like to plot a cross section (longitude x longitude) and would like the model levels to follow the topography. I tried using the Iris module documentation example (https://scitools.org.uk/iris/docs/latest/examples/General/cross_section.html), but it's not working.
由于我已经掌握了每个海平面相对于海平面的高度，因此我只需要切成垂直部分并进行绘图即可.我尝试遵循该文档示例，但它返回一个错误:ValueError:形状不匹配:无法将对象广播为单个形状
As I already have the altitude of each level relative to sea level I just need to slice into vertical sections and plot. I tried to follow the documentation example, but it is returning an error: ValueError: shape mismatch: objects cannot be broadcast to a single shape
下面是Xarray.Dataset:
Bellow is the Xarray.Dataset:
<xarray.Dataset>
Dimensions: (latitude: 49, level: 21, longitude: 49)
Coordinates:
* longitude (longitude) float32 -52.0 -51.75 -51.5 ... -40.5 -40.25 -40.0
* latitude (latitude) float32 -15.0 -15.25 -15.5 ... -26.5 -26.75 -27.0
* level (level) int32 1 2 3 4 5 6 7 8 9 10 ... 13 14 15 16 17 18 19 20 21
time datetime64[ns] 2017-01-01T10:00:00
altitude (level, latitude, longitude) float32 271.3289 ... 1142.3843
Data variables:
ws (level, latitude, longitude) float32 0.77094275 ... 14.978188
我将DataArray转换为名为ws_iris的多维数据集:
I converted the DataArray to a cube named ws_iris:
Ws (unknown) level latitude longitude
Shape 21 49 49
Dimension coordinates
level x - -
latitude - x -
longitude - - x
Auxiliary coordinates
altitude x x x
Scalar coordinates
time 2017-01-01 10:00:00
这是我的代码:
import iris
import iris.plot as iplt
import iris.quickplot as qplt
import xarray as xr
ws = xr.open_dataset('ws.nc')
ws_iris = ws.ws.to_iris()
cross_section = next(ws_iris.slices(['longitude', 'level']))
qplt.contourf(cross_section, coords=['longitude', 'altitude'], cmap='viridis', levels=10)
As you can see I followed the same steps as the documentation example (https://scitools.org.uk/iris/docs/latest/examples/General/cross_section.html)
当我绘制相对于模型级别的经度时，将绘制垂直截面:
When I plot the longitude relative to the model level the vertical section is plotted:
qplt.contourf (cross_section, coords = ['longitude', 'level'], cmap = 'viridis', levels = 10)
但是当我根据海拔绘图时:
But when I plot in relation to altitude:
qplt.contourf (cross_section, coords = ['longitude', 'altitude'], cmap = 'viridis', levels = 10)
我收到以下错误消息:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-35-c93b92f5c581> in <module>
----> 1 qplt.contourf(cross_section, coords=['longitude', 'altitude'], cmap='viridis', levels=10)
~\Anaconda3\lib\site-packages\iris\quickplot.py in contourf(cube, *args, **kwargs)
202 coords = kwargs.get('coords')
203 axes = kwargs.get('axes')
--> 204 result = iplt.contourf(cube, *args, **kwargs)
205 _label_with_points(cube, result, coords=coords, axes=axes)
206 return result
~\Anaconda3\lib\site-packages\iris\plot.py in contourf(cube, *args, **kwargs)
937 coords = kwargs.get('coords')
938 kwargs.setdefault('antialiased', True)
--> 939 result = _draw_2d_from_points('contourf', None, cube, *args, **kwargs)
940
941 # Matplotlib produces visible seams between anti-aliased polygons.
~\Anaconda3\lib\site-packages\iris\plot.py in _draw_2d_from_points(draw_method_name, arg_func, cube, *args, **kwargs)
516
517 u, v = plot_arrays
--> 518 u, v = _broadcast_2d(u, v)
519
520 axes = kwargs.pop('axes', None)
~\Anaconda3\lib\site-packages\iris\plot.py in _broadcast_2d(u, v)
234 u = np.atleast_2d(u)
235 v = np.atleast_2d(v.T).T
--> 236 u, v = np.broadcast_arrays(u, v)
237 return u, v
238
~\Anaconda3\lib\site-packages\numpy\lib\stride_tricks.py in broadcast_arrays(*args, **kwargs)
257 args = [np.array(_m, copy=False, subok=subok) for _m in args]
258
--> 259 shape = _broadcast_shape(*args)
260
261 if all(array.shape == shape for array in args):
~\Anaconda3\lib\site-packages\numpy\lib\stride_tricks.py in _broadcast_shape(*args)
191 # use the old-iterator because np.nditer does not handle size 0 arrays
192 # consistently
--> 193 b = np.broadcast(*args[:32])
194 # unfortunately, it cannot handle 32 or more arguments directly
195 for pos in range(32, len(args), 31):
ValueError: shape mismatch: objects cannot be broadcast to a single shape
有人可以帮助我确定我的代码有什么问题吗?
Can someone help me identify what is wrong with my code.
或者也许有人知道如何制作我想要的图形.
Or maybe someone knows how to make the graph I want otherwise.
非常感谢您.
推荐答案
我不熟悉虹膜，因此我想建议使用 xarray.Datatset 绘制横截面的另一种方法.
I am not familiar with iris so I want to suggest an alternative way to plot cross sections with xarray.Datatset.
Metpy提供了非常有用的功能.对于这个问题.
Metpy provides a very helpful function. for this issue.
https://unidata.github.io/MetPy/latest/api/generated/metpy.interpolate.cross_section.html
否则，您可以使用以下代码来切片数据:
Otherwise you can use following code to slice your datarray:
points_cross = geodesic(crs_data, start, end, steps)
data_sliced = data.interp({
x.name: xr.DataArray(points[:, 0], dims='index', attrs=x.attrs),
y.name: xr.DataArray(points[:, 1], dims='index', attrs=y.attrs)
}, method='linear')
data_sliced.coords['index'] = range(len(points))
使用
def geodesic(crs, start, end, steps):
r"""Construct a geodesic path between two points.
This function acts as a wrapper for the geodesic construction available in `pyproj`.
Parameters
----------
crs: `cartopy.crs`
Cartopy Coordinate Reference System to use for the output
start: (2, ) array_like
A latitude-longitude pair designating the start point of the geodesic (units are
degrees north and degrees east).
end: (2, ) array_like
A latitude-longitude pair designating the end point of the geodesic (units are degrees
north and degrees east).
steps: int, optional
The number of points along the geodesic between the start and the end point
(including the end points).
Returns
-------
`numpy.ndarray`
The list of x, y points in the given CRS of length `steps` along the geodesic.
See Also
--------
cross_section
"""
import cartopy.crs as ccrs
from pyproj import Geod
g = Geod(crs.proj4_init)
geodesic = np.concatenate([
np.array(start[::-1])[None],
np.array(g.npts(start[1], start[0], end[1], end[0], steps - 2)),
np.array(end[::-1])[None]
]).transpose()
points = crs.transform_points(ccrs.Geodetic(), *geodesic)[:, :2]
return points
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