|
137 | 137 | "source": [ |
138 | 138 | "## Applying functions designed for `Dataset` with `map_over_datasets`\n", |
139 | 139 | "\n", |
140 | | - "What if we wanted to convert the data to log-space? For a `Dataset` or `DataArray`, we could just use {py:func}`xarray.ufuncs.log`, but that does not support `DataTree` objects, yet:" |
| 140 | + "What if we wanted to apply a element-wise function, for example to convert the data to log-space? For a `DataArray` we could just use {py:func}`numpy.log`, but this is not supported for `DataTree` objects:" |
141 | 141 | ] |
142 | 142 | }, |
143 | 143 | { |
144 | 144 | "cell_type": "code", |
145 | 145 | "execution_count": null, |
146 | 146 | "id": "12", |
147 | | - "metadata": {}, |
| 147 | + "metadata": { |
| 148 | + "tags": [ |
| 149 | + "raises-exception" |
| 150 | + ] |
| 151 | + }, |
148 | 152 | "outputs": [], |
149 | 153 | "source": [ |
150 | | - "xr.ufuncs.log(tree)" |
| 154 | + "np.log(tree)" |
151 | 155 | ] |
152 | 156 | }, |
153 | 157 | { |
154 | 158 | "cell_type": "markdown", |
155 | 159 | "id": "13", |
156 | 160 | "metadata": {}, |
157 | 161 | "source": [ |
158 | | - "Note how the result is a empty `Dataset`?\n", |
159 | | - "\n", |
160 | 162 | "To map a function to all nodes, we can use {py:func}`xarray.map_over_datasets` and {py:meth}`xarray.DataTree.map_over_datasets`: " |
161 | 163 | ] |
162 | 164 | }, |
|
203 | 205 | "id": "18", |
204 | 206 | "metadata": { |
205 | 207 | "tags": [ |
206 | | - "raises-exception", |
207 | | - "hide-output" |
| 208 | + "raises-exception" |
208 | 209 | ] |
209 | 210 | }, |
210 | 211 | "outputs": [], |
|
235 | 236 | "\n", |
236 | 237 | "tree.map_over_datasets(demean)" |
237 | 238 | ] |
| 239 | + }, |
| 240 | + { |
| 241 | + "cell_type": "markdown", |
| 242 | + "id": "21", |
| 243 | + "metadata": {}, |
| 244 | + "source": [ |
| 245 | + "## Escape hatches\n", |
| 246 | + "\n", |
| 247 | + "For some more complex operations, it might make sense to work on {py:class}`xarray.Dataset` or {py:class}`xarray.DataArray` objects and reassemble the tree afterwards.\n", |
| 248 | + "\n", |
| 249 | + "Let's look at a new dataset:" |
| 250 | + ] |
| 251 | + }, |
| 252 | + { |
| 253 | + "cell_type": "code", |
| 254 | + "execution_count": null, |
| 255 | + "id": "22", |
| 256 | + "metadata": {}, |
| 257 | + "outputs": [], |
| 258 | + "source": [ |
| 259 | + "precipitation = xr.tutorial.open_datatree(\"precipitation.nc4\").load()\n", |
| 260 | + "precipitation" |
| 261 | + ] |
| 262 | + }, |
| 263 | + { |
| 264 | + "cell_type": "markdown", |
| 265 | + "id": "23", |
| 266 | + "metadata": {}, |
| 267 | + "source": [ |
| 268 | + "Suppose we wanted to interpolate the observed precipitation to the modelled precipitation. We could use `map_over_datasets` for this, but we can also have a bit more control:" |
| 269 | + ] |
| 270 | + }, |
| 271 | + { |
| 272 | + "cell_type": "code", |
| 273 | + "execution_count": null, |
| 274 | + "id": "24", |
| 275 | + "metadata": {}, |
| 276 | + "outputs": [], |
| 277 | + "source": [ |
| 278 | + "interpolated = xr.DataTree.from_dict(\n", |
| 279 | + " {\n", |
| 280 | + " \"/\": precipitation.ds,\n", |
| 281 | + " \"/observed\": precipitation[\"/observed\"].ds.interp(\n", |
| 282 | + " lat=precipitation[\"/reanalysis/lat\"],\n", |
| 283 | + " lon=precipitation[\"/reanalysis/lon\"],\n", |
| 284 | + " ),\n", |
| 285 | + " \"/reanalysis\": precipitation[\"/reanalysis\"],\n", |
| 286 | + " }\n", |
| 287 | + ")\n", |
| 288 | + "interpolated" |
| 289 | + ] |
| 290 | + }, |
| 291 | + { |
| 292 | + "cell_type": "markdown", |
| 293 | + "id": "25", |
| 294 | + "metadata": {}, |
| 295 | + "source": [ |
| 296 | + "::::{admonition} Exercise\n", |
| 297 | + ":class: tip\n", |
| 298 | + "Compute the difference between total observed and modelled precipitation, and plot the result.\n", |
| 299 | + "\n", |
| 300 | + ":::{admonition} Solution\n", |
| 301 | + ":class: dropdown\n", |
| 302 | + "\n", |
| 303 | + "```python\n", |
| 304 | + "total = precipitation.sum(dim=[\"lon\", \"lat\"])\n", |
| 305 | + "difference = total[\"/observed/precipitation\"] - total[\"/reanalysis/precipitation\"]\n", |
| 306 | + "difference.plot()\n", |
| 307 | + "```\n", |
| 308 | + ":::\n", |
| 309 | + "::::\n" |
| 310 | + ] |
238 | 311 | } |
239 | 312 | ], |
240 | 313 | "metadata": { |
|
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