Update demo notebooks

duytnguyendtn · May 31, 2023 · cc513b3 · cc513b3
1 parent a937636
commit cc513b3
Show file tree

Hide file tree

Showing 3 changed files with 45 additions and 84 deletions.
diff --git a/notebooks/CubevizExample.ipynb b/notebooks/CubevizExample.ipynb
@@ -29,14 +29,7 @@
  "from photutils.aperture import CircularAperture\n",
  "from regions import PixCoord, CirclePixelRegion\n",
  "\n",
- "from jdaviz import Cubeviz"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We create a Cubeviz instance and show it."
+ "import jdaviz"
  ]
  },
  {
@@ -80,9 +73,26 @@
  "fn = \"jw02732-o004_t004_miri_ch1-shortmediumlong_s3d.fits\"\n",
  "result = Observations.download_file(f\"mast:JWST/product/{fn}\", local_path=f'{data_dir}/{fn}')\n",
  "\n",
+ "with warnings.catch_warnings():\n",
+ " warnings.simplefilter('ignore')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we can ask Jdaviz to automatically load the data. Jdaviz will automatically detect Cubeviz as the most appropriate configuration"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
  "with warnings.catch_warnings():\n",
  " warnings.simplefilter('ignore')\n",
- " cubeviz.load_data(f'{data_dir}/{fn}')"
+ " cubeviz = jdaviz.open(f'{data_dir}/{fn}')"
  ]
  },
  {
@@ -225,7 +235,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.10.8"
+ "version": "3.10.10"
  }
  },
  "nbformat": 4,

diff --git a/notebooks/Specviz2dExample.ipynb b/notebooks/Specviz2dExample.ipynb
@@ -28,27 +28,7 @@
  "\n",
  "from astroquery.mast import Observations\n",
  "\n",
- "from jdaviz import Specviz2d\n",
- "\n",
- "specviz2d = Specviz2d()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "0ed07713",
- "metadata": {},
- "source": [
- "## Display Specviz2d"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "45802673",
- "metadata": {},
- "outputs": [],
- "source": [
- "specviz2d.show()"
+ "import jdaviz"
  ]
  },
  {
@@ -94,7 +74,7 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "specviz2d.load_data(f'{data_dir}/{fn}')"
+ "jdaviz.open(f'{data_dir}/{fn}')"
  ]
  }
  ],
@@ -114,7 +94,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.10.6"
+ "version": "3.10.10"
  }
  },
  "nbformat": 4,

diff --git a/notebooks/SpecvizExample.ipynb b/notebooks/SpecvizExample.ipynb
@@ -26,60 +26,16 @@
  "\n",
  "# Suppress warnings\n",
  "with warnings.catch_warnings():\n",
- " warnings.simplefilter(\"ignore\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Create Specviz via Helper"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "tags": []
- },
- "outputs": [],
- "source": [
- "from jdaviz import Specviz\n",
- "specviz = Specviz()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Display Specviz\n",
+ " warnings.simplefilter(\"ignore\")\n",
  "\n",
- "Note: you probably want to pick one of the three options below depending on preference. Also not the latter two will only work in JupyterLab, not the \"classic\" notebook interface."
+ "import jdaviz"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "This will show Specviz inline in the notebook"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "tags": []
- },
- "outputs": [],
- "source": [
- "specviz.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Load a file to Specviz\n",
+ "## Download Data\n",
  "\n",
  "Here we download a JWST spectrum from [MAST](https://masttest.stsci.edu/) using `astroquery`. \n",
  "By default the downloaded file goes to your temp directory, and thus may eventually be \n",
@@ -106,9 +62,24 @@
  "#data_dir = \"/User/username/Data/\"\n",
  "\n",
  "fn = \"jw02732-o004_t004_miri_ch1-shortmediumlong_x1d.fits\"\n",
- "result = Observations.download_file(f\"mast:JWST/product/{fn}\", local_path=f'{data_dir}/{fn}')\n",
- "\n",
- "specviz.load_spectrum(f'{data_dir}/{fn}', \"myfile\")"
+ "result = Observations.download_file(f\"mast:JWST/product/{fn}\", local_path=f'{data_dir}/{fn}')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Open in Jdaviz\n",
+ "Jdaviz can automatically detect the correct configuration and load the data by using `jdaviz.open`. By default, jdaviz will display the application automatically. To only return the helper, set `show=False`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "specviz = jdaviz.open(f'{data_dir}/{fn}', show=True, data_label=\"myfile\")"
  ]
  },
  {
@@ -293,7 +264,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.9.16"
+ "version": "3.10.10"
  }
  },
  "nbformat": 4,