Moving parallel example to end of notebook, commenting out, and addin…

…g note about runtime.

content/notebooks/romanisim/romanisim.ipynb

@@ -328,6 +328,54 @@
  "source": [
  "If we want to simulate an L1 ramp cube, then we can change the level variable above to 1, which will also change the output file name to `*_uncal.asdf`. The rest of the information stays the same.\n",
  "\n",
+ "## Running Roman I-Sim with Shell Scripts\n",
+ "\n",
+ "You can also run Roman I-Sim tasks from the command line with executables and shell scripts. These are not easily accessible from a Jupyter notebook, but command line executables romanisim-make-image and romanisim-make-catalog (for making a catalog file from Gaia) exist. The scripts in the S3 bucket provide examples for how to use these. Let's look at one now:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s3_uri = 's3://roman-sci-test-data-prod-summer-beta-test/ROMANISIM/CATALOGS_SCRIPTS/make_ra0.47_dec0.51_pa0_l1_f129.sh'\n",
+ "fs = s3fs.S3FileSystem()\n",
+ "\n",
+ "with fs.open(s3_uri, 'rb') as f:\n",
+ " for line in f.readlines():\n",
+ " print(line.decode())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "For additional help with the executables, the -h option can be used to get the help text for the input arguments:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!romanisim-make-catalog -h"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!romanisim-make-image -h"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
  "### Advanced Use Case: Parallelized Simulations\n",
  "\n",
  "Often, we will want to run a simulation using multiple detectors rather than just one at a time. Looping over the above in a serial fashion can take quite a long time, so we want to parallelize the work. In the example below, we will show how to parallelize the procedure with the Python standard library `concurrent` module. Note that there are other, more sophisticated tools such as Dask that can achieve scalable results, and we may cover that in future tutorials."
@@ -393,29 +441,9 @@
  "source": [
  "We'll also need to allocate a number of threads to the pool. For this example, let's simulate two detectors at the same time, in this case WFI02 and WFI03 since we already simulated WFI01. This should be scalable based on the computational resources you have available on the RSP. \n",
  "\n",
- "**WARNING:** Please be cautious when parallelizing tasks such as Roman I-Sim as it can easily consume all of your RSP resources if handled incorrectly!"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "with ThreadPoolExecutor(2) as pool:\n",
- " futures = [pool.submit(run_romanisim, full_catalog, **{'sca': x}) for x in [2, 3]]\n",
- " wait(futures)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "After running this cell, you may notice that some of the log messages are a bit jumbled. That's because the two simulations are running asynchronously on different threads, so messages from both arrive back to the notebook at slightly different but overlapping times.\n",
+ "**WARNING:** Please be cautious when parallelizing tasks such as Roman I-Sim as it can easily consume all of your RSP resources if handled incorrectly!\n",
  "\n",
- "## Running Roman I-Sim with Shell Scripts\n",
- "\n",
- "You can also run Roman I-Sim tasks from the command line with executables and shell scripts. These are not easily accessible from a Jupyter notebook, but command line executables romanisim-make-image and romanisim-make-catalog (for making a catalog file from Gaia) exist. The scripts in the S3 bucket provide examples for how to use these. Let's look at one now:"
+ "We have commented out the lines below. If you want to run the parallelized simulation, uncomment all of the lines in the following code cell. **Note: this code cell will take a long time to run.**"
  ]
  },
  {
@@ -424,37 +452,16 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "s3_uri = 's3://roman-sci-test-data-prod-summer-beta-test/ROMANISIM/CATALOGS_SCRIPTS/make_ra0.47_dec0.51_pa0_l1_f129.sh'\n",
- "fs = s3fs.S3FileSystem()\n",
- "\n",
- "with fs.open(s3_uri, 'rb') as f:\n",
- " for line in f.readlines():\n",
- " print(line.decode())"
+ "#with ThreadPoolExecutor(2) as pool:\n",
+ "# futures = [pool.submit(run_romanisim, full_catalog, **{'sca': x}) for x in [2, 3]]\n",
+ "# wait(futures)"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "For additional help with the executables, the -h option can be used to get the help text for the input arguments:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!romanisim-make-catalog -h"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!romanisim-make-image -h"
+ "After running this cell, you may notice that some of the log messages are a bit jumbled. That's because the two simulations are running asynchronously on different threads, so messages from both arrive back to the notebook at slightly different but overlapping times."
  ]
  },
  {
@@ -477,7 +484,7 @@
  "source": [
  "## About this notebook\n",
  "**Author:** Sanjib Sharma, Tyler Desjardins \n",
- "**Updated On:** 2024-23-01"
+ "**Updated On:** 2024-09-27"
  ]
  },
  {
@@ -498,9 +505,9 @@
  ],
  "metadata": {
  "kernelspec": {
- "display_name": "Roman Calibration latest (2024-03-25)",
+ "display_name": "Python 3 (ipykernel)",
  "language": "python",
- "name": "roman-cal"
+ "name": "python3"
  },
  "language_info": {
  "codemirror_mode": {