diff --git a/data/fake_results/results.ecsv b/data/fake_results/results.ecsv new file mode 100644 index 000000000..ee41fa575 --- /dev/null +++ b/data/fake_results/results.ecsv @@ -0,0 +1,21 @@ +# %ECSV 1.0 +# --- +# datatype: +# - {name: trajectory_x, datatype: int64} +# - {name: trajectory_y, datatype: int64} +# - {name: trajectory_vx, datatype: float64} +# - {name: trajectory_vy, datatype: float64} +# - {name: obs_count, datatype: int64} +# - {name: flux, datatype: float64} +# - {name: likelihood, datatype: float64} +# - {name: stamp, datatype: string, subtype: 'float32[21,21]'} +# - {name: valid_indices, datatype: string, subtype: 'int64[9]'} +# - {name: psi_curve, datatype: string, subtype: 'float64[10]'} +# - {name: phi_curve, datatype: string, subtype: 'float64[10]'} +# - {name: all_stamps, datatype: string, subtype: 'float32[10,21,21]'} +# - {name: pred_ra, datatype: string, subtype: json} +# - {name: pred_dec, datatype: string, subtype: json} +# - {name: all_times, datatype: string, subtype: 'float64[10]'} +# schema: astropy-2.0 +trajectory_x trajectory_y trajectory_vx trajectory_vy obs_count flux likelihood stamp valid_indices psi_curve phi_curve all_stamps pred_ra pred_dec all_times +106 44 10.465370178222656 0.4760266840457916 9 822.6404418945312 243.40751873206497 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null null [57130.19921875,57130.2109375,57130.21875,57131.19921875,57131.2109375,57131.21875,57132.19921875,57132.2109375,57132.21875,57133.19921875] diff --git a/notebooks/KBMOD_Demo.ipynb b/notebooks/KBMOD_Demo.ipynb index fb4e918af..507372f48 100644 --- a/notebooks/KBMOD_Demo.ipynb +++ b/notebooks/KBMOD_Demo.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -18,7 +18,6 @@ "\n", "from pathlib import Path\n", "\n", - "from kbmod.fake_data_creator import *\n", "from kbmod.run_search import *\n", "from kbmod.search import *" ] @@ -45,17 +44,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['000000.fits', '000001.fits', '000002.fits', '000003.fits', '000004.fits', '000005.fits', '000006.fits', '000007.fits', '000008.fits', '000009.fits']\n" - ] - } - ], + "outputs": [], "source": [ "# Define the path for the data.\n", "im_filepath = \"../data/demo\"\n", @@ -64,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -78,64 +69,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Run KBMOD" + "# Run KBMOD\n", + "\n", + "The standard approach to running KBMOD is to perform a grid search over all starting pixels and a grid of velocities. The velocities are defined by steps in velocity space (in pixels per day) and angles. Let’s do a grid search with:\n", + "* 21 different velocity steps from 0 pixels per day and 20 pixels per day\n", + "* 11 different angles from 0.5 below the default angle (computed based on the ecliptic) to 0.5 above.\n", + "\n", + "We require objects to be found in at least 7 of the time steps." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------------------------------------\n", - "Loading Images\n", - "---------------------------------------\n", - "Loaded 10 images\n", - "Times set\n", - "Starting Search\n", - "---------------------------------------\n", - "Ecliptic Angle = 1.1901\n", - "Min. Search Angle = -0.5000\n", - "Max Search Angle = 0.5000\n", - "Min Velocity = 0.0000\n", - "Max Velocity = 20.0000\n", - "Using in-line GPU sigmaG filtering methods\n", - "sigmaG limits: [15,60]\n", - "sigmaG coeff: 0.7753\n", - "Search finished in 0.057s\n", - "---------------------------------------\n", - "Retrieving Results\n", - "---------------------------------------\n", - "Getting results...\n", - "---------------------------------------\n", - "Chunk Start = 0\n", - "Chunk Max Likelihood = 243.35\n", - "Chunk Min. Likelihood = -1.00\n", - "---------------------------------------\n", - "Extracted batch of 1343 results for total of 1343\n", - "Applying Clipped-sigmaG Filtering\n", - "sigmaG limits: [15,60]\n", - "sigmaG coeff: 0.7753\n", - "0.18s elapsed\n", - "Completed filtering.\n", - "---------------------------------------\n", - "---------------------------------------\n", - "Applying Stamp Filtering\n", - "---------------------------------------\n", - "Stamp filtering 1342 results\n", - "Keeping 588 results\n", - "0.02s elapsed\n", - "Clustering 588 results\n", - "---------------------------------------\n", - "Saving Results\n", - "---------------------------------------\n", - "Time taken for patch: 0.9508676528930664\n" - ] - } - ], + "outputs": [], "source": [ "results_suffix = \"DEMO\"\n", "\n", @@ -182,44 +129,89 @@ " # Override the ecliptic angle for the demo data since we\n", " # know the true angle in pixel space.\n", " \"average_angle\": 0.0,\n", + " \"result_filename\": \"./fake_results/results.ecsv\",\n", + " \"save_all_stamps\": True,\n", "}\n", "\n", "rs = SearchRunner()\n", - "rs.run_search_from_config(input_parameters)" + "results = rs.run_search_from_config(input_parameters)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Check that results were written." + "We then check that results were written to an output directory." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['results_DEMO.txt', 'lc_DEMO.txt', 'psi_DEMO.txt', 'phi_DEMO.txt', 'lc_index_DEMO.txt', 'times_DEMO.txt', 'filtered_likes_DEMO.txt', 'ps_DEMO.txt', 'all_ps_DEMO.npy']\n" - ] - } - ], + "outputs": [], "source": [ "if os.path.exists(res_filepath):\n", " files = os.listdir(res_filepath)\n", " print(files)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Analyzing Results\n", + "\n", + "The run function we used returns a `ResultList` containing the individual results of the run. We can perform basic actions on this data structure such as sorting it, extracting individual results, or performing additional filtering." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"Search found {results.num_results()} results.\")\n", + "\n", + "# Sorting one result doesn't do anything.\n", + "results.sort()\n", + "\n", + "# Output the trajectory.\n", + "best_result = results.results[0] \n", + "print(best_result.trajectory)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also plot the different curves for the result." + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axs = plt.subplots(3, 1)\n", + "axs[0].plot(results.all_times, best_result.psi_curve)\n", + "axs[0].set_title(\"Psi\")\n", + "\n", + "axs[1].plot(results.all_times, best_result.phi_curve)\n", + "axs[1].set_title(\"Psi\")\n", + "\n", + "axs[2].plot(results.all_times, best_result.likelihood_curve)\n", + "axs[2].set_title(\"Likelihood\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For additional analysis steps, please refer to the kbmod_analysis_demo notebook which uses the data generated by this notebook." + ] } ], "metadata": { diff --git a/notebooks/kbmod_analysis_demo.ipynb b/notebooks/kbmod_analysis_demo.ipynb index 3241f901f..e92d71e24 100644 --- a/notebooks/kbmod_analysis_demo.ipynb +++ b/notebooks/kbmod_analysis_demo.ipynb @@ -7,54 +7,9 @@ "# KBMod Analysis Demo" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To run an analysis of KBMOD's output you need the results files. For the purposes of this notebook you can use that fake result data (corresponding to the `data/demo` images) included in `data/fake_results/*_DEMO.txt`.\n", - "\n", - "If you would like to use real data, you can run KBMOD from start to finish you can use the following steps:\n", - "\n", - "1) Run `example_search.py` with the following settings:\n", - "\n", - " * **image_dir**: The directory with the images from a single field. If you do not have an example data set, you can use `fake_data_creator.py` to create one.\n", - "\n", - " * **results_dir**: The directory where you want to save the results\n", - "\n", - " * **results_suffix**: Suffix to add when saving results files. Setting this as `test` then files will be saved as \"..._test.txt\". Five results files would be saved:\n", - " * `lc_test.txt`: File with the light curves from results after going through Kalman Filter.\n", - " * `results_test.txt`: File with the x,y pixel locations, velocity, flux, likelihood, and number of unmasked observations of each result.\n", - " * `ps_test.txt`: File with the summed postage stamp for each result.\n", - " * `times_test.txt`: File with the MJD of each observation in the saved lightcurve.\n", - " * `filtered_likes_test.txt`: The recalculated likelihood values for each results after removing observations with the Kalman Filter.\n", - " * **time_file**: [Optional] Location of a file with each row containing (visit_num, visit_mjd) for observations in dataset.\n", - " \n", - "The command will be like the following:\n", - "\n", - "```\n", - "python3 example_search.py --image_dir image_dir --results_dir results_dir --results_suffix test --time_file image_times.dat\n", - "```\n", - "\n", - "2) Once you have the results you can use the steps in this notebook to create plots with postage stamps and lightcurves side-by-side for a final look by eye.\n", - " You will first have to update some variables to match the arguments you chose for example_search.py in step 3.\n", - " * Change results_dir to match `--results_dir option`.\n", - " * Change results_suffix to match `--results_suffix option`." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# Directory where output from kbmod search are located\n", - "results_dir = \"../data/fake_results/\"\n", - "results_suffix = \"DEMO\"" - ] - }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -70,32 +25,46 @@ { "cell_type": "markdown", "metadata": {}, + "source": [ + "To run an analysis of KBMOD's output you need results in the form of either a `ResultList` or saved files. For the purposes of this notebook you can use that fake result data (corresponding to the `data/demo` images) included in `data/fake_results/results.ecsv`. These results were generated by the KBMOD_Demo notebook." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, "source": [ "## Loading Results\n", "\n", - "We load all of the result data as a `ResultList` and extract the first row to use for later examples." + "We load all of the result data as a `ResultList` using the class's `read_table` function. We extract the first row to use for later examples." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded 1 results.\n" - ] - } - ], + "outputs": [], "source": [ - "results = load_result_list_from_files(results_dir, results_suffix)\n", + "results = ResultList.read_table(\"../data/fake_results/results.ecsv\")\n", "print(f\"Loaded {results.num_results()} results.\")\n", "\n", "row0 = results.results[0]" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that in previous versions (<=1.1) KBMOD saved output was also saved in a series of individual files such as `all_ps_DEMO.npy` and `phi_DEMO.txt`. You can still load these using the `load_result_list_from_files` function:\n", + "\n", + "```\n", + "results_dir = \"../data/fake_results/\"\n", + "results_suffix = \"DEMO\"\n", + "results = load_result_list_from_files(results_dir, results_suffix)\n", + "```" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -109,20 +78,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ResultsVisualizer.plot_single_stamp(row0.stamp)" ] @@ -131,25 +89,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "If we have multiple stamps from either all_stamps or from multiple trajectories, we can plot them in a grid." + "If we have multiple stamps from either all_stamps or from multiple trajectories, we can plot them in a grid. Here we use the per-time step stamps." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ResultsVisualizer.plot_stamps(row0.all_stamps, columns=5)" ] @@ -163,20 +110,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig1 = plt.figure(figsize=(10, 15))\n", "(ax1, ax2, ax3) = fig1.subplots(3, 1)\n", @@ -205,23 +141,19 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ResultsVisualizer.plot_result_row(row0)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/src/kbmod/result_list.py b/src/kbmod/result_list.py index cd4024e0b..779f4fbb6 100644 --- a/src/kbmod/result_list.py +++ b/src/kbmod/result_list.py @@ -911,7 +911,7 @@ def to_table(self, filtered_label=None, append_times=False): return Table(table_dict) - def write_table(self, filename, overwrite=True): + def write_table(self, filename, overwrite=True, keep_all_stamps=False): """Write the unfiltered results to a single (ecsv) file. Parameter @@ -920,11 +920,14 @@ def write_table(self, filename, overwrite=True): The name of the result file. overwrite : `bool` Overwrite the file if it already exists. + keep_all_stamps : `bool` + Keep individual stamps for each result and time step. + This is very expensive. """ table_version = self.to_table(append_times=True) - # Drop the all stamps column as this is often too large to write in a CSV entry. - table_version.remove_column("all_stamps") + if not keep_all_stamps: + table_version.remove_column("all_stamps") table_version.write(filename, overwrite=True) diff --git a/src/kbmod/run_search.py b/src/kbmod/run_search.py index 7dd4a33a9..eb71c3247 100644 --- a/src/kbmod/run_search.py +++ b/src/kbmod/run_search.py @@ -201,7 +201,7 @@ def run_search(self, config, stack): config_filename = os.path.join(config["res_filepath"], f"config_{config['output_suffix']}.yml") config.to_file(config_filename, overwrite=True) if config["result_filename"] is not None: - keep.write_table(config["result_filename"]) + keep.write_table(config["result_filename"], keep_all_stamps=config["save_all_stamps"]) full_timer.stop()