{ "cells": [ { "cell_type": "markdown", "id": "7619b911-e058-4c11-93d0-8aa1d73305b9", "metadata": {}, "source": [ "# GMRT conversion guide" ] }, { "cell_type": "code", "execution_count": 1, "id": "6304f081-3151-4813-a383-bc1e0d17983c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "XRADIO version 1.1.3 already installed.\n" ] } ], "source": [ "from importlib.metadata import version\n", "import os\n", "\n", "try:\n", " import xradio\n", "\n", " print(\"XRADIO version\", version(\"xradio\"), \"already installed.\")\n", "except ImportError as exc:\n", " print(f\"Could not import XRADIO: {exc}\")\n", " print(\"Installing XRADIO\")\n", "\n", " os.system(\"pip install xradio\")\n", "\n", " import xradio\n", "\n", " print(\"xradio version\", version(\"xradio\"), \" installed.\")" ] }, { "cell_type": "markdown", "id": "611036ee-e72f-4b15-865d-94be871e15bf", "metadata": {}, "source": [ "## Download dataset" ] }, { "cell_type": "code", "execution_count": 2, "id": "1fb89a45-a951-41c9-bbaf-75f50a6e8fea", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[\u001b[38;2;128;05;128m2026-04-20 15:18:03,597\u001b[0m] \u001b[38;2;50;50;205m INFO\u001b[0m\u001b[38;2;112;128;144m toolviper: \u001b[0m Initializing download... \n", "[\u001b[38;2;128;05;128m2026-04-20 15:18:03,598\u001b[0m] \u001b[38;2;50;50;205m INFO\u001b[0m\u001b[38;2;112;128;144m toolviper: \u001b[0m File already exists: /Users/vdesouza/work/xradio/docs/source/measurement_set/guides/gmrt.ms \n" ] } ], "source": [ "import toolviper\n", "import os\n", "from pathlib import Path\n", "file_path_os = \"gmrt.ms\"\n", "\n", "toolviper.utils.data.download(file=\"gmrt.ms\")" ] }, { "cell_type": "markdown", "id": "57ddd4f9-af5d-4b6b-9355-b60bf9b61d21", "metadata": {}, "source": [ "## Convert to Processing Set" ] }, { "cell_type": "code", "execution_count": 3, "id": "87431f1b-b94d-442a-88b4-936f74be530c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[\u001b[38;2;128;05;128m2026-04-20 15:18:03,897\u001b[0m] \u001b[38;2;50;50;205m INFO\u001b[0m\u001b[38;2;112;128;144m toolviper: \u001b[0m Updated partition scheme used: ['DATA_DESC_ID', 'OBSERVATION_ID'] \n", "[\u001b[38;2;128;05;128m2026-04-20 15:18:03,898\u001b[0m] \u001b[38;2;50;50;205m INFO\u001b[0m\u001b[38;2;112;128;144m toolviper: \u001b[0m Number of partitions: 1 \n", "[\u001b[38;2;128;05;128m2026-04-20 15:18:03,898\u001b[0m] \u001b[38;2;50;50;205m INFO\u001b[0m\u001b[38;2;112;128;144m toolviper: \u001b[0m OBSERVATION_ID [0], DDI [0], STATE [None], FIELD [3], SCAN [7], EPHEMERIS [None] \n" ] } ], "source": [ "from xradio.measurement_set import convert_msv2_to_processing_set\n", "\n", "ms_file = \"gmrt.ms\"\n", "main_chunksize = {\"frequency\": 1, \"time\": 20} # baseline, polarization\n", "outfile = \"gmrt.ps.zarr\"\n", "convert_msv2_to_processing_set(\n", " in_file=ms_file,\n", " out_file=outfile,\n", " parallel_mode=\"none\",\n", " persistence_mode='w',\n", " main_chunksize=main_chunksize,\n", ")" ] }, { "cell_type": "markdown", "id": "b2f1eab6-f0d1-48a0-b10a-3a4290d41a2b", "metadata": {}, "source": [ "## Processing Set" ] }, { "cell_type": "code", "execution_count": 4, "id": "bb4686bf-f333-48ff-b509-ef0f58f0a3f7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namescan_intentsshapeexecution_block_UIDpolarizationscan_namespw_namespw_intentsfield_namesource_nameline_namefield_coordssession_reference_UIDscheduling_block_UIDproject_UIDstart_frequencyend_frequency
0gmrt_0[None](2, 435, 64, 4)---[RR, RL, LR, LL][7]spw_0[UNSPECIFIED][3C286_3][3C286_3][][fk5, 13h31m08.28s, 30d30m32.90s]------551562500.0748437500.0
\n", "
" ], "text/plain": [ " name scan_intents shape execution_block_UID polarization \\\n", "0 gmrt_0 [None] (2, 435, 64, 4) --- [RR, RL, LR, LL] \n", "\n", " scan_name spw_name spw_intents field_name source_name line_name \\\n", "0 [7] spw_0 [UNSPECIFIED] [3C286_3] [3C286_3] [] \n", "\n", " field_coords session_reference_UID \\\n", "0 [fk5, 13h31m08.28s, 30d30m32.90s] --- \n", "\n", " scheduling_block_UID project_UID start_frequency end_frequency \n", "0 --- 551562500.0 748437500.0 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from xradio.measurement_set import open_processing_set\n", "\n", "ps_xdt = open_processing_set(ps_store=outfile)\n", "ps_xdt.xr_ps.summary()" ] }, { "cell_type": "code", "execution_count": 5, "id": "e62a02df-c6d7-4b0e-bf2b-c4c387725359", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ps_xdt.xr_ps.plot_antenna_positions_2d()" ] }, { "cell_type": "code", "execution_count": 6, "id": "dcab23b8-0111-4443-a62a-b117692dded7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ps_xdt.xr_ps.plot_phase_centers()" ] }, { "cell_type": "markdown", "id": "e3077b15-b943-4e73-bac0-0ed5c325a06e", "metadata": {}, "source": [ "## Measurement Sets" ] }, { "cell_type": "markdown", "id": "bcf987eb-8a99-4e50-84c1-708b9ba70bf9", "metadata": {}, "source": [ "### Visibility dataset" ] }, { "cell_type": "code", "execution_count": 7, "id": "89e1faeb-dfe3-44ea-9abc-a7cde1c096ba", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataTree 'gmrt_0'>\n",
       "Group: /gmrt_0\n",
       "│   Dimensions:                     (time: 2, baseline_id: 435, frequency: 64,\n",
       "│                                    polarization: 4, uvw_label: 3)\n",
       "│   Coordinates:\n",
       "│     * time                        (time) float64 16B 1.72e+09 1.72e+09\n",
       "│       field_name                  (time) <U27 216B dask.array<chunksize=(2,), meta=np.ndarray>\n",
       "│       scan_name                   (time) <U21 168B dask.array<chunksize=(2,), meta=np.ndarray>\n",
       "│     * baseline_id                 (baseline_id) int64 3kB 0 1 2 3 ... 432 433 434\n",
       "│       baseline_antenna1_name      (baseline_id) <U3 5kB dask.array<chunksize=(435,), meta=np.ndarray>\n",
       "│       baseline_antenna2_name      (baseline_id) <U3 5kB dask.array<chunksize=(435,), meta=np.ndarray>\n",
       "│     * frequency                   (frequency) float64 512B 5.516e+08 ... 7.484e+08\n",
       "│     * polarization                (polarization) <U2 32B 'RR' 'RL' 'LR' 'LL'\n",
       "│     * uvw_label                   (uvw_label) <U1 12B 'u' 'v' 'w'\n",
       "│   Data variables:\n",
       "│       EFFECTIVE_INTEGRATION_TIME  (time, baseline_id) float64 7kB dask.array<chunksize=(2, 435), meta=np.ndarray>\n",
       "│       FLAG                        (time, baseline_id, frequency, polarization) bool 223kB dask.array<chunksize=(2, 435, 1, 4), meta=np.ndarray>\n",
       "│       TIME_CENTROID               (time, baseline_id) float64 7kB dask.array<chunksize=(2, 435), meta=np.ndarray>\n",
       "│       UVW                         (time, baseline_id, uvw_label) float64 21kB dask.array<chunksize=(2, 435, 3), meta=np.ndarray>\n",
       "│       VISIBILITY                  (time, baseline_id, frequency, polarization) complex64 2MB dask.array<chunksize=(2, 435, 1, 4), meta=np.ndarray>\n",
       "│       WEIGHT                      (time, baseline_id, frequency, polarization) float32 891kB dask.array<chunksize=(2, 435, 1, 4), meta=np.ndarray>\n",
       "│   Attributes:\n",
       "│       creation_date:     2026-04-20T21:18:03.911368+00:00\n",
       "│       creator:           {'software_name': 'xradio', 'version': '1.1.3'}\n",
       "│       data_groups:       {'base': {'correlated_data': 'VISIBILITY', 'date': '20...\n",
       "│       observation_info:  {'observer': ['TEST_PM'], 'observing_log': '[]', 'proj...\n",
       "│       processor_info:    {'sub_type': '', 'type': ''}\n",
       "│       schema_version:    4.0.0\n",
       "│       type:              visibility\n",
       "├── Group: /gmrt_0/antenna_xds\n",
       "│       Dimensions:                 (antenna_name: 30, cartesian_pos_label: 3,\n",
       "│                                    receptor_label: 2)\n",
       "│       Coordinates:\n",
       "│         * antenna_name            (antenna_name) <U3 360B 'C00' 'C01' ... 'W05' 'W06'\n",
       "│           mount                   (antenna_name) <U6 720B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "│           station_name            (antenna_name) <U6 720B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "│           telescope_name          (antenna_name) <U4 480B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "│         * cartesian_pos_label     (cartesian_pos_label) <U1 12B 'x' 'y' 'z'\n",
       "│         * receptor_label          (receptor_label) <U5 40B 'pol_0' 'pol_1'\n",
       "│           polarization_type       (antenna_name, receptor_label) <U1 240B dask.array<chunksize=(30, 2), meta=np.ndarray>\n",
       "│       Data variables:\n",
       "│           ANTENNA_DISH_DIAMETER   (antenna_name) float64 240B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "│           ANTENNA_POSITION        (antenna_name, cartesian_pos_label) float64 720B dask.array<chunksize=(30, 3), meta=np.ndarray>\n",
       "│           ANTENNA_RECEPTOR_ANGLE  (antenna_name, receptor_label) float64 480B dask.array<chunksize=(30, 2), meta=np.ndarray>\n",
       "│       Attributes:\n",
       "│           overall_telescope_name:  GMRT\n",
       "│           relocatable_antennas:    False\n",
       "│           type:                    antenna\n",
       "└── Group: /gmrt_0/field_and_source_base_xds\n",
       "        Dimensions:                       (field_name: 1, sky_dir_label: 2,\n",
       "                                           line_label: 1)\n",
       "        Coordinates:\n",
       "          * field_name                    (field_name) <U27 108B '3C286_3'\n",
       "            source_name                   (field_name) <U27 108B dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "          * sky_dir_label                 (sky_dir_label) <U3 24B 'ra' 'dec'\n",
       "          * line_label                    (line_label) <U21 84B '0'\n",
       "            line_name                     (field_name, line_label) <U1 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "        Data variables:\n",
       "            FIELD_PHASE_CENTER_DIRECTION  (field_name, sky_dir_label) float64 16B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
       "            LINE_REST_FREQUENCY           (field_name, line_label) float64 8B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "            LINE_SYSTEMIC_VELOCITY        (field_name, line_label) float64 8B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "            SOURCE_DIRECTION              (field_name, sky_dir_label) float64 16B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
       "        Attributes:\n",
       "            type:     field_and_source
" ], "text/plain": [ "\n", "Group: /gmrt_0\n", "│ Dimensions: (time: 2, baseline_id: 435, frequency: 64,\n", "│ polarization: 4, uvw_label: 3)\n", "│ Coordinates:\n", "│ * time (time) float64 16B 1.72e+09 1.72e+09\n", "│ field_name (time) \n", "│ scan_name (time) \n", "│ * baseline_id (baseline_id) int64 3kB 0 1 2 3 ... 432 433 434\n", "│ baseline_antenna1_name (baseline_id) \n", "│ baseline_antenna2_name (baseline_id) \n", "│ * frequency (frequency) float64 512B 5.516e+08 ... 7.484e+08\n", "│ * polarization (polarization) \n", "│ FLAG (time, baseline_id, frequency, polarization) bool 223kB dask.array\n", "│ TIME_CENTROID (time, baseline_id) float64 7kB dask.array\n", "│ UVW (time, baseline_id, uvw_label) float64 21kB dask.array\n", "│ VISIBILITY (time, baseline_id, frequency, polarization) complex64 2MB dask.array\n", "│ WEIGHT (time, baseline_id, frequency, polarization) float32 891kB dask.array\n", "│ Attributes:\n", "│ creation_date: 2026-04-20T21:18:03.911368+00:00\n", "│ creator: {'software_name': 'xradio', 'version': '1.1.3'}\n", "│ data_groups: {'base': {'correlated_data': 'VISIBILITY', 'date': '20...\n", "│ observation_info: {'observer': ['TEST_PM'], 'observing_log': '[]', 'proj...\n", "│ processor_info: {'sub_type': '', 'type': ''}\n", "│ schema_version: 4.0.0\n", "│ type: visibility\n", "├── Group: /gmrt_0/antenna_xds\n", "│ Dimensions: (antenna_name: 30, cartesian_pos_label: 3,\n", "│ receptor_label: 2)\n", "│ Coordinates:\n", "│ * antenna_name (antenna_name) \n", "│ station_name (antenna_name) \n", "│ telescope_name (antenna_name) \n", "│ * cartesian_pos_label (cartesian_pos_label) \n", "│ Data variables:\n", "│ ANTENNA_DISH_DIAMETER (antenna_name) float64 240B dask.array\n", "│ ANTENNA_POSITION (antenna_name, cartesian_pos_label) float64 720B dask.array\n", "│ ANTENNA_RECEPTOR_ANGLE (antenna_name, receptor_label) float64 480B dask.array\n", "│ Attributes:\n", "│ overall_telescope_name: GMRT\n", "│ relocatable_antennas: False\n", "│ type: antenna\n", "└── Group: /gmrt_0/field_and_source_base_xds\n", " Dimensions: (field_name: 1, sky_dir_label: 2,\n", " line_label: 1)\n", " Coordinates:\n", " * field_name (field_name) \n", " * sky_dir_label (sky_dir_label) \n", " Data variables:\n", " FIELD_PHASE_CENTER_DIRECTION (field_name, sky_dir_label) float64 16B dask.array\n", " LINE_REST_FREQUENCY (field_name, line_label) float64 8B dask.array\n", " LINE_SYSTEMIC_VELOCITY (field_name, line_label) float64 8B dask.array\n", " SOURCE_DIRECTION (field_name, sky_dir_label) float64 16B dask.array\n", " Attributes:\n", " type: field_and_source" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ms_xdt = ps_xdt[\"gmrt_0\"]\n", "ms_xdt" ] }, { "cell_type": "code", "execution_count": 8, "id": "d4840aca-1900-4d2d-add1-6fbfccd3b1ff", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataArray 'frequency' (frequency: 64)> Size: 512B\n",
       "array([5.515625e+08, 5.546875e+08, 5.578125e+08, 5.609375e+08, 5.640625e+08,\n",
       "       5.671875e+08, 5.703125e+08, 5.734375e+08, 5.765625e+08, 5.796875e+08,\n",
       "       5.828125e+08, 5.859375e+08, 5.890625e+08, 5.921875e+08, 5.953125e+08,\n",
       "       5.984375e+08, 6.015625e+08, 6.046875e+08, 6.078125e+08, 6.109375e+08,\n",
       "       6.140625e+08, 6.171875e+08, 6.203125e+08, 6.234375e+08, 6.265625e+08,\n",
       "       6.296875e+08, 6.328125e+08, 6.359375e+08, 6.390625e+08, 6.421875e+08,\n",
       "       6.453125e+08, 6.484375e+08, 6.515625e+08, 6.546875e+08, 6.578125e+08,\n",
       "       6.609375e+08, 6.640625e+08, 6.671875e+08, 6.703125e+08, 6.734375e+08,\n",
       "       6.765625e+08, 6.796875e+08, 6.828125e+08, 6.859375e+08, 6.890625e+08,\n",
       "       6.921875e+08, 6.953125e+08, 6.984375e+08, 7.015625e+08, 7.046875e+08,\n",
       "       7.078125e+08, 7.109375e+08, 7.140625e+08, 7.171875e+08, 7.203125e+08,\n",
       "       7.234375e+08, 7.265625e+08, 7.296875e+08, 7.328125e+08, 7.359375e+08,\n",
       "       7.390625e+08, 7.421875e+08, 7.453125e+08, 7.484375e+08])\n",
       "Coordinates:\n",
       "  * frequency  (frequency) float64 512B 5.516e+08 5.547e+08 ... 7.484e+08\n",
       "Attributes:\n",
       "    channel_width:            {'attrs': {'type': 'quantity', 'units': 'Hz'}, ...\n",
       "    observer:                 TOPO\n",
       "    reference_frequency:      {'attrs': {'observer': 'TOPO', 'type': 'spectra...\n",
       "    spectral_window_intents:  ['UNSPECIFIED']\n",
       "    spectral_window_name:     spw_0\n",
       "    type:                     spectral_coord\n",
       "    units:                    Hz
" ], "text/plain": [ " Size: 512B\n", "array([5.515625e+08, 5.546875e+08, 5.578125e+08, 5.609375e+08, 5.640625e+08,\n", " 5.671875e+08, 5.703125e+08, 5.734375e+08, 5.765625e+08, 5.796875e+08,\n", " 5.828125e+08, 5.859375e+08, 5.890625e+08, 5.921875e+08, 5.953125e+08,\n", " 5.984375e+08, 6.015625e+08, 6.046875e+08, 6.078125e+08, 6.109375e+08,\n", " 6.140625e+08, 6.171875e+08, 6.203125e+08, 6.234375e+08, 6.265625e+08,\n", " 6.296875e+08, 6.328125e+08, 6.359375e+08, 6.390625e+08, 6.421875e+08,\n", " 6.453125e+08, 6.484375e+08, 6.515625e+08, 6.546875e+08, 6.578125e+08,\n", " 6.609375e+08, 6.640625e+08, 6.671875e+08, 6.703125e+08, 6.734375e+08,\n", " 6.765625e+08, 6.796875e+08, 6.828125e+08, 6.859375e+08, 6.890625e+08,\n", " 6.921875e+08, 6.953125e+08, 6.984375e+08, 7.015625e+08, 7.046875e+08,\n", " 7.078125e+08, 7.109375e+08, 7.140625e+08, 7.171875e+08, 7.203125e+08,\n", " 7.234375e+08, 7.265625e+08, 7.296875e+08, 7.328125e+08, 7.359375e+08,\n", " 7.390625e+08, 7.421875e+08, 7.453125e+08, 7.484375e+08])\n", "Coordinates:\n", " * frequency (frequency) float64 512B 5.516e+08 5.547e+08 ... 7.484e+08\n", "Attributes:\n", " channel_width: {'attrs': {'type': 'quantity', 'units': 'Hz'}, ...\n", " observer: TOPO\n", " reference_frequency: {'attrs': {'observer': 'TOPO', 'type': 'spectra...\n", " spectral_window_intents: ['UNSPECIFIED']\n", " spectral_window_name: spw_0\n", " type: spectral_coord\n", " units: Hz" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ms_xdt.coords[\"frequency\"]" ] }, { "cell_type": "markdown", "id": "41c7e6fd-d106-41ef-b6ab-1f823a26ef0c", "metadata": {}, "source": [ "### Antenna dataset" ] }, { "cell_type": "code", "execution_count": 9, "id": "0c65b8cd-f84c-40c6-a331-b3a83e585b55", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataTree 'antenna_xds'>\n",
       "Group: /gmrt_0/antenna_xds\n",
       "    Dimensions:                 (time: 2, baseline_id: 435, frequency: 64,\n",
       "                                 polarization: 4, uvw_label: 3, antenna_name: 30,\n",
       "                                 cartesian_pos_label: 3, receptor_label: 2)\n",
       "    Coordinates:\n",
       "      * antenna_name            (antenna_name) <U3 360B 'C00' 'C01' ... 'W05' 'W06'\n",
       "        mount                   (antenna_name) <U6 720B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "        station_name            (antenna_name) <U6 720B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "        telescope_name          (antenna_name) <U4 480B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "      * cartesian_pos_label     (cartesian_pos_label) <U1 12B 'x' 'y' 'z'\n",
       "      * receptor_label          (receptor_label) <U5 40B 'pol_0' 'pol_1'\n",
       "        polarization_type       (antenna_name, receptor_label) <U1 240B dask.array<chunksize=(30, 2), meta=np.ndarray>\n",
       "    Inherited coordinates:\n",
       "      * baseline_id             (baseline_id) int64 3kB 0 1 2 3 ... 431 432 433 434\n",
       "      * frequency               (frequency) float64 512B 5.516e+08 ... 7.484e+08\n",
       "      * polarization            (polarization) <U2 32B 'RR' 'RL' 'LR' 'LL'\n",
       "      * time                    (time) float64 16B 1.72e+09 1.72e+09\n",
       "      * uvw_label               (uvw_label) <U1 12B 'u' 'v' 'w'\n",
       "    Data variables:\n",
       "        ANTENNA_DISH_DIAMETER   (antenna_name) float64 240B dask.array<chunksize=(30,), meta=np.ndarray>\n",
       "        ANTENNA_POSITION        (antenna_name, cartesian_pos_label) float64 720B dask.array<chunksize=(30, 3), meta=np.ndarray>\n",
       "        ANTENNA_RECEPTOR_ANGLE  (antenna_name, receptor_label) float64 480B dask.array<chunksize=(30, 2), meta=np.ndarray>\n",
       "    Attributes:\n",
       "        overall_telescope_name:  GMRT\n",
       "        relocatable_antennas:    False\n",
       "        type:                    antenna
" ], "text/plain": [ "\n", "Group: /gmrt_0/antenna_xds\n", " Dimensions: (time: 2, baseline_id: 435, frequency: 64,\n", " polarization: 4, uvw_label: 3, antenna_name: 30,\n", " cartesian_pos_label: 3, receptor_label: 2)\n", " Coordinates:\n", " * antenna_name (antenna_name) \n", " station_name (antenna_name) \n", " telescope_name (antenna_name) \n", " * cartesian_pos_label (cartesian_pos_label) \n", " Inherited coordinates:\n", " * baseline_id (baseline_id) int64 3kB 0 1 2 3 ... 431 432 433 434\n", " * frequency (frequency) float64 512B 5.516e+08 ... 7.484e+08\n", " * polarization (polarization) \n", " ANTENNA_POSITION (antenna_name, cartesian_pos_label) float64 720B dask.array\n", " ANTENNA_RECEPTOR_ANGLE (antenna_name, receptor_label) float64 480B dask.array\n", " Attributes:\n", " overall_telescope_name: GMRT\n", " relocatable_antennas: False\n", " type: antenna" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ms_xdt.antenna_xds" ] }, { "cell_type": "markdown", "id": "f04c4344-c5d0-4308-a6c0-8ae4628f3064", "metadata": {}, "source": [ "### Field and source dataset" ] }, { "cell_type": "code", "execution_count": 10, "id": "5ace2bea-0588-4440-951f-723f3fa1af50", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DatasetView> Size: 4kB\n",
       "Dimensions:                       (field_name: 1, sky_dir_label: 2,\n",
       "                                   line_label: 1, baseline_id: 435,\n",
       "                                   frequency: 64, polarization: 4, time: 2,\n",
       "                                   uvw_label: 3)\n",
       "Coordinates:\n",
       "  * field_name                    (field_name) <U27 108B '3C286_3'\n",
       "    source_name                   (field_name) <U27 108B dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "  * sky_dir_label                 (sky_dir_label) <U3 24B 'ra' 'dec'\n",
       "  * line_label                    (line_label) <U21 84B '0'\n",
       "    line_name                     (field_name, line_label) <U1 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "  * baseline_id                   (baseline_id) int64 3kB 0 1 2 ... 432 433 434\n",
       "  * frequency                     (frequency) float64 512B 5.516e+08 ... 7.48...\n",
       "  * polarization                  (polarization) <U2 32B 'RR' 'RL' 'LR' 'LL'\n",
       "  * time                          (time) float64 16B 1.72e+09 1.72e+09\n",
       "  * uvw_label                     (uvw_label) <U1 12B 'u' 'v' 'w'\n",
       "Data variables:\n",
       "    FIELD_PHASE_CENTER_DIRECTION  (field_name, sky_dir_label) float64 16B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
       "    LINE_REST_FREQUENCY           (field_name, line_label) float64 8B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "    LINE_SYSTEMIC_VELOCITY        (field_name, line_label) float64 8B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "    SOURCE_DIRECTION              (field_name, sky_dir_label) float64 16B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
       "Attributes:\n",
       "    type:     field_and_source
" ], "text/plain": [ " Size: 4kB\n", "Dimensions: (field_name: 1, sky_dir_label: 2,\n", " line_label: 1, baseline_id: 435,\n", " frequency: 64, polarization: 4, time: 2,\n", " uvw_label: 3)\n", "Coordinates:\n", " * field_name (field_name) \n", " * sky_dir_label (sky_dir_label) \n", " * baseline_id (baseline_id) int64 3kB 0 1 2 ... 432 433 434\n", " * frequency (frequency) float64 512B 5.516e+08 ... 7.48...\n", " * polarization (polarization) \n", " LINE_REST_FREQUENCY (field_name, line_label) float64 8B dask.array\n", " LINE_SYSTEMIC_VELOCITY (field_name, line_label) float64 8B dask.array\n", " SOURCE_DIRECTION (field_name, sky_dir_label) float64 16B dask.array\n", "Attributes:\n", " type: field_and_source" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ms_xdt.xr_ms.get_field_and_source_xds()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 5 }