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Add easy import surface for std-compiling + SpecResults, and expose runtime __version__ #13

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Merged
Yong2Sheng merged 6 commits into from
Feb 27, 2026
Merged

Add easy import surface for std-compiling + SpecResults, and expose runtime __version__ #13

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6f34be0
simplify imports by reorganizing structures and using __init__ files.
Yong2Sheng Feb 27, 2026
acdb813
Update README.md for the editable installation of reserchcodes.
Yong2Sheng Feb 27, 2026
4be3c8e
Update smoke test file; chores: pre-commit auto fix.
Yong2Sheng Feb 27, 2026
960c002
Read the package version automatically from the metadata.
Yong2Sheng Feb 27, 2026
5d639fb
Remove unrelated comments.
Yong2Sheng Feb 27, 2026
64eb6b9
Fix smoke test failure in CI test.
Yong2Sheng Feb 27, 2026
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5 changes: 5 additions & 0 deletions .github/workflows/ci.yml
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Expand Up @@ -43,6 +43,11 @@ jobs:
- conda-forge
- defaults

- name: Install package (editable)
shell: micromamba-shell {0}
run: |
python -m pip install -e . --no-deps

- name: Run smoke tests
shell: micromamba-shell {0}
run: |
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3 changes: 2 additions & 1 deletion README.md
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Expand Up @@ -13,11 +13,12 @@ cd ResearchCodes

### 2) Create the conda environment from `environment.yml`

Create a fresh environment:
Create a fresh environment and install `researchcodes` in editable mode:

```bash
conda env create -f environment.yml
conda activate researchcodes
python -m pip install -e . --no-deps
```
Notes:
- `environment.yml` is the source of truth for dependencies.
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Binary file renamed ..._Standard_Star_Catalog/APASS/APASSDR10.h5 → ..._Standard_Star_Catalog/APASS/APASSDR10.h5
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94 changes: 49 additions & 45 deletions ...rd_Star_Catalog/APASS/Compile_APASS.ipynb → ...rd_Star_Catalog/APASS/Compile_APASS.ipynb
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Expand Up @@ -11,19 +11,11 @@
"source": [
"import sys\n",
"from pathlib import Path\n",
"\n",
"# set up the system path to import the \n",
"# compile_standard_catalog module \n",
"extra = Path(\"..\").resolve()\n",
"sys.path.insert(0, str(extra))\n",
"\n",
"from compile_standard_catalog import (\n",
"from researchcodes import (\n",
" define_column_desc, \n",
" iter_multi_csv_chunks, \n",
" write_std_h5, \n",
")\n",
"\n",
"\n"
")"
]
},
{
Expand All @@ -36,18 +28,29 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 12,
"id": "ded1390c-30c1-439a-a321-b0194e3591ff",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# define magnitude column names\n",
"# Define magnitude column names\n",
"\n",
"# Note this magnitude column order is not necessarily\n",
"# to be the same as the column order in the text file. \n",
"\n",
"# It is OK as long as the filter names in \n",
"# `magnitude_column_names` matches `colnames` defined \n",
"# when reading the text file\n",
"\n",
"magnitude_column_names = [\n",
" \"mag_B\",\"mag_V\",\"mag_u\",\"mag_g\",\"mag_r\",\"mag_i\",\"mag_PanSTARRS_zs\",\"mag_PanSTARRS_Y\",\n",
" # emag 8个\n",
" \"emag_B\",\"emag_V\",\"emag_u\",\"emag_g\",\"emag_r\",\"emag_i\",\"emag_PanSTARRS_zs\",\"emag_PanSTARRS_Y\",\n",
" \"Johnson_B\", \"Johnson_V\",\n",
" \"SDSS_up\", \"SDSS_gp\", \"SDSS_rp\", \"SDSS_ip\",\n",
" \"PanSTARRS_zs\",\"PanSTARRS_Y\",\n",
" \"Johnson_B_err\", \"Johnson_V_err\",\n",
" \"SDSS_up_err\", \"SDSS_gp_err\", \"SDSS_rp_err\", \"SDSS_ip_err\",\n",
" \"PanSTARRS_zs_err\",\"PanSTARRS_Y_err\",\n",
"]\n",
"\n",
"# define h5 file column description\n",
Expand All @@ -71,22 +74,22 @@
" 'ra_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=2),\n",
" 'dec': Float32Col(shape=(), dflt=np.float32(0.0), pos=3),\n",
" 'dec_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=4),\n",
" 'mag_B': Float32Col(shape=(), dflt=np.float32(0.0), pos=5),\n",
" 'mag_V': Float32Col(shape=(), dflt=np.float32(0.0), pos=6),\n",
" 'mag_u': Float32Col(shape=(), dflt=np.float32(0.0), pos=7),\n",
" 'mag_g': Float32Col(shape=(), dflt=np.float32(0.0), pos=8),\n",
" 'mag_r': Float32Col(shape=(), dflt=np.float32(0.0), pos=9),\n",
" 'mag_i': Float32Col(shape=(), dflt=np.float32(0.0), pos=10),\n",
" 'mag_PanSTARRS_zs': Float32Col(shape=(), dflt=np.float32(0.0), pos=11),\n",
" 'mag_PanSTARRS_Y': Float32Col(shape=(), dflt=np.float32(0.0), pos=12),\n",
" 'emag_B': Float32Col(shape=(), dflt=np.float32(0.0), pos=13),\n",
" 'emag_V': Float32Col(shape=(), dflt=np.float32(0.0), pos=14),\n",
" 'emag_u': Float32Col(shape=(), dflt=np.float32(0.0), pos=15),\n",
" 'emag_g': Float32Col(shape=(), dflt=np.float32(0.0), pos=16),\n",
" 'emag_r': Float32Col(shape=(), dflt=np.float32(0.0), pos=17),\n",
" 'emag_i': Float32Col(shape=(), dflt=np.float32(0.0), pos=18),\n",
" 'emag_PanSTARRS_zs': Float32Col(shape=(), dflt=np.float32(0.0), pos=19),\n",
" 'emag_PanSTARRS_Y': Float32Col(shape=(), dflt=np.float32(0.0), pos=20),\n",
" 'Johnson_B': Float32Col(shape=(), dflt=np.float32(0.0), pos=5),\n",
" 'Johnson_V': Float32Col(shape=(), dflt=np.float32(0.0), pos=6),\n",
" 'SDSS_up': Float32Col(shape=(), dflt=np.float32(0.0), pos=7),\n",
" 'SDSS_gp': Float32Col(shape=(), dflt=np.float32(0.0), pos=8),\n",
" 'SDSS_rp': Float32Col(shape=(), dflt=np.float32(0.0), pos=9),\n",
" 'SDSS_ip': Float32Col(shape=(), dflt=np.float32(0.0), pos=10),\n",
" 'PanSTARRS_zs': Float32Col(shape=(), dflt=np.float32(0.0), pos=11),\n",
" 'PanSTARRS_Y': Float32Col(shape=(), dflt=np.float32(0.0), pos=12),\n",
" 'Johnson_B_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=13),\n",
" 'Johnson_V_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=14),\n",
" 'SDSS_up_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=15),\n",
" 'SDSS_gp_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=16),\n",
" 'SDSS_rp_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=17),\n",
" 'SDSS_ip_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=18),\n",
" 'PanSTARRS_zs_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=19),\n",
" 'PanSTARRS_Y_err': Float32Col(shape=(), dflt=np.float32(0.0), pos=20),\n",
" 'ipix': Int32Col(shape=(), dflt=np.int32(0), pos=21),\n",
" 'bucket': Int32Col(shape=(), dflt=np.int32(0), pos=22)}"
]
Expand Down Expand Up @@ -125,7 +128,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 9,
"id": "416165d4-bb8c-466b-abe8-c85f02114537",
"metadata": {
"tags": []
Expand All @@ -135,12 +138,13 @@
"# csv column names\n",
"colnames = [\n",
" \"id_name\", \"ra\", \"ra_err\", \"dec\", \"dec_err\",\n",
" # nobs 8个\n",
" \"nobs_B\",\"nobs_V\",\"nobs_u\",\"nobs_g\",\"nobs_r\",\"nobs_i\",\"nobs_PanSTARRS_zs\",\"nobs_PanSTARRS_Y\",\n",
" # mag 8个\n",
" \"mag_B\",\"mag_V\",\"mag_u\",\"mag_g\",\"mag_r\",\"mag_i\",\"mag_PanSTARRS_zs\",\"mag_PanSTARRS_Y\",\n",
" # emag 8个\n",
" \"emag_B\",\"emag_V\",\"emag_u\",\"emag_g\",\"emag_r\",\"emag_i\",\"emag_PanSTARRS_zs\",\"emag_PanSTARRS_Y\",\n",
" \"Johnson_B\", \"Johnson_V\",\n",
" \"SDSS_up\", \"SDSS_gp\", \"SDSS_rp\", \"SDSS_ip\",\n",
" \"PanSTARRS_zs\",\"PanSTARRS_Y\",\n",
" \"Johnson_B_err\", \"Johnson_V_err\",\n",
" \"SDSS_up_err\", \"SDSS_gp_err\", \"SDSS_rp_err\", \"SDSS_ip_err\",\n",
" \"PanSTARRS_zs_err\",\"PanSTARRS_Y_err\",\n",
"]\n",
"\n",
"dataframe_iterator = iter_multi_csv_chunks(\n",
Expand All @@ -158,7 +162,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 10,
"id": "2349f2b6-cae4-4eee-a4f1-cc033080993e",
"metadata": {
"tags": []
Expand All @@ -173,15 +177,15 @@
" \"version\": \"dr10\",\n",
" \"mag_system\": {\n",
" \"Johnson_BV\": \"Vega\", \n",
" \"SDSS_ugri\": \"AB\", \n",
" \"SDSS_ugri_primed\": \"AB\", \n",
" \"PanSTARRS_zsY\": \"AB\", \n",
" }, \n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 11,
"id": "01200976-6664-47af-8868-a6c75ed283ec",
"metadata": {
"tags": []
Expand All @@ -190,7 +194,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1145d58e3b024d8ab904ee67ff969314",
"model_id": "3b1bbb836bc14e329189cd3d4cfd4720",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -204,12 +208,12 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a660e868200b4d369719f07206757394",
"model_id": "de28e8dc18aa44a3bc0fda04c0fc3596",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
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]
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"metadata": {},
Expand All @@ -218,12 +222,12 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "fa85bc70ff734c9cb736a567ced405a7",
"model_id": "01849ab9bb5149be8668fcc140683d74",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Chunks: 0%| …"
"Chunks: 0%| | 0/825 [00:00<?, ?it/s]"
]
},
"metadata": {},
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0 ...pile_Standard_Star_Catalog/APASS/zm90.txt → ...pile_Standard_Star_Catalog/APASS/zm90.txt
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66 changes: 28 additions & 38 deletions ...SS_Stripe_82/Compile_SDSS_Stripe_82.ipynb → ...SS_Stripe_82/Compile_SDSS_Stripe_82.ipynb
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Expand Up @@ -2,28 +2,21 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 5,
"id": "30731961-2747-4074-871c-ea7be2ddfb2c",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import sys\n",
"import pandas as pd\n",
"import numpy as np\n",
"from pathlib import Path\n",
"\n",
"# set up the system path to import the \n",
"# compile_standard_catalog module \n",
"extra = Path(\"..\").resolve()\n",
"sys.path.insert(0, str(extra))\n",
"\n",
"from compile_standard_catalog import (\n",
"from researchcodes import (\n",
" define_column_desc, \n",
" iter_multi_csv_chunks, \n",
" write_std_h5, \n",
")\n",
"\n",
"\n"
")"
]
},
{
Expand Down Expand Up @@ -57,18 +50,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"id": "cc8772ef-cb16-4efa-a3ae-d1530942aba1",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 6,
"id": "05700bea-d17e-4049-b1ef-e1de623e1415",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -100,7 +82,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 7,
"id": "0191ee0c-5e97-48a0-9f0a-ce7560a08137",
"metadata": {},
"outputs": [],
Expand All @@ -116,7 +98,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 8,
"id": "38b43a9d-0e11-4551-be6b-aa820db327f4",
"metadata": {},
"outputs": [],
Expand All @@ -140,7 +122,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 9,
"id": "2a463e75-156f-4103-bd65-f4616147d094",
"metadata": {},
"outputs": [],
Expand All @@ -164,14 +146,22 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 10,
"id": "ded1390c-30c1-439a-a321-b0194e3591ff",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# define magnitude column names\n",
"# Define magnitude column names\n",
"\n",
"# Note this magnitude column order is not necessarily\n",
"# to be the same as the column order in the text file. \n",
"\n",
"# It is OK as long as the filter names in \n",
"# `magnitude_column_names` matches `colnames` defined \n",
"# when reading the text file\n",
"\n",
"magnitude_column_names = [\n",
" \"SDSS_up\",\"SDSS_gp\",\"SDSS_rp\",\"SDSS_ip\",\"SDSS_zp\",\n",
" \"SDSS_up_err\",\"SDSS_gp_err\",\"SDSS_rp_err\",\"SDSS_ip_err\",\"SDSS_zp_err\",\n",
Expand All @@ -186,7 +176,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 11,
"id": "028b9e76-735f-4a60-9632-bdd370344af5",
"metadata": {},
"outputs": [
Expand All @@ -212,7 +202,7 @@
" 'bucket': Int32Col(shape=(), dflt=np.int32(0), pos=16)}"
]
},
"execution_count": 9,
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -231,7 +221,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 12,
"id": "1e3e364a-d139-463d-a592-3125a366abc9",
"metadata": {
"tags": []
Expand All @@ -245,7 +235,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 22,
"id": "416165d4-bb8c-466b-abe8-c85f02114537",
"metadata": {
"tags": []
Expand Down Expand Up @@ -278,7 +268,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 23,
"id": "2349f2b6-cae4-4eee-a4f1-cc033080993e",
"metadata": {
"tags": []
Expand All @@ -299,7 +289,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 24,
"id": "01200976-6664-47af-8868-a6c75ed283ec",
"metadata": {
"tags": []
Expand All @@ -308,7 +298,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "8ec29b674b154dfe8d9d9807bc9e714d",
"model_id": "802eaaa133fd419a89881afb1300a434",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -322,12 +312,12 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "15543887849e4fd2ac570dca5a2a639b",
"model_id": "7272cb61947941e4977c8f21fa74add0",
"version_major": 2,
"version_minor": 0
},
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]
},
"metadata": {},
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