mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 19:38:02 +00:00
187 lines
4.8 KiB
Text
187 lines
4.8 KiB
Text
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from h5py import File\n",
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"from scipy.stats import spearmanr\n",
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"\n",
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"import csiborgtools\n",
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"\n",
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"%matplotlib inline\n",
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"%load_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)\n",
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"\n",
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"# d = np.load(paths.field_interpolated(\"SDSS\", \"csiborg2_main\", 16817, \"density\", \"SPH\", 1024))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {},
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"outputs": [],
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"source": [
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"survey = csiborgtools.SDSS()(apply_selection=False)\n",
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"# survey = csiborgtools.SDSSxALFALFA()(apply_selection=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Reading fields: 0%| | 0/20 [00:00<?, ?it/s]"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Reading fields: 100%|██████████| 20/20 [00:11<00:00, 1.80it/s]\n",
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"Reading fields: 100%|██████████| 20/20 [00:10<00:00, 1.86it/s]\n"
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]
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}
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],
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"source": [
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"for kind in [\"main\", \"random\"]:\n",
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" x, smooth = csiborgtools.summary.read_interpolated_field(survey, f\"csiborg2_{kind}\", \"density\", \"SPH\", 1024, paths)\n",
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" np .savez(f\"../data/{survey.name}_{kind}_density_SPH_1024.npz\", val=x, smooth_scales=smooth)\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(20, 641409, 5)"
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]
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},
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"execution_count": 37,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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"\n",
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan]],\n",
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"\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan]],\n",
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"\n",
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" [[nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan]],\n",
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"\n",
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" [[nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan],\n",
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" ...,\n",
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" [nan, nan, nan, nan, nan],\n",
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" [nan, nan, nan, nan, nan]]], dtype=float32)"
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]
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},
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.load(\"../data/SDSS_main_density_SPH_1024.npz\")[\"val\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv_csiborg",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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