{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Day 2 - Finding neighbours" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "from time import time" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reading the lens/source catalog" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [ "hide_input" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ra,dec,z,col_3,col_4,col_5\r\n", "30.611734783139795,-6.3569091978972425,23.901826,23.043298,22.649281,0.5\r\n", "30.61078116389429,-6.350381359287763,22.385773,21.548382,21.272576,0.38\r\n", "30.596477830319948,-6.3461523588063935,23.948118,23.121471,22.773187,0.37\r\n", "30.592680083175416,-6.3445214768250775,23.42731400000001,22.022285999999998,21.334948,0.45\r\n" ] } ], "source": [ "!head -n 5 /home/idies/workspace/Storage/divyar/IAGRG_2022/DataStore/demo_objects.csv\n", "\n", "# !wc -l /home/idies/workspace/Storage/divyar/IAGRG_2022/DataStore/demo_objects.csv" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#reading lens file\n", "\n", "#tries to read everthing in the file\n", "path=\"/home/idies/workspace/Storage/divyar/IAGRG_2022/DataStore/demo_objects.csv\"\n", "\n", "df = pd.read_csv(path, sep=',') " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# a brief look of what dataFrame has for us-\n", "\n", "Data from - `HSC survey`
\n", "\n", "ra,dec - coordinates in units of degrees.
\n", "\n", "z - photometric redshifts of the objects.\n", "\n", "col_1,col_2,col_3 - extra columns which have to be ignored\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " ra dec z col_3 col_4 col_5\n", "0 30.611735 -6.356909 23.901826 23.043298 22.649281 0.50\n", "1 30.610781 -6.350381 22.385773 21.548382 21.272576 0.38\n", "2 30.596478 -6.346152 23.948118 23.121471 22.773187 0.37\n", "3 30.592680 -6.344521 23.427314 22.022286 21.334948 0.45\n", "4 30.601111 -6.338650 21.660045 20.812223 20.383688 0.32" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# select required columns only" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(path, sep=',', usecols=[0,1,2])" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " ra dec z\n", "0 30.611735 -6.356909 23.901826\n", "1 30.610781 -6.350381 22.385773\n", "2 30.596478 -6.346152 23.948118\n", "3 30.592680 -6.344521 23.427314\n", "4 30.601111 -6.338650 21.660045" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualising the coordinate space of input data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise: \n", " \n", "- write a python code to plot dec (on Y-axis) vs ra (on X-axis) of the objects passed in the dataFrame.\n", "\n", " This plot will look very dense, so in order to visually see the points distributed on the (ra,dec) plane, downsample the number of points by 100 and again plot.\n", "- In order to downsample the points, use `numpy.random.choise()` function.\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of points before down sampling = 220622\n", "Number of points after down sampling by 100 = 2206\n", "\n", "randomly picked indices:\n", " [ 77470 149688 79224 ... 44467 39179 90845]\n" ] } ], "source": [ "# Using numpy.random.choise() to randomly pick up points\n", "# and hence reduce the density of points\n", "\n", "Number_of_points = df.ra.size\n", "down_sample_by = 100\n", "random_indices = np.random.choice(np.arange(Number_of_points), \n", " size=int(Number_of_points/down_sample_by), \n", " replace=False)\n", "\n", "print(\"Number of points before down sampling = \", Number_of_points)\n", "print(f\"Number of points after down sampling by {down_sample_by} = \", random_indices.size)\n", "print()\n", "print(\"randomly picked indices:\\n\",random_indices)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
Your plot should look something like
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} }, "cell_type": "markdown", "metadata": {}, "source": [ "![coordinateSpacePlots.png](attachment:coordinateSpacePlots.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### `On-sky distance` between two points on the surface of a unit sphere" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$\\vec{r_i} = r_i(\\sin\\theta \\cos\\phi \\ \\hat{x}+ \\sin\\theta \\sin\\phi \\ \\hat{y} + \\cos\\theta \\ \\hat{z})$, $\\hspace{0.5cm}$for $\\mathrm{i \\in (1,2)}$.\n", "\n", "$\\cos(\\theta)=\\frac{\\vec{r_1}\\cdot\\vec{r_2}}{r_1 r_2}$
\n", "\n", "set $r_1=r_2=1$ \n", "\n", "get $\\theta$\n", "\n", "Using: $\\mathrm{arc\\_distance}=s=r \\times \\theta$, obtain the distance between the two ra,dec values.\n", "\n", "Since $r_1=r_2=1$, \n", "\n", "$\\Rightarrow s=\\theta$ (radians)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise: Using the above formula\n", "\n", "- Implement a function which takes tuples of (ra,dec) of two objects and returns the distance between them on the Unit sphere.\n", "\n", " Your code should return the result in units of arc seconds and **NOT** in radians.\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": [ "rad_to_arcsec = 180.0*3600./np.pi\n", "arcsec_to_rad = 1/rad_to_arcsec\n", "\n", "def dist_betw_two_obj(obj1,obj2):\n", " ra1,dec1 = obj1\n", " #complete this code\n", " return dist" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# Running and testing the distance computation code:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# creating a list/array tuple of values from ra,dec of each object" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "coords = list( zip(df.ra.values,df.dec.values))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# print the (ra,dec) tuples of first two objects in the above list \n", "\n", "\\# compute and print the distance between these two objects, \n", "\n", "I get the following:\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Brute force search for neighbour objects within a specified distance \n", "time complexity ~ $\\mathcal{O}(n^2)$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise: \n", " \n", "1)\n", " \n", "- Write a function `find_neighbour_points` that uses (ra,dec) coordinates of an object, and within some given `rmax` distance, finds its neighbour points in the given dataFrame catalog.\n", "\n", "- Using this code you should be able to find neighbours of each object in the dataFrame - within the same dataFrame.\n", "\n", " Say the $1^{st}$ object in the dataFrame has 5 objects within say rmax=15 arcsec, then you should be able to print/store the `indices` and `distances` of these neighbours.\n", "\n", "2)\n", " \n", "- Write a function `query_neighbour_points` that can use (ra,dec) coordinates of one object or an list/array of objets, and within some given `rmax` distance, finds its neighbour points in any other catalog.\n", "\n", "- Using this code you should be able to access the coordinates of all the neighbours of each object that you are querying for. And hence you should be able to tell how far each neighbour is from the queried object.\n", " \n", "
" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "# Exercise (1) is solved here:\n", "\n", "from collections import defaultdict\n", "\n", "def find_neighbour_points(coords, rmax=10, verbose=True):\n", " \"\"\"\n", " finding neighbour objects within some distance, for all the objects in a given array of coordinates.\n", " \n", " coords: an array/list of tuples (ra,dec)\n", " \n", " Returns:\n", " `nnids`: indices into `coords` of neighbours of each object in `coords` within `rmax`\n", " `distances`: distance of objects matched in `nnids\"\"\"\n", "\n", " # define containers for the distance and id information of matched objects\n", " distances = defaultdict(list)\n", " nnids = defaultdict(list)\n", "\n", " c=0\n", " for ii,obj1 in enumerate(coords):\n", " c+=1\n", " d=0\n", " for jj,obj2 in enumerate(coords):\n", " if jj==ii:\n", " continue\n", " d+=1\n", " dist = dist_betw_two_obj(obj1,obj2)\n", " if dist <= rmax:\n", " nnids[ii].append(jj)\n", " distances[ii].append(dist)\n", " if verbose:\n", " print(ii,nnids[ii],distances[ii]) \n", " return nnids,distances\n", "\n", "#try to build on the information/tricks you have to solve for exerise (2) given above.\n", "def query_neighbour_points(coords1, coords2, rmax=10):\n", " \"\"\"\n", " coords1: a tuple or an array/list of tuples (ra,dec)\n", " coords2: an array/list of tuples (ra,dec)\n", " \n", " Returns:\n", " `nnids`: indices into `coords2` of neighbours of each object `coords1` within `rmax`.\n", " `distances`: distance of objects matched in `nnids`\"\"\"\n", " \n", " # finish this code\n", " return nnids,distances" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Testing the above `brute force search` functions " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise: \n", "\n", "- Using the first 50 objects in the catalog, Search for their neighbours within a ball of radius `rmax`, say for `rmax`(default value)=15 arcsec.\n", "\n", " **Note:** We're only using 50 points in order to reduce the compute time, but the code has no such limitation. If you run your code for a large number of points, it will take more time to finish that's all.\n", " \n", " \n", "- Access the above result and print indices,distances and coordinates of the neighbours of few objects.\n", " \n", "- Then test out the function `query_neighbour_points` for the same objects you take above. The neighbour matches from `query_neighbour_points` and `find_neighbour_points` must match. \n", " \n", "
" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "object index, neighbours indices list, neighbours distances list \n", "0 [] []\n", "1 [] []\n", "2 [3] [14.802299176580224]\n", "3 [2] [14.802299176580224]\n", "4 [36] [13.682331312465545]\n", "5 [] []\n", "6 [] []\n", "7 [] []\n", "8 [13] [9.465537930627812]\n", "9 [10, 12, 38] [10.94680374083333, 5.876628853240463, 14.594679725290598]\n", "10 [9, 12] [10.94680374083333, 10.280601486171243]\n", "11 [42] [7.151725370768233]\n", "12 [9, 10, 14] [5.876628853240463, 10.280601486171243, 11.314136132011965]\n", "13 [8] [9.465537930627812]\n", "14 [12, 15, 16] [11.314136132011965, 5.475958296970058, 11.765854084075805]\n", "15 [14, 16, 44] [5.475958296970058, 13.47975484115049, 10.276694006812336]\n", "16 [14, 15] [11.765854084075805, 13.47975484115049]\n", "17 [46] [6.898087849306218]\n", "18 [] []\n", "19 [] []\n", "20 [] []\n", "21 [] []\n", "22 [] []\n", "23 [] []\n", "24 [] []\n", "25 [26] [13.29908354885402]\n", "26 [25] [13.29908354885402]\n", "27 [] []\n", "28 [] []\n", "29 [30] [3.6918325238285883]\n", "30 [29] [3.6918325238285883]\n", "31 [] []\n", "32 [] []\n", "33 [] []\n", "34 [] []\n", "35 [36] [10.896870606370635]\n", "36 [4, 35] [13.682331312465545, 10.896870606370635]\n", "37 [] []\n", "38 [9, 40] [14.594679725290598, 14.719522078343205]\n", "39 [40] [1.984703189527645]\n", "40 [38, 39] [14.719522078343205, 1.984703189527645]\n", "41 [] []\n", "42 [11] [7.151725370768233]\n", "43 [] []\n", "44 [15] [10.276694006812336]\n", "45 [] []\n", "46 [17] [6.898087849306218]\n", "47 [] []\n", "48 [] []\n", "49 [] []\n", "CPU times: user 54.2 ms, sys: 4.6 ms, total: 58.8 ms\n", "Wall time: 53.3 ms\n" ] } ], "source": [ "print(\"object index, neighbours indices list, neighbours distances list \")\n", "\n", "# from time import time \n", "# t=time()\n", "# nnids,distances = find_neighbour_points(coords[:100],rmax=15)\n", "# print(f\"total time taken to run = {time()-t}\")\n", "\n", "\n", "%time nnids,distances = find_neighbour_points(coords[:50],rmax=15)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accessing the neighbour points for the 15th object using the output \n", "of our brute force method:\n", "neighbours: [14, 16, 44] \n", "distances: [5.475958296970058, 13.47975484115049, 10.276694006812336]\n", "\n", "Accessing the neighbour coordinates of the 15th object:\n", "14 (30.564297942270603, -6.322030429805476)\n", "16 (30.56234780563957, -6.319398928221537)\n", "44 (30.568297869918087, -6.3202347701814166)\n" ] } ], "source": [ "nth = 15\n", "print(f\"\"\"Accessing the neighbour points for the {nth}th object using the output \n", "of our brute force method:\"\"\")\n", "\n", "print(f\"neighbours: {nnids[nth]} \\ndistances: {distances[nth]}\")\n", "\n", "print()\n", "\n", "print(f\"Accessing the neighbour coordinates of the {nth}th object:\")\n", "for ii in nnids[nth]:\n", " print(ii, coords[ii])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "#### A visual sanity check for execution of `find_neighbour_points` function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise:\n", "\n", "- Plot the coordinates of the neighbours of any one test point. This exercise can help us visually inspect whether our neighbour search code gave us reasonable results or not.\n", "\n", "\n", "- Along with plotting, also print the distances of each of these neighbours and visually confirm that the nearest looking object on the plot indeed has the smallest distance from the test point, and similarly check for other neighbour points.\n", " \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I'm plotting the neighbours of $15^{th}$ point from the catalog.
\n", "And also printing their `indices` and `distances` to compare the stored distances by eye!\n", "\n", "Point marked as $\\star$ is the $15^{th}$ point. Other points are its neighbours.\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "#converting list to arrays\n", "coords=np.array(coords)\n", "\n", "demoid = 15\n", "#get coordinates of `demoid` object \n", "\n", "#get neighbours of `demoid` object --> store it in a variable `neighbours`\n", "#get coordinates of all the neighbours of `demoid` object \n", "\n", "#Make scatter plot of demo point\n", "\n", "#Make scatter plot of all the neighbour points on the same axis.\n", "\n", "#pass x and y labels\n", "\n", "# You're done! Do : plt.show()\n", "\n", "#access distances of all the neighbours of `demoid` and store in a variable.\n", "# print `index of each neighbour` ---> `its distance`\n", "\n", "# Now visually compare the distances...does it make sense?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Using k-d tree algorithm to query the neighbour points within a given distance \n", "time complexity ~ $\\mathcal{O}(n\\log{}n)$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We'll use the `spatial.cKDTree` package from `scipy`.\n", "\n", "If you have many points whose neighbors you want to find, you may save substantial amounts of time by putting them in a `cKDTree` and using functions defined on this tree. For example: `query_ball_point`" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "from scipy import spatial\n", "sin = np.sin\n", "cos = np.cos\n", "deg2rad = np.deg2rad" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise:\n", " \n", "- Write a code using cKDTree to find out the neighbours of a given `set1` of objects (coordinates) from a catalog of other `set2` objects.\n", " \n", " Write this code in a `class structure` where it takes-in arrays of `ra,dec` of the catalog objects (set2) and \n", " - converts (ra,dec) to (x,y,z) of cartesian coordinates,\n", " - creates k-d tree of the `set2` catalog objects using (x,y,z),\n", " - queries for the neighbour points of - each object in the `set1`, and returns the indices in `set2`.\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "class find_neighbours:\n", " def __init__(self, tra=None, tdec=None, r=1):\n", " \"\"\"r==1 --> unit sphere calculations\n", " tra,tdec--> coordinates to create tree for.\"\"\"\n", " \n", " self.tra = tra\n", " self.tdec= tdec\n", " self.r = r\n", " self.rad_to_arcsec = 180.0*3600./np.pi\n", " self.arcsec_to_rad = 1/self.rad_to_arcsec\n", " \n", " print(f\"Initializing with sphere of radius, r={r}.\")\n", " \n", " # write a function that converts ra,dec to cartesian components.\n", " def RA_DEC_to_xyz(self, ra,dec, units='deg'):\n", " \"\"\"converts ra,dec to cartesian x,y,z components on a unit sphere\"\"\"\n", " if units==\"deg\":\n", " ra = deg2rad(ra)\n", " dec= deg2rad(dec)\n", " \n", " # fill the details to compute x,y,z coordinates\n", " \n", " return x,y,z \n", "\n", " # write a function `create_tree` uses arrays of tra,tdec \n", " # values as inputs and returns a cKDTree object into these coordinates.\n", " # use the below function -\n", " def create_tree(self):\n", " # fill the details to create an array of tuples of x,y,z from tra,tdec\n", " x,y,z = ?? \n", " \n", " # make a tree using cKDTree method \n", " tree = spatial.cKDTree(np.c_[x,y,z])\n", " return tree\n", "\n", " # write a function that takes arrays of ra,dec coordinates\n", " # and returns the neighbour object's indices from the tree \n", " # within some distance `rmax` arcsec .\n", " # use the below function -\n", " def query_within_rmax(self, ra, dec, rmax=15, units=\"deg\"):\n", " print(f\"Searching for {ra.size} number of objects in the catalog with rmax={rmax} arcsec.\")\n", " #convert rmax from arcsec to distance units\n", " rmax = 15 * ??\n", " \n", " #get x,y,z from ra,dec passed to this function.\n", " x,y,z = ??\n", " \n", " # copmute x,y,z of input objetcs\n", " cartesian_coords = np.c_[x,y,z]\n", "\n", " # make tree from catalog by calling function self.create_tree\n", " tree = ??\n", " \n", " # look for the neighbour objects\n", " ids_into_tree = tree.query_ball_point(cartesian_coords,rmax)\n", " \n", " return ids_into_tree" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### A sanity check\n", "\n", "Testing conversion of (ra,dec) to (x,y,z) " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "# Here we are not passing `tra` and `tdec` while initialising the class `find_neighbours`\n", "# So these variables take default values of `None`. \n", "# We only want to test the coordinate conversion code `RA_DEC_to_xyz`. So it's ok to not \n", "# pass `tra`,`tdec`!\n", "\n", "code = find_neighbours()\n", "\n", "# a look at the cartesian coordinates\n", "x,y,z = code.RA_DEC_to_xyz(coords[:,0], coords[:,1])\n", "cartesian_coords = np.c_[x,y,z]\n", "\n", "print(\"shapes of x,y,z arrays:\",x.shape,y.shape,z.shape)\n", "print(\"shapes of (x,y,z) tuple array:\", cartesian_coords.shape)\n", "#field on objects looks close to equator\n", "print(cartesian_coords)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Compare the output of our brute force algorithm with cKDTree algorithm on few Demo objects" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "Exercise:\n", "\n", "- Take the same bunch of objects for which we already have run our brute force search method, \n", "\n", " feed them into the wrapper code of k-d tree written above, \n", " \n", " find out their neighbour points within the same `rmax`(default value)=15 arcsec.\n", " \n", " The neighbour objects found from both the methods should match!\n", "\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "I had chosen following indices from set2(catalog) as my test objects: [15]\n" ] } ], "source": [ "# Store some demo objects as per your choice\n", "demo_ids = [15] #9,15\n", "demo_ra =coords[demo_ids,0] #in degrees\n", "demo_dec=coords[demo_ids,1] #in degrees\n", "\n", "print(\"\"\"I had chosen following indices from set2(catalog) as my test objects:\"\"\",demo_ids)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# Initialize class and set up the tree by passing it a catalog of objects." ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Initializing with sphere of radius, r=1.\n" ] } ], "source": [ "code_tree = find_neighbours(tra=coords[:,0], tdec=coords[:,1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# Query the neighbours of demo objects " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "idx=code_tree.query_within_rmax(demo_ra, demo_dec)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\\# Go back to brute force output and compare this result.... does it match? " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "idx" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Compare the computer time required by our brute force algorithm vs the k-d tree algorithm " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First let's use k-d tree to query neighbours within `rmax`=15 arcsec for each object within the catalog." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%time idx = code_tree.query_within_rmax(coords[:,0], coords[:,1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Reminder:** full catalog has about 2,20,000 objects... and k-d tree found neighbours for each one of them in 1-2 seconds. (This time will vary depending on your computer's capability.)\n", "\n", "Now let's use the brute force method only for 1000 objects." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "%time nnids,distances = query_neighbour_points(coords[:1000],rmax=15, verbose=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Congratulations! Now you have learnt to - \n", "\n", "- use `cKDTree` to find out neighbours of a given `set1` of objects into some other `set2` of objects.\n", "\n", "- count the number of neighbours of any given object in `set1`. \n", "\n", "- access the results of cKDTree and identify neighbours of each obejct in `set1` into the `set2`.\n", "\n", "- access the coordinates and distances of each neighbour of every point in `set1`." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 4 }