add Query functions

Examples/Basic_cosmo_example.jl

@@ -1,5 +1,5 @@
 ### A Pluto.jl notebook ###
-# v0.19.36
+# v0.19.41
 
 using Markdown
 using InteractiveUtils
@@ -51,6 +51,14 @@ H(c,100)#takes your cosmology model and z
 # ╔═╡ 3aa50f1f-04e8-4d0d-a650-c0ef8e75089f
 md"Let's try plotting $\frac{H(z)}{(1+z)}$ vs $z$."
 
+# ╔═╡ 5156f459-79e4-467e-b894-9e7cb89d58e7
+# ╠═╡ disabled = true
+#=╠═╡
+begin
+	Pkg.add("LaTeXStrings")
+end
+  ╠═╡ =#
+
 # ╔═╡ 2ee6b0bf-3511-4fea-8132-9896f5f112ec
 begin
 	z_vals = range(0, 2.5, length=1000)
@@ -132,6 +140,7 @@ plot!([13.807434539,13.807434539],[0,2.5],lc=:green,lw=2.5,label="t = 13.80743",
 # ╟─5d11e724-326a-436f-94f4-211f99d30990
 # ╠═7e4c3515-02f7-498b-829f-23e78997fb70
 # ╟─3aa50f1f-04e8-4d0d-a650-c0ef8e75089f
+# ╠═5156f459-79e4-467e-b894-9e7cb89d58e7
 # ╠═1473e933-d04a-4a0b-90d8-ab33df9ff3ee
 # ╠═2ee6b0bf-3511-4fea-8132-9896f5f112ec
 # ╟─4984ac71-b8eb-4085-a20a-9a2ac5f439a4

Project.toml

@@ -4,10 +4,17 @@ authors = ["Kazi Abu Rousan"]
 version = "1.0.0-DEV"
 
 [deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
+LaTeXStrings = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Pluto = "c3e4b0f8-55cb-11ea-2926-15256bba5781"
 QuadGK = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 
 [compat]

src/Cosmic.jl

@@ -1,9 +1,11 @@
 module Cosmic
 
 include("basic_cos.jl")
+include("thermo.jl")
+include("astroquery.jl")
 
 export a, redshift, cosmology, Mpc_to_km, sec_to_year, H, my_f, my_g,
         hubble_distance, χ, hubble_time, T, age, look_back_time, scale_fact,
-        da_dt, ageGyr,scalefact_part
+        da_dt, ageGyr,scalefact_part, fetch_gaia_data, filter_missing_values
 
 end#  module end

src/astroquery.jl

@@ -0,0 +1,61 @@
+using HTTP
+using DataFrames
+using CSV
+
+function fetch_gaia_data(query::String)
+    url = "https://gea.esac.esa.int/tap-server/tap/sync"
+    params = Dict(
+        "REQUEST" => "doQuery",
+        "LANG" => "ADQL",
+        "FORMAT" => "csv",
+        "QUERY" => query
+    )
+    encoded_params = join(["$k=$(HTTP.escapeuri(v))" for (k, v) in params], "&")
+    response = HTTP.post(url, ["Content-Type" => "application/x-www-form-urlencoded"], encoded_params)
+    if response.status == 200
+        data = CSV.read(IOBuffer(response.body), DataFrame)
+        return data
+    else
+        error("Error: ", response.status, "\n", String(response.body))
+    end
+end
+
+function filter_missing_values(df::DataFrame)
+    clean_data = dropmissing(df)
+    return clean_data
+end
+
+query = """
+SELECT TOP 10
+    source_id,
+    ra,
+    dec,
+    parallax,
+    phot_g_mean_mag
+FROM gaiadr3.gaia_source
+WHERE ra BETWEEN 0 AND 10
+  AND dec BETWEEN -10 AND 10
+"""
+
+query1 = """
+SELECT
+    source_id,
+    ra,
+    dec,
+    parallax,
+    phot_g_mean_mag
+FROM gaiadr3.gaia_source
+WHERE ra BETWEEN 0 AND 10
+  AND dec BETWEEN -10 AND 10
+"""
+
+function filter_missing_values(df::DataFrame)
+    # Filter rows containing missing values
+    clean_data = dropmissing(df)
+    return clean_data
+end
+
+
+data = fetch_gaia_data(query1)
+dat_fil = filter_missing_values(data)
+println(dat_fil)

test/runtests.jl

@@ -1,11 +1,51 @@
 using Cosmic
 using Test
+using Plots
 
 @testset "Cosmic.jl" begin
-    @test my_f(2,1) == 11
-    @test my_g(2) == 4
     @test redshift(2.9e-4) ≈ 3447.27586
     @test cosmology().h ≈ 0.6774
     @test scalefact_part(cosmology(),100) ≈ 148.9412838881
     @test ageGyr(cosmology(),0) ≈ 13.80743453918
-end
+end
+
+
+
+query = """
+SELECT source_id,
+    phot_g_mean_mag,
+    bp_rp,
+    phot_g_mean_flux,
+    parallax
+FROM gaiadr3.gaia_source
+WHERE bp_rp IS NOT NULL AND phot_g_mean_mag IS NOT NULL AND parallax > 50
+ORDER BY phot_g_mean_mag ASC
+"""
+
+gaia_data = fetch_gaia_data(query)
+data = filter_missing_values(gaia_data)
+
+parallax = gaia_data[:, "parallax"]
+distance = 1000.0 ./ parallax # distance in parsecs
+abs_mag = gaia_data[:, "phot_g_mean_mag"] .+ 5 .* log10.(parallax / 100.0)
+
+luminosity = 10 .^ ((4.83 .- abs_mag) ./ 2.5)
+
+bp_rp = gaia_data[:, "bp_rp"]
+
+normalized_bp_rp = (bp_rp .- minimum(bp_rp)) ./ (maximum(bp_rp) .- minimum(bp_rp))
+
+cmap = cgrad(:plasma)
+
+scatter(bp_rp, log10.(luminosity), 
+        marker_z=normalized_bp_rp, 
+        color=cmap, 
+        xlabel="BP-RP", 
+        ylabel="Log(Luminosity/Lsun)", 
+        title="HR Diagram", 
+        legend=false, 
+        reverse=true)
+
+ylims!((minimum(log10.(luminosity)) - 0.5, maximum(log10.(luminosity)) + 0.5))
+
+plot!()