Merge pull request #4 from gaelforget/argovisexample

Argovis example

.gitignore

@@ -6,4 +6,6 @@
 /dev/
 /docs/build/
 /docs/site/
+MITprof
+examples/*.ipynb
 .ipynb_checkpoints/

Project.toml

@@ -1,7 +1,7 @@
 name = "ArgoData"
 uuid = "9eb831cf-c491-48dc-bed4-6aca718df73c"
 authors = ["gaelforget <[email protected]>"]
-version = "0.1.1"
+version = "0.1.2"
 
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"

examples/Argovis_Julia_Example.jl

@@ -0,0 +1,65 @@
+# ---
+# jupyter:
+#   jupytext:
+#     formats: ipynb,jl:light
+#     text_representation:
+#       extension: .jl
+#       format_name: light
+#       format_version: '1.4'
+#       jupytext_version: 1.2.4
+#   kernelspec:
+#     display_name: Julia 1.3.0-rc4
+#     language: julia
+#     name: julia-1.3
+# ---
+
+# # Access Argo data using [ArgoVis](https://argovis.colorado.edu/ng/home) in Julia
+#
+# Citation for the Argovis web application and the Argovis database: 
+# Tucker, T., D. Giglio, M. Scanderbeg, and S.S.P. Shen, 0: Argovis: A Web Application for Fast Delivery, Visualization, and Analysis of Argo Data. J. Atmos. Oceanic Technol., 0, https://doi.org/10.1175/JTECH-D-19-0041.1
+#
+# Argo data reference 
+# " These data were collected and made freely available by the International Argo Program and the national programs that contribute to it. (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System. " 
+# Argo (2000). Argo float data and metadata from Global Data Assembly Centre (Argo GDAC). SEANOE. http://doi.org/10.17882/42182
+
+# +
+#run(pipeline(`which python`,"whichpython.txt")) #external python path
+#ENV["PYTHON"]=readline("whichpython.txt")
+#import Pkg; Pkg.build("PyCall")
+
+using PyCall
+
+requests = pyimport("requests")
+pd = pyimport("pandas")
+np = pyimport("numpy")
+sp = pyimport("scipy.interpolate")
+griddata=sp.griddata
+datetime = pyimport("datetime")
+pdb = pyimport("pdb")
+os = pyimport("os")
+netCDF4 = pyimport("netCDF4")
+netcdf_dataset=netCDF4.Dataset
+
+# +
+function get_monthly_profile_pos(month, year)
+    baseURL = "https://argovis.colorado.edu/selection/profiles"
+    url = baseURL*"/"*string(month)*"/"*string(year)
+    resp = requests.get(url)
+    monthlyProfilePos = resp.json()
+    return monthlyProfilePos
+end
+
+function parse_meta_into_df(profiles)
+    #initialize dict
+    df = pd.DataFrame(profiles)
+    return df
+end
+
+# set month and year for metadata
+month = 1
+year = 2004
+metaProfiles = get_monthly_profile_pos(month, year)
+metaDf = parse_meta_into_df(metaProfiles)
+# -
+
+