import brewer2mpl
mpl.rcParams['axes.color_cycle'] = brewer2mpl.get_map('Dark2', 'qualitative', 7).mpl_colors
mpl.rcParams['figure.figsize'] = (9,6)

import os
DEV_KEY = os.environ['ADS_DEV_KEY']
BASE_URL = 'http://adslabs.org/adsabs/api/search/'

params = {}

params['q'] = 'ack:simbad'  # searches for the word 'simbad'

params['fl'] = 'pubdate'

params['rows'] = '10'  # use a small value for now
params['dev_key'] = DEV_KEY

import requests
params['start'] = 0
r = requests.get(BASE_URL, params=params)

import simplejson
data = simplejson.loads(r.text)

data['results']['docs'][0]

for d in data['results']['docs']:
    print(d['pubdate'])

year = d['pubdate'].split('-')[0]
print(year)

import os
DEV_KEY = os.environ['ADS_DEV_KEY']
BASE_URL = 'http://adslabs.org/adsabs/api/search/'

def query_acknowledgments(word):

    # Set query parameters
    params = {
              'q': 'ack:{0:s},property:REFEREED'.format(word),
              'fl': 'pubdate',
              'rows': '200',
              'dev_key': DEV_KEY
             }
    
    import requests
    params['start'] = 0
    
    processed = 0
    
    pub_years = []
    while True:
        
        # Execute the query
        r = requests.get(BASE_URL, params=params)
        
        # Check if anything went wrong
        if r.status_code != requests.codes.ok:
            e = simplejson.loads(r.text)
            sys.stderr.write("error retrieving results: {0:s}\n".format(e['error']))
            continue
            
        # Extract results
        import simplejson
        data = simplejson.loads(r.text)
        for d in data['results']['docs']:
            pub_years.append(float(d['pubdate'].split('-')[0]))
    
        # Update starting point
        params['start'] += data['meta']['count']
        
        # Check if finished
        if params['start'] >= data['meta']['hits']:
            break
            
    import numpy as np
    return np.array(pub_years)

pub_years = query_acknowledgments('simbad')
pub_years

YEARS = list(range(1995, 2014))
YEARS

query_count = np.array([np.sum(pub_years == year) for year in YEARS])

plt.plot(YEARS, query_count)
_ = plt.xlabel("Year")
_ = plt.ylabel("Number of papers mentioning SIMBAD")

def total_number(year):
    
    params = {
          'q': 'pubdate:{0:s},property:REFEREED'.format(year),
          'dev_key':DEV_KEY,
          'rows':1
          }

    import requests
    r = requests.get(BASE_URL, params=params)
    
    import simplejson
    data = simplejson.loads(r.text)
    
    return data['meta']['hits']

total_number('2012')

TOTAL_COUNT = []

for year in YEARS:
    date = '{0:04d}'.format(year)
    TOTAL_COUNT.append(total_number(date))

TOTAL_COUNT = np.array(TOTAL_COUNT)

plt.plot(YEARS, TOTAL_COUNT)
plt.ylim(0, 400000)
_ = plt.xlabel("Year")
_ = plt.ylabel("Total number of papers")

plt.plot(YEARS, query_count / TOTAL_COUNT * 100.)
plt.xlabel("Year")
plt.ylabel("% of papers mentioning SIMBAD")

def plot_yearly_trend(keyword, label=None):
    pub_years = query_acknowledgments(keyword)
    query_count = np.array([np.sum(pub_years == year) for year in YEARS])
    plt.plot(YEARS, query_count / TOTAL_COUNT * 100., label=label, lw=2, alpha=0.8)

plot_yearly_trend('simbad', label='simbad')
plt.legend(loc=2)
_ = plt.xlabel("Year")
_ = plt.ylabel("% of papers mentioning various keywords")

plot_yearly_trend('Astrophysics Data System', label='Astrophysics Data System')
plt.legend(loc=2)
_ = plt.xlabel("Year")
_ = plt.ylabel("% of papers mentioning various keywords")

plot_yearly_trend('simbad', label='Simbad')
plot_yearly_trend('vizier', label='Vizier')
plot_yearly_trend('ned', label='NED')
plt.legend(loc=2)
_ = plt.xlabel("Year")
_ = plt.ylabel("% of papers mentioning various keywords")

plot_yearly_trend('idl', label='IDL')
plot_yearly_trend('python', label='Python')
plot_yearly_trend('fortran', label='Fortran')
plot_yearly_trend('perl', label='perl')
plt.legend(loc=2)
_ = plt.xlabel("Year")
_ = plt.ylabel("% of papers mentioning various keywords")

plot_yearly_trend('starlink', label='Starlink')
plot_yearly_trend('ds9', label='ds9')
plot_yearly_trend('topcat', label='Topcat')
plot_yearly_trend('aladin', label='Aladin')
plot_yearly_trend('iraf', label='IRAF')
plt.legend(loc=2)
_ = plt.xlabel("Year")
_ = plt.ylabel("% of papers mentioning various keywords")