import pymongo
from function import count_occurences_field
client = pymongo.MongoClient("localhost", 27017)
db = client.phoenix
##collections
genre = db.genre
event = db.event
total_number_of_events = event.count()
##make the histogram
field_list = ["metadata.live", "metadata.new_episode", "metadata.new_serie", "metadata.premiere"]
for fieldname in field_list:
data = count_occurences_field(event,fieldname)
x = data.keys()
y = data.values()
pos = np.arange(len(x))+0.5
plt.figure()
plt.barh(x, y)
plt.axvline(total_number_of_events,linestyle="dashed",color="black")
plt.xlabel("Counts")
plt.ylabel(fieldname)
plt.yticks(pos,x)
plt.savefig("figures/histogram_"+fieldname+".pdf")
os.mkdir(root_output+c)
##get keys
current_collection = db[c]
document_example = current_collection.find_one()
list_keys = get_allkeys(document_example) #get a random example (might not contain all the keys accross all documents of the current collection)
total_number_of_documents = current_collection.find().count()
for k in list_keys:
try:
counts_distinct = len(current_collection.distinct(k))
except pymongo.errors.OperationFailure: #if returns too many documents
print "operationfailure"
if counts_distinct <= threshold:
data = count_occurences_field(current_collection,k)
x = data.keys()
y = data.values()
pos = np.arange(len(x))+0.5
if len(x) > 1: #do not plot if only 1 element
if not isinstance(x[0],float): #keep float for plot
x = [type_to_string(i) for i in data.keys()]
x = [i.decode('utf-8') for i in x]
plt.figure()
plt.barh(pos, y)
plt.axvline(total_number_of_documents,linestyle="dashed",color="black")
plt.xlabel("Counts")
plt.ylabel(k)
plt.yticks(pos+0.5,x)
