def getTimelineValues():
global items
yearCol = "year"
if yearCol not in items[0]:
print("Could not find column %s in items, please add this column to metadata cols with 'type' = 'int'" % yearCol)
sys.exit()
years = [item[yearCol] for item in items]
minYear = min(years)
maxYear = max(years)
totalYears = maxYear - minYear + 1
groups = lu.groupList(items, yearCol) # group by year
yearDataLookup = lu.createLookup(groups, yearCol)
timelineItems = []
for i in range(totalYears):
year = i + minYear
yearKey = str(year)
count = 0
if yearKey in yearDataLookup:
count = yearDataLookup[yearKey]["count"]
timelineItems.append({
"year": year,
"value": count
})
return timelineItems
cleanedItems[i]["Acquisition Type"] = acquisitionType.capitalize()
cleanedItems[i]["Acquisition Type Confidence"] = typeConfidence
# Debugging...
# lu.countValues(cleanedItems, "Acquisition Year")
# lu.countValues(cleanedItems, "Acquisition Type")
# sys.exit()
##############################################
# STEP 2: retrieve country #
##############################################
# lu.countValues(items, "Country")
_, countrySynonyms = io.readCsv("data/usergen/CountriesSynonyms.csv")
countrySynonymLookup = lu.createLookup(countrySynonyms, "alt")
_, countryLatLons = io.readCsv("data/vendor/CountriesLatLon.csv")
countryLookup = lu.createLookup(countryLatLons, "name")
for i, item in enumerate(items):
country = item["Country"].strip()
countryConfidence = 1.0
if len(country) < 1:
continue
# normalize lists
country = country.replace("/", ", ")
country = country.replace(" OR ", ", ")
if "," in country:
countryConfidence *= 0.5
# input
parser = argparse.ArgumentParser()
parser.add_argument("-in", dest="INPUT_FILE", default="data/processed/MexicoAndCentralAmerica_cleaned.csv", help="File generated by clean_data.py")
parser.add_argument("-out", dest="OUTPUT_FILE", default="data/processed/MexicoAndCentralAmerica_geotag.csv", help="Output csv file")
a = parser.parse_args()
# Make sure output dirs exist
io.makeDirectories([a.OUTPUT_FILE])
fieldNames, items = io.readCsv(a.INPUT_FILE)
itemCount = len(items)
items = [item for item in items if len(item["Locale"].strip()) > 0 and len(item["Country"].strip()) > 0]
for i, item in enumerate(items):
items[i]["LookupString"] = item["Locale"]
lookupTable = lu.createLookup(items, "LookupString")
values = [item["LookupString"] for item in items]
counter = collections.Counter(values)
counts = counter.most_common()
rows = []
for value, count in counts:
if len(str(value).strip()) < 1:
continue
row = {}
row["geoname"] = value
item = lookupTable[value]
row["id"] = item["Id"]
row["country"] = item["Country"]
"items": timelineValues
}
# Category key
keys["categories"] = {
"type": "legend",
"parent": "#legend-container",
"items": categories
}
yearRange = [timelineValues[0]["year"], timelineValues[-1]["year"]]
outjson["keys"] = keys
# Generate content/Stories
validStories = {}
if "stories" in config:
itemLookup = lu.createLookup(items, "_id")
stories = config["stories"]
for key, story in stories.items():
# determine which item to highlight for this story
hotspotItemIndex = -1
if "itemId" in story and story["itemId"] in itemLookup:
hotspotItemIndex = itemLookup[story["itemId"]]["index"]
else:
# retrieve the story-specific items
storyItems = lu.filterByQueryString(items, story["query"]) if "query" in story else items[:]
# limit the results if specified
if "limit" in story and len(storyItems) > story["limit"]:
storyItems = storyItems[:story["limit"]]
def getSphereCategoryTimelineLayout(userOptions={}):
global items
global sets
cfg = {"layout": "spheres"}
categoryCol = "category"
yearCol = "year"
if yearCol not in items[0]:
print(
"Could not find column %s in items, please add this column to metadata cols with 'type' = 'int'"
% yearCol)
sys.exit()
if categoryCol not in sets:
print(
"Could not find column %s in sets, please add this column to metadata cols with 'asIndex' = true"
% categoryCol)
sys.exit()
categorySet = sets[categoryCol]
categoryCount = len(categorySet)
dimensions = 3
groups = lu.groupList(items, yearCol) # group by year
groups = sorted(groups, key=lambda group: group[yearCol])
years = [item[yearCol] for item in items]
minYear = min(years)
maxYear = max(years) + 1
nUnit = 1.0 / (maxYear - minYear)
# determine category sphere count range
minCount = 9999999999
maxCount = 0
for i, group in enumerate(groups):
subgroups = lu.groupList(group["items"],
categoryCol) # group by category
for subgroup in subgroups:
minCount = min(minCount, subgroup["count"])
maxCount = max(maxCount, subgroup["count"])
groups[i]["categoryGroups"] = subgroups
# assign position values
values = np.zeros(len(items) * dimensions)
for i, group in enumerate(groups):
z = mu.norm(
group[yearCol],
(minYear,
maxYear)) + nUnit * 0.5 # place spheres in the center of the year
subgroups = group["categoryGroups"]
subgroupLookup = lu.createLookup(subgroups, categoryCol)
for j, category in enumerate(categorySet):
x = 1.0 - 1.0 * j / (categoryCount - 1)
categoryKey = str(j)
if categoryKey in subgroupLookup:
subgroup = subgroupLookup[categoryKey]
y = mu.norm(subgroup["count"], (minCount, maxCount))
y = mu.lerp((0.01, 1.0), y)
for catItem in subgroup["items"]:
itemIndex = catItem["index"]
values[itemIndex * dimensions] = round(x, PRECISION)
values[itemIndex * dimensions + 1] = round(y, PRECISION)
values[itemIndex * dimensions + 2] = round(z, PRECISION)
values = values.tolist()
return (cfg, values)
def getSphereCategoryTimelineLayout(userOptions={}):
global items
global categories
cfg = {
"layout": "spheres"
}
categoryCol = "category"
yearCol = "year"
if yearCol not in items[0]:
print("`dateColumn` needs to be set in config yml to support timelineTracks layout")
return (False, False)
if categoryCol not in items[0]:
print("`groupByColumn` needs to be set in config yml to support timelineTracks layout")
return (False, False)
categoryCount = len(categories)
dimensions = 3
groups = lu.groupList(items, yearCol) # group by year
groups = sorted(groups, key=lambda group: group[yearCol])
years = [item[yearCol] for item in items]
minYear = min(years)
maxYear = max(years) + 1
nUnit = 1.0 / (maxYear-minYear)
# determine category sphere count range
minCount = 9999999999
maxCount = 0
for i, group in enumerate(groups):
subgroups = lu.groupList(group["items"], categoryCol) # group by category
for subgroup in subgroups:
minCount = min(minCount, subgroup["count"])
maxCount = max(maxCount, subgroup["count"])
groups[i]["categoryGroups"] = subgroups
# assign position values
values = np.zeros(len(items) * dimensions)
for i, group in enumerate(groups):
z = mu.norm(group[yearCol], (minYear, maxYear)) + nUnit*0.5 # place spheres in the center of the year
subgroups = group["categoryGroups"]
subgroupLookup = lu.createLookup(subgroups, categoryCol)
for j, category in enumerate(categories):
x = 1.0 - 1.0 * j / (categoryCount-1)
categoryKey = category["text"]
if categoryKey in subgroupLookup:
subgroup = subgroupLookup[categoryKey]
y = mu.norm(subgroup["count"], (minCount, maxCount))
y = mu.lerp((0.01, 1.0), y)
for catItem in subgroup["items"]:
itemIndex = catItem["index"]
cy = y
# a bit of a hack to ensure highighted items are visible
if itemHasStory(catItem):
cy = y + 1.25
values[itemIndex*dimensions] = round(x, PRECISION)
values[itemIndex*dimensions+1] = round(cy, PRECISION)
values[itemIndex*dimensions+2] = round(z, PRECISION)
values = values.tolist()
return (cfg, values)
# pprint(xLabels)
# pprint(yLabels)
itemCount = len(items)
for i, item in enumerate(items):
items[i]["index"] = i
# First group by X
groupedItems = lu.groupList(items, a.X_AXIS)
# Then by Y
maxGroupItemCount = 0
for i, xgroup in enumerate(groupedItems):
ygroups = lu.groupList(xgroup["items"], a.Y_AXIS)
maxGroupItemCount = max(maxGroupItemCount, max(group["count"] for group in ygroups))
groupedItems[i]["items"] = lu.createLookup(ygroups, a.Y_AXIS)
# Debug with matplotlib
if a.PLOT:
import matplotlib.pyplot as plt
yGroups = [[0]*xLabelCount for ygroup in yLabels]
for i, xgroup in enumerate(groupedItems):
for j, yLabel in enumerate(yLabels):
count = 0
if yLabel in xgroup["items"]:
count = len(xgroup["items"][yLabel]["items"])
yGroups[j][i] = count
bars = []
for i, yGroup in enumerate(yGroups):
bar = None
if i > 0:
itemCount = len(items)
for i, item in enumerate(items):
items[i]["LookupString"] = ""
# only lookup items that have country and locale with values
if len(item["Country"]) < 1 or len(item[LOCALE_FIELD]) < 1:
continue
items[i]["LookupString"] = item[LOCALE_FIELD] + ", " + item["Country"]
locales = []
localeLookup = {}
if os.path.isfile(a.CACHE_FILE):
_, locales = io.readCsv(a.CACHE_FILE)
localeLookup = lu.createLookup(locales, "LookupString")
if "GeoName" not in fieldNames:
fieldNames.append("GeoName")
values = [item["LookupString"] for item in items]
counter = collections.Counter(values)
counts = counter.most_common()
total = len(counts)
geolocator = Nominatim(user_agent=a.USER_AGENT_STRING)
for i, c in enumerate(counts):
value, count = c
if len(str(value).strip()) < 1: