315 lines
11 KiB
Python
315 lines
11 KiB
Python
import csv
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from datetime import datetime
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from matplotlib import pyplot
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def counts(lst):
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counts = {}
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for v in lst:
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if not v in counts:
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counts[v] = 0
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counts[v] += 1
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return counts
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class Hist:
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def __init__(self, firstcolumn):
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self.key = "\"" + firstcolumn + "\""
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self.dictionary = {}
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self.key = ""
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def add(self, key, value):
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if not key in self.dictionary:
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self.dictionary[key] = []
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self.dictionary[key].append(value)
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def values(self):
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allV = []
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for v in self.dictionary.values():
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allV += list(set(v))
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return list(set(allV))
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def keys(self):
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return self.dictionary.keys()
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def get(self, key):
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if key in self.dictionary:
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return self.dictionary[key]
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return None
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# Returns (keys, values.map(f)). To be used with e.g. pyplot.plot
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def map(self, f):
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vals = []
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keys = self.keys()
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for key in keys:
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vals.append(f(self.get(key)))
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return vals
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def mapcumul(self, f, add, zero):
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vals = []
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running_value = zero
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keys = self.keys()
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for key in keys:
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v = f(self.get(key))
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running_value = add(running_value, v)
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vals.append(running_value)
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return vals
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def csv(self):
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csv = self.key + "," + ",".join(self.values())
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header = self.values()
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for k in self.dictionary.keys():
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csv += k
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values = counts(self.dictionary[k])
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for head in header:
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if head in values:
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csv += "," + str(values[head])
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else:
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csv += ",0"
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csv += "\n"
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return csv
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def __str__(self):
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return str(self.dictionary)
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def build_hist(stats, keyIndex, valueIndex):
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hist = Hist("date")
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c = 0
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for row in stats:
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c += 1
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hist.add(row[keyIndex], row[valueIndex])
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return hist
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def as_date(str):
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return datetime.strptime(str, "%Y-%m-%d")
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def cumulative_users(stats):
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users_hist = build_hist(stats, 0, 1)
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all_users_per_day = users_hist.mapcumul(
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lambda users: set(users),
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lambda a, b: a.union(b),
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set([])
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)
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cumul_uniq = list(map(len, all_users_per_day))
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unique_per_day = users_hist.map(lambda users: len(set(users)))
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new_users = [0]
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for i in range(len(cumul_uniq) - 1):
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new_users.append(cumul_uniq[i + 1] - cumul_uniq[i])
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dates = map(as_date, users_hist.keys())
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return list(dates), cumul_uniq, list(unique_per_day), list(new_users)
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def pyplot_init():
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pyplot.figure(figsize=(14, 8), dpi=200)
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pyplot.xticks(rotation='vertical')
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pyplot.tight_layout()
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def create_usercount_graphs(stats, extra_text=""):
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print("Creating usercount graphs " + extra_text)
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dates, cumul_uniq, unique_per_day, new_users = cumulative_users(stats)
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total = cumul_uniq[-1]
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pyplot_init()
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pyplot.fill_between(dates, unique_per_day, label='Unique contributors')
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pyplot.fill_between(dates, new_users, label='First time contributor via MapComplete')
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pyplot.legend()
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pyplot.title("Unique contributors" + extra_text + ' with MapComplete (' + str(total) + ' contributors)')
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pyplot.ylabel("Number of unique contributors")
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pyplot.xlabel("Date")
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pyplot.savefig("Contributors" + extra_text + ".png", dpi=400, facecolor='w', edgecolor='w', bbox_inches='tight')
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pyplot_init()
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pyplot.plot(dates, cumul_uniq, label='Cumulative unique contributors')
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pyplot.legend()
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pyplot.title("Cumulative unique contributors" + extra_text + " with MapComplete - " + str(total) + " contributors")
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pyplot.ylabel("Number of unique contributors")
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pyplot.xlabel("Date")
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pyplot.savefig("CumulativeContributors" + extra_text + ".png", dpi=400, facecolor='w', edgecolor='w',
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bbox_inches='tight')
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def create_theme_breakdown(stats, fileExtra="", cutoff=5):
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print("Creating theme breakdown " + fileExtra)
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themeCounts = {}
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for row in stats:
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theme = row[3].lower()
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if theme in theme_remappings:
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theme = theme_remappings[theme]
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if theme in themeCounts:
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themeCounts[theme] += 1
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else:
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themeCounts[theme] = 1
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themes = list(themeCounts.items())
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if len(themes) == 0:
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print("No entries found for theme breakdown (extra: " + str(fileExtra) + ")")
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return
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themes.sort(key=lambda kv: kv[1], reverse=True)
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other_count = sum([theme[1] for theme in themes if theme[1] < cutoff])
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themes_filtered = [theme for theme in themes if theme[1] >= cutoff]
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keys = list(map(lambda kv: kv[0] + " (" + str(kv[1]) + ")", themes_filtered))
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values = list(map(lambda kv: kv[1], themes_filtered))
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total = sum(map(lambda kv: kv[1], themes))
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first_pct = themes[0][1] / total;
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if other_count > 0:
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keys.append("other")
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values.append(other_count)
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pyplot_init()
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pyplot.pie(values, labels=keys, startangle=(90 - 360 * first_pct / 2))
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pyplot.title("MapComplete changes per theme" + fileExtra + " - " + str(total) + " total changes")
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pyplot.savefig("Theme distribution" + fileExtra + ".png", dpi=400, facecolor='w', edgecolor='w',
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bbox_inches='tight')
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return themes
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def cumulative_changes_per(contents, index, subject, filenameextra="", cutoff=5, cumulative=True):
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print("Creating graph about " + subject + filenameextra)
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themes = Hist("date")
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dates_per_theme = Hist("theme")
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all_themes = set()
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for row in contents:
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th = row[index]
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all_themes.add(th)
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themes.add(as_date(row[0]), th)
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dates_per_theme.add(th, row[0])
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per_theme_count = list(zip(dates_per_theme.keys(), dates_per_theme.map(len)))
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# PerThemeCount gives the most popular theme first
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per_theme_count.sort(key=lambda kv: kv[1], reverse=False)
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values_to_show = [] # (theme name, value to fill between - this is stacked, with the first layer to print last)
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running_totals = None
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other_total = 0
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other_theme_count = 0
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other_cumul = None
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for kv in per_theme_count:
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theme = kv[0]
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total_for_this_theme = kv[1]
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if cumulative:
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edits_per_day_cumul = themes.mapcumul(
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lambda themes_for_date: len([x for x in themes_for_date if theme == x]),
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lambda a, b: a + b, 0)
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else:
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edits_per_day_cumul = themes.map(lambda themes_for_date: len([x for x in themes_for_date if theme == x]))
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if (not cumulative) or (running_totals is None):
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running_totals = edits_per_day_cumul
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else:
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running_totals = list(map(lambda ab: ab[0] + ab[1], zip(running_totals, edits_per_day_cumul)))
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if total_for_this_theme >= cutoff:
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values_to_show.append((theme, running_totals))
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else:
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other_total += total_for_this_theme
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other_theme_count += 1
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if other_cumul is None:
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other_cumul = edits_per_day_cumul
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else:
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other_cumul = list(map(lambda ab: ab[0] + ab[1], zip(other_cumul, edits_per_day_cumul)))
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keys = list(themes.keys())
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values_to_show.reverse()
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values_to_show.append(("other", other_cumul))
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totals = dict(per_theme_count)
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total = sum(totals.values())
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totals["other"] = other_total
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pyplot_init()
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for kv in values_to_show:
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if kv[1] is None:
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continue # No 'other' graph
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msg = kv[0] + " (" + str(totals[kv[0]]) + ")"
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if kv[0] == "other":
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msg = str(other_theme_count) + " small " + subject + "s (" + str(other_total) + " changes)"
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if cumulative:
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pyplot.fill_between(keys, kv[1], label=msg)
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else:
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print("Keys:"+str(keys)+" "+str(kv[1]))
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pyplot.plot(keys, kv[1], label=msg)
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if cumulative:
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cumulative_txt = "Cumulative changesets"
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else:
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cumulative_txt = "Changesets"
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pyplot.title(cumulative_txt + " per " + subject + filenameextra + " (" + str(total) + " changesets)")
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pyplot.legend(loc="upper left", ncol=3)
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pyplot.savefig(cumulative_txt + " per " + subject + filenameextra + ".png")
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def contents_where(contents, index, starts_with, invert=False):
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for row in contents:
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if row[index].startswith(starts_with) is not invert:
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yield row
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def create_graphs(contents):
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create_usercount_graphs(contents)
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create_theme_breakdown(contents)
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cumulative_changes_per(contents, 3, "theme", cutoff=10)
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cumulative_changes_per(contents, 3, "theme", cutoff=10, cumulative=False)
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cumulative_changes_per(contents, 1, "contributor", cutoff=15)
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cumulative_changes_per(contents, 2, "language", cutoff=1)
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cumulative_changes_per(contents, 4, "version number", cutoff=1)
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cumulative_changes_per(contents, 8, "host", cutoff=1)
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currentYear = datetime.now().year
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for year in range(2020, currentYear + 1):
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contents_filtered = list(contents_where(contents, 0, str(year)))
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extratext = " in " + str(year)
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create_usercount_graphs(contents_filtered, extratext)
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create_theme_breakdown(contents_filtered, extratext)
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cumulative_changes_per(contents_filtered, 3, "theme", extratext, cutoff=5)
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cumulative_changes_per(contents_filtered, 3, "theme", extratext, cutoff=5, cumulative=False)
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cumulative_changes_per(contents_filtered, 1, "contributor", extratext, cutoff=10)
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cumulative_changes_per(contents_filtered, 2, "language", extratext, cutoff=1)
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cumulative_changes_per(contents_filtered, 4, "version number", extratext, cutoff=1, cumulative=False)
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cumulative_changes_per(contents_filtered, 8, "host", extratext, cutoff=1)
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theme_remappings = {
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"metamap": "maps",
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"groen": "buurtnatuur",
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"wiki:mapcomplete/fritures": "fritures",
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"wiki:MapComplete/Fritures": "fritures",
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"lits": "lit",
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"pomp": "cyclofix",
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"wiki:user:joost_schouppe/campersite": "campersite",
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"wiki-user-joost_schouppe-geveltuintjes": "geveltuintjes",
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"wiki-user-joost_schouppe-campersite": "campersites",
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"wiki-User-joost_schouppe-campersite": "campersites",
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"wiki-User-joost_schouppe-geveltuintjes": "geveltuintjes",
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"wiki:User:joost_schouppe/campersite": "campersites",
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"https://raw.githubusercontent.com/osmbe/play/master/mapcomplete/geveltuinen/geveltuinen.json": "geveltuintjes"
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}
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def clean_input(contents):
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for row in contents:
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theme = row[3].strip().strip("\"").lower()
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if theme == "null":
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# The theme metadata has only been set later on - we fetch this from the comment
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i = row[7].rfind("#")
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theme = row[7][i + 1:-1].lower()
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if theme in theme_remappings:
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theme = theme_remappings[theme]
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row[3] = theme
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row[4] = row[4].strip().strip("\"")[0:len("MapComplete x.x.x")]
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yield [data.strip().strip("\"") for data in row]
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def main():
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print("Creating graphs...")
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with open('stats.csv', newline='') as csvfile:
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stats = list(clean_input(csv.reader(csvfile, delimiter=',', quotechar='"')))
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print("Found " + str(len(stats)) + " changesets")
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create_graphs(stats)
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print("All done!")
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# pyplot.fill_between(range(0,5), [1,2,3,3,2],)
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# pyplot.show()
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main()
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