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figures_functions.py
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figures_functions.py
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import matplotlib.pyplot as plt
import powerlaw
import powerlaw
from powerlaw import plot_pdf, Fit
import json
import numpy as np
st_parameters = {
"xylabel_size":14,
"xyticks_size": 12,
"legend_size":12,
"title_size":16,
"line_w":3,
}
def plot_data_fit(data, xlabel, ylabel, fitting="lognormal", tip="data", color="red"):
data = [x for x in data if x>0]
plot_pdf(data, linestyle=':',linewidth=st_parameters["line_w"]+2, label=tip, color=color)
fit = Fit(data, xmin=min(data), discrete=False)
if fitting=='powerlaw':
fit.power_law.plot_pdf( linestyle='--', color=color, label = '%s-power-law'%tip)
elif fitting=='lognormal':
fit.lognormal.plot_pdf( linestyle='--', linewidth=st_parameters["line_w"], color=color, label = 'lognormal fit')
#print(fit.lognormal.mu, fit.lognormal.sigma)
elif fitting =='pl+ln':
fit.power_law.plot_pdf( linestyle='--',color=color, label = '%s-power-law'%tip,)
fit.lognormal.plot_pdf( linestyle='-', color=color, label = '%s-lognormal'%tip)
plt.xlabel(xlabel, fontsize=st_parameters["xylabel_size"])
plt.ylabel(ylabel, fontsize=st_parameters["xylabel_size"])
plt.xticks(fontsize=st_parameters["xyticks_size"])
plt.yticks(fontsize=st_parameters["xyticks_size"])
plt.legend(ncol=1, fontsize=st_parameters["legend_size"], frameon=False)
def plot_line(data, xlabel, ylabel, color, label):
plt.plot(data, lw=st_parameters["line_w"], color=color, label=label)
plt.xlabel(xlabel, fontsize=st_parameters["xylabel_size"])
plt.ylabel(ylabel, fontsize=st_parameters["xylabel_size"])
plt.xticks(fontsize=st_parameters["xyticks_size"])
plt.yticks(fontsize=st_parameters["xyticks_size"])
def plot_rate_size(data, xlabel, ylabel, color):
plt.plot(data[:,0],data[:,1], '.', lw=st_parameters["line_w"], color=color)
plt.xlabel(xlabel, fontsize=st_parameters["xylabel_size"])
plt.ylabel(ylabel, fontsize=st_parameters["xylabel_size"])
plt.xticks(fontsize=st_parameters["xyticks_size"])
plt.yticks(fontsize=st_parameters["xyticks_size"])
#plt.legend(ncol=1, fontsize=st_parameters["legend_size"], frameon=False)
plt.xscale('log')
def plot(dictionary, keymin, keymax, xlabel, ylabel, color_dict):
keys = sorted([int(x) for x in list(dictionary.keys())])
for key in keys:
if int(key)>=keymin and int(key)<=keymax:
data = dictionary[str(key)]
data = [x for x in data if x>0]
plot_pdf(data, linestyle=':',linewidth=st_parameters["line_w"]+2, label=key, )#color=color_dict[str(key)])
plt.xlabel(xlabel, fontsize=st_parameters["xylabel_size"])
plt.ylabel(ylabel, fontsize=st_parameters["xylabel_size"])
plt.xticks(fontsize=st_parameters["xyticks_size"])
plt.yticks(fontsize=st_parameters["xyticks_size"])
plt.legend(ncol=5, fontsize=st_parameters["legend_size"], bbox_to_anchor=(2, -0.3), frameon=False)
#plt.legend(ncol=5, fontsize=12, bbox_to_anchor=(2, -0.3), frameon=False)
def plot_data_model(data, model, xlabel, ylabel, color):
data = [x for x in data if x>0]
model_p = [x for x in model[0] if x>0]
plot_pdf(data, linestyle=":", linewidth=st_parameters["line_w"]+2, label="data", color=color)
plot_pdf(model_p, linestyle='--',color=color, lw=st_parameters["line_w"], label = "pa=%s\n pg=%s\n paff=%s"%(model[1][0], model[1][1], model[1][2]))
plt.xlabel(xlabel, fontsize=st_parameters["xylabel_size"])
plt.ylabel(ylabel, fontsize=st_parameters["xylabel_size"])
plt.xticks(fontsize=st_parameters["xyticks_size"])
plt.yticks(fontsize=st_parameters["xyticks_size"])
plt.legend(ncol=1, fontsize=st_parameters["legend_size"], frameon=False)
def plot_sizes_rates_in_row(data, year1, year2, color_dict):
lab = {"cityLondon": "Meetup: London", "cityNY": "Meetup: New York", "reddit2017": "Subreddits", "reddit2012": "Subreddits", "reddit2012a": "Subreddits"}
xlab = {"sizes": r"$Size/Size_0$", "logrates": r"$Lograte/Lograte_0$"}
ylab = {"sizes": r"$P(Size/Size_0)$", "logrates": r"$P(Lograte/Lograte_0)$"}
parameters = list(data.keys())
plt.figure(figsize = (10, 6))
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.4, hspace=0.4)
i = 1
for param in parameters:
communities = list(data[param].keys())
xlabel = xlab[param];
for category in communities:
plt.subplot(2,3,i)
dictionary = data[param][category]
if i==1 or i==4:
ylabel = ylab[param]
else:
ylabel = ""
plot(dictionary, year1, year2, xlabel, ylabel, color_dict )
if i!=5:
plt.legend().set_visible(False)
if i<4:
plt.title(lab[category], fontsize=st_parameters["title_size"])
i+=1
def plot_statistics_row(data, color_dict):
lab = {"cityLondon": "Meetup: London", "cityNY": "Meetup: New York", "reddit2017": "Subreddits", "reddit2012": "Subreddits", "reddit2012a": "Subreddits"}
xlab = {"p_sizes": r"$Size$", "p_logrates": r"$Lograte$", "Ngroups":"Time(months)", "rate_size": "Size"}
ylab = {"p_sizes": r"$P(Size)$", "p_logrates": r"$P(Lograte)$", "Ngroups":"N groups", "rate_size":"LogRate"}
parameters = list(data.keys())
plt.figure(figsize = (10, 12))
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.4, hspace=0.4)
i = 1
for param in parameters:
communities = list(data[param].keys())
for category in communities:
plt.subplot(4,3,i)
if i<4:
plt.title(lab[category], fontsize=st_parameters["title_size"])
dictionary = data[param][category]
if i==1 or i==4 or i==7 or i==10:
ylabel=ylab[param]
else:ylabel = " "
if param[0]=="p":
plot_data_fit(dictionary, xlab[param], ylabel, color=color_dict[category])
if (i!=4) and (i!=7):
plt.legend().set_visible(False)
else:
if param=="Ngroups":
plot_line(dictionary, xlab[param], ylabel, color_dict[category], "")
else:
if param=="rate_size":
plot_rate_size(dictionary, xlab[param], ylabel, color=color_dict[category])
i+=1
def plot_model_and_data_row(data_dict, color_dict):
plt.figure(figsize=(10, 7))
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.4, hspace=0.4)
lab = {"cityLondon": "Meetup: London", "cityNY": "Meetup: New York", "reddit2017": "Subreddits",
"reddit2012": "Subreddits", "reddit2012a": "Subreddits"}
xlab = {"sizes": r"$Size/Size_0$", "logrates": r"$Lograte/Lograte_0$", "newusers":"time(months)"}
ylab = {"sizes": r"$P(Size/Size_0)$", "logrates": r"$P(Lograte/Lograte_0)$", "newusers": "New users"}
i=1
param = "sizes"
data_s = data_dict["%s_data"%param]
data_m = data_dict["%s_model"%param]
comms = list(data_s.keys())
for comm in comms:
plt.subplot(2, 3, i)
xlabel=xlab[param]
if i==1:
ylabel=ylab[param]
else:
ylabel=""
plot_data_model(data_s[comm], data_m[comm], xlabel, ylabel, color_dict[comm])
plt.title(lab[comm], fontsize=st_parameters["title_size"])
i+=1
param = "logrates"
data_s = data_dict["%s_data"%param]
data_m = data_dict["%s_model"%param]
comms = list(data_s.keys())
for comm in comms:
plt.subplot(2, 3, i)
xlabel=xlab[param]
if i==4:
ylabel=ylab[param]
else:
ylabel=""
plot_data_model(data_s[comm], data_m[comm], xlabel, ylabel, color_dict[comm])
i+=1
def plot_time_series(data_dict, color_dict):
plt.figure(figsize=(10, 9))
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.4, hspace=0.4)
lab = {"cityLondon": "Meetup: London", "cityNY": "Meetup: New York", "reddit2017": "Subreddits",
"reddit2012": "Subreddits", "reddit2012a": "Subreddits"}
xlab = {"sizes": r"$Size/Size_0$", "logrates": r"$Lograte/Lograte_0$", "newusers":"time(months)",
"oldusers_totalusers":"time(months)", "newgroups_activeusers":"time(months)"}
ylab = {"sizes": r"$P(Size/Size_0)$", "logrates": r"$P(Lograte/Lograte_0)$", "newusers": "New users",
"oldusers_totalusers":"Old users/Total users", "newgroups_activeusers":"New groups/Active users"}
i=1
param = "newusers"
data_s = data_dict[param]
comms = list(data_s.keys())
for comm in comms:
plt.subplot(3, 3, i)
xlabel= ""
if i==1:
ylabel=ylab[param]
else:
ylabel=""
plot_line(data_s[comm], xlabel, ylabel, color_dict[comm], "")
plt.title(lab[comm], fontsize=st_parameters["title_size"])
i+=1
param = "oldusers_totalusers"
data_s = data_dict[param]
comms = list(data_s.keys())
for comm in comms:
plt.subplot(3, 3, i)
xlabel=""
if i==4:
ylabel=ylab[param]
else:
ylabel=""
med = np.median(data_s[comm])
plot_line(data_s[comm], xlabel, ylabel, color_dict[comm], "pa = %.2f"%med)
plt.legend(fontsize=st_parameters["legend_size"], frameon=False)
i+=1
param = "newgroups_activeusers"
data_s = data_dict[param]
comms = list(data_s.keys())
for comm in comms:
plt.subplot(3, 3, i)
xlabel=xlab[param]
if i==7:
ylabel=ylab[param]
else:
ylabel=""
med = np.median(data_s[comm].dropna())
print(med)
plot_line(data_s[comm], xlabel, ylabel, color_dict[comm], "pg = %.3f"%med)
plt.legend(fontsize=st_parameters["legend_size"], frameon=False)
i+=1