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Commit a00eaaef authored by Ivan Pavlovich's avatar Ivan Pavlovich
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Calculated number of published pubmed articles for ncds with keywords

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dataSources/PubMed/data_num_locale.py
+ 215
− 80
View file @ a00eaaef
......@@ -8,10 +8,34 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../../"
from variables.pubmed import NCDS_MESH_TERM, KEYWORDS_MESH_TERM, KEYWORDS_MESH_SUBHEADING, KEYWORDS_MESH_SITE_PROPOSITION, KEYWORDS_MESH_PROPOSITION
CATEGORIES = [
"KEYWORDS",
"SUBHEADINGS",
"SITE PROPOSITION",
"PROPOSITION"
]
INTERVALS = [
"day",
"week",
"month"
]
DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "./data"))
file_path = f"{DATA_DIR}/save_3_years.json"
def lower_keywords(mesh_terms):
res = []
for _, mesh_term in mesh_terms.items():
if isinstance(mesh_term, list):
res.append([part.lower() for part in mesh_term])
else:
res.append(mesh_term.lower())
return res
def get_date_indices(date, start_date):
delta_days = (date - start_date).days
day_index = delta_days
......@@ -37,26 +61,149 @@ def match_mesh_terms(article_mesh_terms, ncd, keyword):
else:
return False
def init_index(category, counts, ncd, article_date):
start_date = datetime(2022, 1, 1)
day_index, week_index, month_index = get_date_indices(article_date, start_date)
if day_index not in counts[ncd][category]["day"]:
counts[ncd][category]["day"][day_index] = []
if week_index not in counts[ncd][category]["week"]:
counts[ncd][category]["week"][week_index] = []
if month_index not in counts[ncd][category]["month"]:
counts[ncd][category]["month"][month_index] = []
def add_article(article, category, counts, ncd, article_date):
start_date = datetime(2022, 1, 1)
day_index, week_index, month_index = get_date_indices(article_date, start_date)
if article["PMID"] not in counts[ncd][category]["day"][day_index]:
counts[ncd][category]["day"][day_index].append(article["PMID"])
if article["PMID"] not in counts[ncd][category]["week"][week_index]:
counts[ncd][category]["week"][week_index].append(article["PMID"])
if article["PMID"] not in counts[ncd][category]["month"][month_index]:
counts[ncd][category]["month"][month_index].append(article["PMID"])
with open(file_path, "r", encoding="utf-8") as file:
data = json.load(file)
print(len(data))
ncds_mesh_terms = [mesh_term.lower() for ncd, mesh_term in NCDS_MESH_TERM.items()]
keywords_mesh_terms = [mesh_term.lower() for keyword, mesh_term in KEYWORDS_MESH_TERM.items()]
keywords_subheading_mesh_terms = keywords_mesh_terms + [mesh_term.lower() for mesh_term in KEYWORDS_MESH_SUBHEADING]
keywords_site_proposition_mesh_terms = keywords_subheading_mesh_terms + [mesh_term.lower() for mesh_term in KEYWORDS_MESH_SITE_PROPOSITION]
keywords_proposition_mesh_terms = keywords_site_proposition_mesh_terms + [mesh_term.lower() for mesh_term in KEYWORDS_MESH_PROPOSITION]
keywords_mesh_terms = lower_keywords(KEYWORDS_MESH_TERM)
keywords_subheading_mesh_terms = lower_keywords(KEYWORDS_MESH_SUBHEADING)
keywords_site_proposition_mesh_terms = lower_keywords(KEYWORDS_MESH_SITE_PROPOSITION)
keywords_proposition_mesh_terms = lower_keywords(KEYWORDS_MESH_PROPOSITION)
counts = {}
for ncd in ncds_mesh_terms:
counts[ncd] = {
"KEYWORDS" : {
"day": {},
"week": {},
"month": {}
},
"SUBHEADINGS" : {
"day": {},
"week": {},
"month": {}
},
"SITE PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
"PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
}
start_date = datetime(2022, 1, 1)
end_date = datetime(2024, 12, 31)
current_date = start_date
while(current_date < end_date):
day_index, week_index, month_index = get_date_indices(current_date, start_date)
for category in CATEGORIES:
counts[ncd][category]["day"][day_index] = []
counts[ncd][category]["week"][week_index] = []
counts[ncd][category]["month"][month_index] = []
current_date += timedelta(days=1)
counts["ALL"] = {
"KEYWORDS" : {
"day": {},
"week": {},
"month": {}
},
"SUBHEADINGS" : {
"day": {},
"week": {},
"month": {}
},
"SITE PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
"PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
}
start_date = datetime(2022, 1, 1)
end_date = datetime(2024, 12, 31)
current_date = start_date
while(current_date < end_date):
day_index, week_index, month_index = get_date_indices(current_date, start_date)
for category in CATEGORIES:
counts["ALL"][category]["day"][day_index] = []
counts["ALL"][category]["week"][week_index] = []
counts["ALL"][category]["month"][month_index] = []
current_date += timedelta(days=1)
for article in data:
mesh_terms = [mesh_term.lower() for mesh_term in article["MeshTerms"]]
article_date = datetime(int(article["Date"]["Year"]), int(article["Date"]["Month"]), int(article["Date"]["Day"]))
if "ALL" not in counts:
counts["ALL"] = {}
counts["ALL"] = {
"KEYWORDS" : {
"day": {},
"week": {},
"month": {}
},
"SUBHEADINGS" : {
"day": {},
"week": {},
"month": {}
},
"SITE PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
"PROPOSITION" : {
"day": {},
"week": {},
"month": {}
},
}
for ncd in ncds_mesh_terms:
if ncd not in counts:
......@@ -85,104 +232,92 @@ for article in data:
for keyword in keywords_mesh_terms:
if match_mesh_terms(mesh_terms, ncd, mesh_terms):
if match_mesh_terms(mesh_terms, ncd, keyword):
init_index("KEYWORDS", counts, ncd, article_date)
init_index("SUBHEADINGS", counts, ncd, article_date)
init_index("SITE PROPOSITION", counts, ncd, article_date)
init_index("PROPOSITION", counts, ncd, article_date)
article_date = datetime(int(article["Date"]["Year"]), int(article["Date"]["Month"]), int(article["Date"]["Day"]))
add_article(article, "KEYWORDS", counts, ncd, article_date)
add_article(article, "SUBHEADINGS", counts, ncd, article_date)
add_article(article, "SITE PROPOSITION", counts, ncd, article_date)
add_article(article, "PROPOSITION", counts, ncd, article_date)
day_index, week_index, month_index = get_date_indices(article_date, start_date)
init_index("KEYWORDS", counts, "ALL", article_date)
init_index("SUBHEADINGS", counts, "ALL", article_date)
init_index("SITE PROPOSITION", counts, "ALL", article_date)
init_index("PROPOSITION", counts, "ALL", article_date)
if day_index not in counts[ncd]["KEYWORDS"]["day"]:
counts[ncd]["KEYWORDS"]["day"][day_index] = []
if week_index not in counts[ncd]["KEYWORDS"]["week"]:
counts[ncd]["KEYWORDS"]["week"][week_index] = []
if month_index not in counts[ncd]["KEYWORDS"]["month"]:
counts[ncd]["KEYWORDS"]["month"][month_index] = []
if article["PMID"] not in counts[ncd]["KEYWORDS"]["day"][day_index]:
counts[ncd]["KEYWORDS"]["day"][day_index].append(article["PMID"])
if article["PMID"] not in counts[ncd]["KEYWORDS"]["week"][week_index]:
counts[ncd]["KEYWORDS"]["week"][week_index].append(article["PMID"])
if article["PMID"] not in counts[ncd]["KEYWORDS"]["month"][month_index]:
counts[ncd]["KEYWORDS"]["month"][month_index].append(article["PMID"])
add_article(article, "KEYWORDS", counts, "ALL", article_date)
add_article(article, "SUBHEADINGS", counts, "ALL", article_date)
add_article(article, "SITE PROPOSITION", counts, "ALL", article_date)
add_article(article, "PROPOSITION", counts, "ALL", article_date)
for keyword in keywords_subheading_mesh_terms:
if match_mesh_terms(mesh_terms, ncd, mesh_terms):
article_date = datetime(int(article["Date"]["Year"]), int(article["Date"]["Month"]), int(article["Date"]["Day"]))
day_index, week_index, month_index = get_date_indices(article_date, start_date)
if day_index not in counts[ncd]["SUBHEADINGS"]["day"]:
counts[ncd]["SUBHEADINGS"]["day"][day_index] = []
if week_index not in counts[ncd]["SUBHEADINGS"]["week"]:
counts[ncd]["SUBHEADINGS"]["week"][week_index] = []
if match_mesh_terms(mesh_terms, ncd, keyword):
init_index("SUBHEADINGS", counts, ncd, article_date)
init_index("SITE PROPOSITION", counts, ncd, article_date)
init_index("PROPOSITION", counts, ncd, article_date)
if month_index not in counts[ncd]["SUBHEADINGS"]["month"]:
counts[ncd]["SUBHEADINGS"]["month"][month_index] = []
add_article(article, "SUBHEADINGS", counts, ncd, article_date)
add_article(article, "SITE PROPOSITION", counts, ncd, article_date)
add_article(article, "PROPOSITION", counts, ncd, article_date)
if article["PMID"] not in counts[ncd]["SUBHEADINGS"]["day"][day_index]:
counts[ncd]["SUBHEADINGS"]["day"][day_index].append(article["PMID"])
init_index("SUBHEADINGS", counts, "ALL", article_date)
init_index("SITE PROPOSITION", counts, "ALL", article_date)
init_index("PROPOSITION", counts, "ALL", article_date)
if article["PMID"] not in counts[ncd]["SUBHEADINGS"]["week"][week_index]:
counts[ncd]["SUBHEADINGS"]["week"][week_index].append(article["PMID"])
if article["PMID"] not in counts[ncd]["SUBHEADINGS"]["month"][month_index]:
counts[ncd]["SUBHEADINGS"]["month"][month_index].append(article["PMID"])
add_article(article, "SUBHEADINGS", counts, "ALL", article_date)
add_article(article, "SITE PROPOSITION", counts, "ALL", article_date)
add_article(article, "PROPOSITION", counts, "ALL", article_date)
for keyword in keywords_site_proposition_mesh_terms:
if match_mesh_terms(mesh_terms, ncd, mesh_terms):
article_date = datetime(int(article["Date"]["Year"]), int(article["Date"]["Month"]), int(article["Date"]["Day"]))
day_index, week_index, month_index = get_date_indices(article_date, start_date)
if day_index not in counts[ncd]["SITE PROPOSITION"]["day"]:
counts[ncd]["SITE PROPOSITION"]["day"][day_index] = []
if match_mesh_terms(mesh_terms, ncd, keyword):
init_index("SITE PROPOSITION", counts, ncd, article_date)
init_index("PROPOSITION", counts, ncd, article_date)
if week_index not in counts[ncd]["SITE PROPOSITION"]["week"]:
counts[ncd]["SITE PROPOSITION"]["week"][week_index] = []
add_article(article, "SITE PROPOSITION", counts, ncd, article_date)
add_article(article, "PROPOSITION", counts, ncd, article_date)
if month_index not in counts[ncd]["SITE PROPOSITION"]["month"]:
counts[ncd]["SITE PROPOSITION"]["month"][month_index] = []
init_index("SITE PROPOSITION", counts, "ALL", article_date)
init_index("PROPOSITION", counts, "ALL", article_date)
if article["PMID"] not in counts[ncd]["SITE PROPOSITION"]["day"][day_index]:
counts[ncd]["SITE PROPOSITION"]["day"][day_index].append(article["PMID"])
if article["PMID"] not in counts[ncd]["SITE PROPOSITION"]["week"][week_index]:
counts[ncd]["SITE PROPOSITION"]["week"][week_index].append(article["PMID"])
if article["PMID"] not in counts[ncd]["SITE PROPOSITION"]["month"][month_index]:
counts[ncd]["SITE PROPOSITION"]["month"][month_index].append(article["PMID"])
add_article(article, "SITE PROPOSITION", counts, "ALL", article_date)
add_article(article, "PROPOSITION", counts, "ALL", article_date)
for keyword in keywords_proposition_mesh_terms:
if match_mesh_terms(mesh_terms, ncd, mesh_terms):
if match_mesh_terms(mesh_terms, ncd, keyword):
init_index("PROPOSITION", counts, ncd, article_date)
article_date = datetime(int(article["Date"]["Year"]), int(article["Date"]["Month"]), int(article["Date"]["Day"]))
add_article(article, "PROPOSITION", counts, ncd, article_date)
day_index, week_index, month_index = get_date_indices(article_date, start_date)
init_index("PROPOSITION", counts, "ALL", article_date)
if day_index not in counts[ncd]["PROPOSITION"]["day"]:
counts[ncd]["PROPOSITION"]["day"][day_index] = []
add_article(article, "PROPOSITION", counts, "ALL", article_date)
if week_index not in counts[ncd]["PROPOSITION"]["week"]:
counts[ncd]["PROPOSITION"]["week"][week_index] = []
for ncd in ncds_mesh_terms:
for category in CATEGORIES:
for interval in INTERVALS:
counts[ncd][category][interval] = [len(tmp) for key, tmp in counts[ncd][category][interval].items()]
if month_index not in counts[ncd]["PROPOSITION"]["month"]:
counts[ncd]["PROPOSITION"]["month"][month_index] = []
counts[ncd][category][interval] = {
"min": min(counts[ncd][category][interval]),
"max": max(counts[ncd][category][interval]),
"mean": statistics.mean(counts[ncd][category][interval])
}
if article["PMID"] not in counts[ncd]["PROPOSITION"]["day"][day_index]:
counts[ncd]["PROPOSITION"]["day"][day_index].append(article["PMID"])
for category in CATEGORIES:
for interval in INTERVALS:
counts["ALL"][category][interval] = [len(tmp) for key, tmp in counts["ALL"][category][interval].items()]
if article["PMID"] not in counts[ncd]["PROPOSITION"]["week"][week_index]:
counts[ncd]["PROPOSITION"]["week"][week_index].append(article["PMID"])
counts["ALL"][category][interval] = {
"min": min(counts["ALL"][category][interval]),
"max": max(counts["ALL"][category][interval]),
"mean": statistics.mean(counts["ALL"][category][interval])
}
if article["PMID"] not in counts[ncd]["PROPOSITION"]["month"][month_index]:
counts[ncd]["PROPOSITION"]["month"][month_index].append(article["PMID"])
with open(f"{DATA_DIR}/locale_articles_count.json", "w") as json_file:
json.dump(counts, json_file, indent=4)
\ No newline at end of file
dataSources/PubMed/doc/locale_articles_count.json 0 → 100644
+ 632
− 0
View file @ a00eaaef
{
"noncommunicable diseases": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 3,
"mean": 0.20639269406392693
},
"week": {
"min": 0,
"max": 6,
"mean": 1.4394904458598725
},
"month": {
"min": 2,
"max": 12,
"mean": 6.277777777777778
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 3,
"mean": 0.20639269406392693
},
"week": {
"min": 0,
"max": 6,
"mean": 1.4394904458598725
},
"month": {
"min": 2,
"max": 12,
"mean": 6.277777777777778
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 3,
"mean": 0.2328767123287671
},
"week": {
"min": 0,
"max": 6,
"mean": 1.624203821656051
},
"month": {
"min": 2,
"max": 14,
"mean": 7.083333333333333
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 4,
"mean": 0.34885844748858447
},
"week": {
"min": 0,
"max": 8,
"mean": 2.43312101910828
},
"month": {
"min": 4,
"max": 17,
"mean": 10.61111111111111
}
}
},
"diabetes mellitus": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 5,
"mean": 0.7497725204731575
},
"week": {
"min": 1,
"max": 11,
"mean": 5.248407643312102
},
"month": {
"min": 3,
"max": 31,
"mean": 22.27027027027027
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 5,
"mean": 0.7497725204731575
},
"week": {
"min": 1,
"max": 11,
"mean": 5.248407643312102
},
"month": {
"min": 3,
"max": 31,
"mean": 22.27027027027027
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 8,
"mean": 1.0454959053685169
},
"week": {
"min": 2,
"max": 15,
"mean": 7.318471337579618
},
"month": {
"min": 3,
"max": 44,
"mean": 31.054054054054053
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 10,
"mean": 1.4249317561419472
},
"week": {
"min": 3,
"max": 20,
"mean": 9.97452229299363
},
"month": {
"min": 5,
"max": 57,
"mean": 42.32432432432432
}
}
},
"neoplasms": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 16,
"mean": 2.692447679708826
},
"week": {
"min": 2,
"max": 33,
"mean": 18.727848101265824
},
"month": {
"min": 14,
"max": 101,
"mean": 79.97297297297297
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 16,
"mean": 2.692447679708826
},
"week": {
"min": 2,
"max": 33,
"mean": 18.727848101265824
},
"month": {
"min": 14,
"max": 101,
"mean": 79.97297297297297
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 16,
"mean": 2.735213830755232
},
"week": {
"min": 2,
"max": 33,
"mean": 19.025316455696203
},
"month": {
"min": 14,
"max": 101,
"mean": 81.24324324324324
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 21,
"mean": 3.5281818181818183
},
"week": {
"min": 2,
"max": 43,
"mean": 24.563291139240505
},
"month": {
"min": 17,
"max": 127,
"mean": 104.89189189189189
}
}
},
"respiratory tract diseases": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 1,
"mean": 0.02281021897810219
},
"week": {
"min": 0,
"max": 2,
"mean": 0.15822784810126583
},
"month": {
"min": 0,
"max": 3,
"mean": 0.6756756756756757
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 1,
"mean": 0.02281021897810219
},
"week": {
"min": 0,
"max": 2,
"mean": 0.15822784810126583
},
"month": {
"min": 0,
"max": 3,
"mean": 0.6756756756756757
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 1,
"mean": 0.02281021897810219
},
"week": {
"min": 0,
"max": 2,
"mean": 0.15822784810126583
},
"month": {
"min": 0,
"max": 3,
"mean": 0.6756756756756757
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 1,
"mean": 0.0364963503649635
},
"week": {
"min": 0,
"max": 2,
"mean": 0.25316455696202533
},
"month": {
"min": 0,
"max": 3,
"mean": 1.0810810810810811
}
}
},
"cardiovascular diseases": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 5,
"mean": 0.6584699453551912
},
"week": {
"min": 0,
"max": 13,
"mean": 4.575949367088608
},
"month": {
"min": 3,
"max": 40,
"mean": 19.54054054054054
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 5,
"mean": 0.6584699453551912
},
"week": {
"min": 0,
"max": 13,
"mean": 4.575949367088608
},
"month": {
"min": 3,
"max": 40,
"mean": 19.54054054054054
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 5,
"mean": 0.6930783242258652
},
"week": {
"min": 0,
"max": 13,
"mean": 4.8164556962025316
},
"month": {
"min": 3,
"max": 42,
"mean": 20.56756756756757
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 8,
"mean": 1.1474067333939946
},
"week": {
"min": 1,
"max": 24,
"mean": 7.981012658227848
},
"month": {
"min": 5,
"max": 58,
"mean": 34.08108108108108
}
}
},
"mental health": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 8,
"mean": 1.1856232939035487
},
"week": {
"min": 1,
"max": 21,
"mean": 8.246835443037975
},
"month": {
"min": 4,
"max": 52,
"mean": 35.21621621621622
}
},
"SUBHEADINGS": {
"day": {
"min": 0,
"max": 8,
"mean": 1.1856232939035487
},
"week": {
"min": 1,
"max": 21,
"mean": 8.246835443037975
},
"month": {
"min": 4,
"max": 52,
"mean": 35.21621621621622
}
},
"SITE PROPOSITION": {
"day": {
"min": 0,
"max": 8,
"mean": 1.2438580527752503
},
"week": {
"min": 1,
"max": 22,
"mean": 8.651898734177216
},
"month": {
"min": 4,
"max": 55,
"mean": 36.945945945945944
}
},
"PROPOSITION": {
"day": {
"min": 0,
"max": 11,
"mean": 2.1618181818181816
},
"week": {
"min": 1,
"max": 32,
"mean": 15.050632911392405
},
"month": {
"min": 8,
"max": 84,
"mean": 64.27027027027027
}
}
},
"diabetes mellitus, type 1": {
"KEYWORDS": {
"day": {
"min": 0,
"max": 3,
"mean": 0.3072014585232452
},
"week": {
"min": 0,
"max": 8,
"mean": 2.132911392405063
},
"month": {
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\ No newline at end of file
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