def process_data_concept(record):
import aixm
import amxm
aixm = aixm.Aixm()
amxm = amxm.Amxm()
if isinstance(record['Semantic Correspondence'], str):
urn = record['Semantic Correspondence']
urn = urn.strip()
if aixm.is_in_aixm_mapping(urn):
global overlap_aixm_counter
overlap_aixm_counter += 1
if amxm.is_in_amxm_mapping(urn):
global overlap_amxm_counter
overlap_amxm_counter += 1
def process_data_concept(record):
import aixm
import fixm
aixm = aixm.Aixm()
fixm = fixm.Fixm()
if isinstance(record['AIRM Concept Identifier'], str):
urn = record['AIRM Concept Identifier']
urn = urn.strip()
if aixm.is_in_aixm_mapping(urn):
global overlap_aixm_counter
overlap_aixm_counter += 1
if fixm.is_in_fixm_mapping(urn):
global overlap_fixm_counter
overlap_fixm_counter += 1
def create_html():
mapping_pages_directory = "docs/developers/aixm-5.1.1-to-airm-1.0.0"
# creates docs/developers/amxm-2.0.0-to-airm-1.0.0 directory
path = mapping_pages_directory
try:
os.mkdir(path)
except OSError:
print ("Creation of the directory %s failed" % path)
else:
print ("Successfully created the directory %s " % path)
import aixm
aixm = aixm.Aixm()
aixm_mapping_merged_dict = aixm.aixm_mapping_merged_dataframe.to_dict('records')
#Create index page
#creates soup for developers/amxm-2.2.0-to-airm-1.0.0.html using amxm_mapping_template.html
html = open("data/html/templates/AIXM-list-template.html").read()
soup = BeautifulSoup(html, "lxml")
#For each entry
#create table entry
for record in aixm_mapping_merged_dict:
tr = soup.new_tag("tr")
print(record)
print("\n")
td_ic_name = soup.new_tag("td")
if str(record["Information Concept"]) != "missing data" and str(record["Information Concept"]) != "":
if str(record["Data Concept"]) == "missing data" or str(record["Data Concept"]) == "":
url = "aixm-5.1.1-to-airm-1.0.0/"+str(record["Information Concept"])+".html"
text = str(record["Information Concept"])
#print(text)
new_link = soup.new_tag("a")
new_link['href'] = url
new_link['target'] = "_blank"
new_link.string = text
td_ic_name.insert(1,new_link)
td_ic_name["data-order"] = record["Information Concept"]
else:
td_ic_name.string = str(record["Information Concept"])
td_ic_name["data-order"] = record["Information Concept"]
else:
td_ic_name.string = "-"
tr.insert(0,td_ic_name)
td_dc_name = soup.new_tag("td")
if str(record["Data Concept"]) != "missing data" and str(record["Data Concept"]) != "":
url = "aixm-5.1.1-to-airm-1.0.0/"+str(record["Information Concept"])+".html"+"#"+str(record["Data Concept"])
text = str(record["Data Concept"])
#print(text)
new_link = soup.new_tag("a")
new_link['href'] = url
new_link['target'] = "_blank"
new_link.string = text
td_dc_name.insert(1,new_link)
td_dc_name["data-order"] = record["Data Concept"]
else:
td_dc_name.string = "-"
tr.insert(1,td_dc_name)
td_def = soup.new_tag("td")
if str(record["Concept Definition"]) != "missing data":
td_def.string = str(record["Concept Definition"])
else:
td_def.string = "-"
tr.insert(2,td_def)
td_type = soup.new_tag("td")
if str(record["Basic Type"]) != "missing data":
td_type.string = str(record["Basic Type"])
else:
td_type.string = "-"
tr.insert(3,td_type)
#td_dc_type = soup.new_tag("td")
#if str(record["Data Concept's Basic Type"]) != "missing data":
# parts = str(record["Data Concept's Basic Type"]).split(":")
# clean_type = parts[-1]
# url = "amxm-2.0.0-to-airm-1.0.0/"+clean_type+".html"
# text = clean_type
# print(text)
# new_link = soup.new_tag("a")
# new_link['href'] = url
# new_link['target'] = "_blank"
# new_link.string = text
# td_dc_type.insert(1,new_link)
#else:
# td_dc_type = soup.new_tag("td")
# td_dc_type.string = "-"
#tr.insert(3,td_dc_type)
soup.find('tbody').insert(1,tr)
f= open("docs/developers/aixm-5.1.1-to-airm-1.0.0.html","w+")
f.write(soup.prettify())
f.close()
def create_html_pages():
import aixm
import airm
aixm = aixm.Aixm()
airm = airm.Airm()
aixm_info_concepts_dict = aixm.get_information_concepts()
for info_concept in aixm_info_concepts_dict:
if info_concept['Information Concept']!="missing data":
print(info_concept['Information Concept'])
#creates soup for concept page using concept-template.html
html = open("data/html/templates/AIXM-concept-template.html").read()
soup = BeautifulSoup(html, "lxml")
#span = soup.new_tag("span")
#span.string = str(info_concept['Information Concept'])
#soup.find(id="BC_INFO_CONCEPT_NAME").insert(0,span)span = soup.new_tag("span")
#span.string = str(info_concept['Information Concept'])
soup.title.string = str(info_concept['Information Concept'])+" - AIXM 5.1.1 to AIRM 1.0.0 | AIRM.aero"
soup.find(text="FIXM_CLASS_NAME_BC").replace_with(str(info_concept['Information Concept']))
definition = str(info_concept["Concept Definition"])
definition = definition.replace("Definition: ","")
soup.find(text="FIXM_CLASS_DEFINITION").replace_with(definition)
h2 = soup.new_tag("h2")
h2.string = str(info_concept['Information Concept'])
soup.find(id="INFO_CONCEPT_NAME").insert(0,h2)
code = soup.new_tag("code")
datac_identifier = info_concept['Concept Identifier']
code.string = datac_identifier
code["class"] = "text-secondary"
soup.find(id="INFO_CONCEPT_NAME").insert(1,code)
traces = aixm.get_traces_by_info_concept(info_concept['Information Concept'])
for trace in traces:
print('\t'+str(trace['Data Concept']))
tr = soup.new_tag("tr")
if str(trace["Data Concept"]) != "":
td_dc_name = soup.new_tag("td")
url = "#"+str(trace["Data Concept"])
text = str(trace["Data Concept"])
new_link = soup.new_tag("a")
new_link['href'] = url
new_link.string = text
td_dc_name.insert(1,new_link)
tr.insert(1,td_dc_name)
if trace["Concept Definition"] != "":
td_def = soup.new_tag("td")
definition = str(trace["Concept Definition"])
definition = definition.replace("Definition: ","")
td_def.string = definition
tr.insert(2,td_def)
soup.find(id="DATA_CONCEPTS_LIST").insert(1,tr)
for trace in traces:
property_div = soup.new_tag("div")
property_div["style"] = "border: 0.5px solid #b2b2b2;border-radius: 4px;box-shadow: 2px 2px #b2b2b2;padding: 15px;padding-bottom: 0px; margin-bottom: 30px"
h3 = soup.new_tag("h3")
h3.string = str(trace["Data Concept"])
h3["id"] = str(trace["Data Concept"])
h3["style"] = "padding-top: 120px; margin-top: -120px;"
property_div.insert(0,h3)
code = soup.new_tag("code")
identifier = trace['Concept Identifier']
code.string = identifier
code["class"] = "text-secondary"
property_div.insert(1,code)
p = soup.new_tag("p")
definition = str(trace["Concept Definition"])
definition = definition.replace("Definition: ","")
p.string = definition
br = soup.new_tag("br")
p.insert(2,br)
property_div.insert(2,p)
sc_h5 = soup.new_tag("h5")
sc_h5.string = "Semantic Correspondence"
sc_h5['style'] = "margin-top: 40px;"
property_div.insert(3,sc_h5)
sc_div = soup.new_tag("div")
sc_div["class"] = "table-responsive"
sc_table = soup.new_tag("table")
sc_table["class"] = "table"
sc_thead = soup.new_tag("thead")
tr = soup.new_tag("tr")
th = soup.new_tag("th")
th.string = "AIRM Concept"
tr.insert(1,th)
th = soup.new_tag("th")
th.string = "Definition"
tr.insert(2,th)
sc_thead.insert(1,tr)
sc_table.insert(1,sc_thead)
tbody = soup.new_tag("tbody")
#for each insert row
print('\t\tSemantic Corresponce:')
if str(trace['AIRM Concept Identifier']) == "missing data":
tr = soup.new_tag("tr")
td = soup.new_tag("td")
line = str(trace['Special Case'])
url = create_url(line)
text = create_name(line)
a = soup.new_tag("a")
a['href'] = url
a['target'] = "_blank"
a.string = text
a["data-toggle"] = "tooltip"
a["data-placement"] = "right"
a["title"] = line
td.insert(1,a)
tr.insert(1,td)
td = soup.new_tag("td")
airm_entry = airm.load_and_find_urn(line)
td.string = airm_entry["definition"]
tr.insert(2,td)
tbody.insert(1,tr)
else:
sem_correspondences = str(trace['AIRM Concept Identifier']).split('\n')
for line in sem_correspondences:
print('\t\t\t'+line)
tr = soup.new_tag("tr")
td = soup.new_tag("td")
url = create_url(line)
text = create_name(line)
a = soup.new_tag("a")
a['href'] = url
a['target'] = "_blank"
a.string = text
a["data-toggle"] = "tooltip"
a["data-placement"] = "right"
a["title"] = line
td.insert(1,a)
tr.insert(1,td)
td = soup.new_tag("td")
airm_entry = airm.load_and_find_urn(line)
td.string = airm_entry["definition"]
tr.insert(2,td)
tbody.insert(1,tr)
sc_table.insert(2,tbody)
sc_div.insert(1,sc_table)
property_div.insert(4,sc_div)
if str(trace["Rationale"]) != "missing data":
h5 = soup.new_tag("h5")
h5.string = "Rationale"
property_div.insert(5,h5)
p = soup.new_tag("p")
p.string = str(trace["Rationale"])
print('Rationale:'+str(trace["Rationale"]))
property_div.insert(6,p)
if str(trace["Remarks"]) != "missing data":
notes_h5 = soup.new_tag("h5")
notes_h5.string = "Remarks"
property_div.insert(7,notes_h5)
p = soup.new_tag("p")
p.string = str(trace["Remarks"])
print('Remarks:'+str(trace["Remarks"]))
property_div.insert(8,p)
top_link_p = soup.new_tag("p")
new_link = soup.new_tag("a")
new_link['href'] = "#top"
new_icon = soup.new_tag("i")
new_icon['class'] = "fa fa-arrow-circle-up"
new_icon["data-toggle"] = "tooltip"
new_icon["data-placement"] = "left"
new_icon["title"] = "Top of page"
new_link.insert(1,new_icon)
top_link_p.insert(1,new_link)
top_link_p['class'] = "text-right"
property_div.insert(9,top_link_p)
soup.find(id="DATA_CONCEPTS_DETAIL").insert(1,property_div)
f= open("docs/developers/aixm-5.1.1-to-airm-1.0.0/"+str(info_concept['Information Concept'])+".html","w+")
f.write(soup.prettify())
f.close()
def create_connected_index():
df_connected_index_cols = [
"airm_urn", "model_name", "concept_name", "concept_id", "concept_type"
]
df_connected_index_rows = []
import fixm
fixm = fixm.Fixm()
fixm_mapping_dict = fixm.fixm_mapping_dataframe.to_dict('records')
for entry in fixm_mapping_dict:
sem_correspondences = str(entry['Semantic Correspondence']).split('\n')
for line in sem_correspondences:
urn = line
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"FIXM 4.2.0",
"concept_name":
entry["Data Concept"],
"concept_id":
entry["Identifier"],
"concept_type":
entry["Type"]
})
import amxm
amxm = amxm.Amxm()
amxm_mapping_dict = amxm.amxm_mapping_dataframe.to_dict('records')
for entry in amxm_mapping_dict:
sem_correspondences = str(entry['AIRM Concept Identifier']).split('\n')
for line in sem_correspondences:
urn = line
if str(entry["Data Concept"]) == "missing data":
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AMXM 2.0.0",
"concept_name":
entry["Information Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
else:
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AMXM 2.0.0",
"concept_name":
entry["Data Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
amxm_mapping_dict = amxm.amxm_mapping_enum_dataframe.to_dict('records')
for entry in amxm_mapping_dict:
sem_correspondences = str(entry['AIRM Concept Identifier']).split('\n')
for line in sem_correspondences:
urn = line
if str(entry["Data Concept"]) == "missing data":
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AMXM 2.0.0",
"concept_name":
entry["Information Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
else:
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AMXM 2.0.0",
"concept_name":
entry["Data Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
import aixm
aixm = aixm.Aixm()
aixm_mapping_merged_dict = aixm.aixm_mapping_merged_dataframe.to_dict(
'records')
for entry in aixm_mapping_merged_dict:
sem_correspondences = str(entry['AIRM Concept Identifier']).split('\n')
for line in sem_correspondences:
urn = line
if str(entry["Data Concept"]) == "missing data":
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AIXM 5.1.1",
"concept_name":
entry["Information Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
else:
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"AIXM 5.1.1",
"concept_name":
entry["Data Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
import aixm_adr
aixm_adr = aixm_adr.Aixm_adr()
aixm_adr_mapping_dict = aixm_adr.aixm_adr_mapping_dataframe.to_dict(
'records')
for entry in aixm_adr_mapping_dict:
sem_correspondences = str(entry['AIRM Concept Identifier']).split('\n')
for line in sem_correspondences:
urn = line
if str(entry["Data Concept"]) == "missing data":
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"ADR 23.5.0 Extension (AIXM 5.1.1)",
"concept_name":
entry["Information Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
else:
df_connected_index_rows.append({
"airm_urn":
urn,
"model_name":
"ADR 23.5.0 Extension (AIXM 5.1.1)",
"concept_name":
entry["Data Concept"],
"concept_id":
entry["Concept Identifier"],
"concept_type":
entry["Basic Type"]
})
df_connected_index_out = pd.DataFrame(df_connected_index_rows,
columns=df_connected_index_cols)
with pd.ExcelWriter('data/xlsx/' + 'connected_index.xlsx',
engine='xlsxwriter') as writer:
df_connected_index_out.to_excel(writer, sheet_name='connceted_index')