def main_area(url, nodes, edges, state):
logger.debug('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
# Get the count by state of visits shown
bar_chart_data = edges[edges['label'] == 'visited']
group_label = 'state'
if not state == 'All States': # If a state is chosen group by city
group_label = 'city'
bar_chart_data['count'] = bar_chart_data.groupby(
group_label)[group_label].transform('count')
bar_chart_data = bar_chart_data[[
group_label, 'count'
]].drop_duplicates().reset_index()[[group_label, 'count']]
# Sort the values by group_label
bar_chart_data.sort_values(by=[group_label], inplace=True)
chart = alt.Chart(bar_chart_data).mark_bar().encode(x=group_label,
y='count')
st.altair_chart(chart, use_container_width=True)
# Show a datatable with the values transposed
st.dataframe(bar_chart_data.set_index(group_label).T)
st.markdown(f'''<small>
Neptune Load Time (s): {float(metrics['neptune_time']):0.2f} |
Graphistry Load Time (s): {float(metrics['graphistry_time']):0.2f} |
Node Count: {metrics['node_cnt']} |
Edge Count: {metrics['edge_cnt']} |
Property Count: {metrics['prop_cnt']}
</small>''',
unsafe_allow_html=True)
def plot_url(edges_df, n):
nodes_df = pd.DataFrame(
{'n': pd.concat([edges_df['s'], edges_df['d']]).unique()})
nodes_df['nc'] = nodes_df['n'].apply(
lambda v: 0x01000000 * round(255 * v / n))
logger.info('Starting graphistry plot')
if not GraphistrySt().test_login():
return ''
url = graphistry\
.bind(source="s", destination="d")\
.edges(edges_df)\
.nodes(nodes_df)\
.bind(node='n', point_color='nc')\
.settings(url_params={
'pointSize': 0.3,
'splashAfter': 'false',
'bg': '%23' + 'f0f2f6'
})\
.plot(render=False)
logger.info('Generated viz, got back urL: %s', url)
return url
def main_area(num_nodes, num_edges, bank, bank_ids, nodes_df, edges_df,
graph_url, ego_banks_df):
logger.debug('rendering main area, with url: %s', graph_url)
GraphistrySt().render_url(graph_url)
st.subheader('Selected banks')
st.write(ego_banks_df)
st.subheader('Surrounding banks')
st.write(nodes_df)
st.subheader('Reported transactions')
st.write(edges_df)
def main_area(url, nodes, edges, user_id, conn):
logger.debug('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
dates = []
amounts = []
transfer_type = []
results = None
try:
results = conn.runInstalledQuery("totalTransaction",
params={"Source": user_id})[0]
except Exception as e:
print(e)
# Create bar chart of transactions
if results != None:
for action in results:
for transfer in results[action]:
dates.append(
datetime.datetime.fromtimestamp(
transfer['attributes']['ts']))
amounts.append(transfer['attributes']['amount'])
transfer_type.append(action)
cols = list(zip(dates, amounts, transfer_type))
cols = sorted(cols, key=lambda x: x[0].day)
cols = sorted(cols, key=lambda x: x[0].month)
cols = sorted(cols, key=lambda x: x[0].year)
df = pd.DataFrame(data=cols, columns=['Date', 'Amount', 'Type'])
df['Date'] = pd.to_datetime(df['Date'])
map_color = {
"receive": "rgba(0,0,255,0.5)",
"transfer": "rgba(255,0,0,0.5)"
}
df['Color'] = df['Type'].map(map_color)
df = df.groupby([df['Date'].dt.to_period('M'), 'Type', 'Color']).sum()
df = df.reset_index(level=['Type', 'Color'])
df.index = df.index.values.astype('datetime64[M]')
bar = px.bar(
df,
x=df.index,
y='Amount',
labels={'x': 'Date'},
color='Type',
color_discrete_map=map_color,
text='Amount',
title="Transaction Amounts by Month for User {}".format(user_id),
height=350,
barmode='group')
bar.update_xaxes(dtick="M1", tickformat="%b\n%Y")
try:
for trace in bar.data:
trace.name = trace.name.split('=')[1].capitalize()
except:
for trace in bar.data:
trace.name = trace.name.capitalize()
st.plotly_chart(bar, use_container_width=True)
st.markdown(f'''<small>
TigerGraph Load Time (s): {float(metrics['tigergraph_time']):0.2f} |
Graphistry Load Time (s): {float(metrics['graphistry_time']):0.2f} |
Node Count: {metrics['node_cnt']} |
Edge Count: {metrics['edge_cnt']} |
Property Count: {metrics['prop_cnt']}
</small>''',
unsafe_allow_html=True)
def main_area(top, selval, selstr, conn):
file_path = os.path.dirname(os.path.realpath(__file__))
parent_path = os.path.abspath(os.path.join(file_path, os.path.pardir))
logo_its = Image.open(os.path.join(parent_path, 'logo.jpeg'))
st.image(logo_its, caption=None, width=250, use_column_width='True', clamp=False, channels='RGB', output_format='auto')
st.write(""" # LODHalal: Similar Product """)
st.write('Search product with similar ingredients. We can enter the name of the product (Based on 10 Similar Product Name), \
then the system will search up to 10 products that contain the input word, and finally return the products that \
contain similar ingredients with them. Or we can enter the product ID (Based on Product ID) and then the system \
will return the products that contain similar ingredients with the input product.')
tic = time.perf_counter()
if conn is None:
logger.error('Cannot run tg demo without creds')
st.write(RuntimeError('Demo requires a TigerGraph connection. Put creds into left sidebar, or fill in envs/tigergraph.env & restart'))
return None
new_from_id = []
new_foodname = []
new_cert = []
new_org = []
new_to_id = []
if selval == 1:
# Get Similar Product
error = 0
try:
query2 = "GetSimilarProduct"
resultTG2 = conn.runInstalledQuery(query2, params={'ids': selstr, 'top': top})
results2 = resultTG2[0]['SIMILAR_Product']
except Exception as e:
print(e)
error = 1
if error == 1:
new_from_id.append(selstr)
new_foodname.append('')
new_cert.append('')
new_org.append('')
new_to_id.append(selstr)
else:
dataawal = pd.DataFrame(results2)
dataname = []
for dataattr in dataawal['attributes']:
name = dataattr.get('Subjects.food_name')
dataname.append(name)
i=0
for product in results2:
new_from_id.append(selstr)
new_foodname.append(dataname[i])
new_cert.append('')
new_org.append('')
new_to_id.append(product['v_id'])
i += 1
elif selval == 0:
# Search Product by Name
query = "GetProductByName"
resultTG = conn.runInstalledQuery(query, params={'foodname': selstr})
results = resultTG[0]['@@tupleRecords']
results = results[0:10]
# Get Similar Product
for product in results:
error = 0
try:
query2 = "GetSimilarProduct"
resultTG2 = conn.runInstalledQuery(query2, params={'ids': product['id'], 'top': top})
results2 = resultTG2[0]['SIMILAR_Product']
except Exception as e:
print(e)
error = 1
if error == 1:
new_from_id.append(product['id'])
new_foodname.append(product['foodname'])
new_cert.append(product['cert'])
new_org.append(product['org'])
new_to_id.append(product['id'])
else:
for simproduct in results2:
new_from_id.append(product['id'])
new_foodname.append(product['foodname'])
new_cert.append(product['cert'])
new_org.append(product['org'])
new_to_id.append(simproduct['v_id'])
nodes_from_df = pd.DataFrame({
'Food ID': [int (i) for i in new_from_id],
'Name': new_foodname,
'Halal Certifate': new_cert,
'Issuing Authority': new_org
})
nodes_to_df = pd.DataFrame({
'Food ID': [int (i) for i in new_to_id],
'Name': '',
'Halal Certifate': '',
'Issuing Authority': ''
})
nodes_df = nodes_from_df.append(nodes_to_df)
edges_df = pd.DataFrame({
'from_id': [int (i) for i in new_from_id],
'to_id': [int (i) for i in new_to_id]
})
nodes_df = nodes_df.drop_duplicates(subset='Food ID')
edges_df = edges_df.drop_duplicates()
try:
res = nodes_df.values.tolist()
toc = time.perf_counter()
logger.info(f'Query Execution: {toc - tic:0.02f} seconds')
logger.debug('Query Result Count: %s', len(res))
metrics['tigergraph_time'] = toc - tic
# Calculate the metrics
metrics['node_cnt'] = nodes_df.size
metrics['prop_cnt'] = (nodes_df.size * nodes_df.columns.size) + \
(edges_df.size * edges_df.columns.size)
if nodes_df.size > 0:
url = plot_url(nodes_df, edges_df)
# g = graphistry.edges(edges_df).bind(source='from_id', destination='to_id')
# url = g.plot(render=False, as_files=True)
else:
url = ""
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info("Finished compute phase")
try:
pass
except RuntimeError as e:
if str(e) == "There is no current event loop in thread 'ScriptRunner.scriptThread'.":
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
else:
raise e
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
def main_area(num_nodes, num_edges, nodes_df, edges_df, graph_url):
logger.debug('rendering main area, with url: %s', graph_url)
GraphistrySt().render_url(graph_url)
st.header('Edges (RAPIDS GPU cudf DataFrame)')
st.write(edges_df)
def main_area(conn):
file_path = os.path.dirname(os.path.realpath(__file__))
parent_path = os.path.abspath(os.path.join(file_path, os.path.pardir))
logo_its = Image.open(os.path.join(parent_path, 'logo.jpeg'))
st.image(logo_its,
caption=None,
width=250,
use_column_width='True',
clamp=False,
channels='RGB',
output_format='auto')
st.write(""" # LODHalal: Halal Product & Manufacture Link """)
st.write(
'Shows the link between products and its manufacturers. The \'cutlery\' icon in the node is for product while \
the \'building\' icon is for manufacturer.')
tic = time.perf_counter()
if conn is None:
logger.error('Cannot run tg demo without creds')
st.write(
RuntimeError(
'Demo requires a TigerGraph connection. Put creds into left sidebar, or fill in envs/tigergraph.env & restart'
))
return None
query = "ProductManufactureLink"
resultTG = conn.runInstalledQuery(query)
results = resultTG[0]['@@tupleRecords']
data = pd.DataFrame(results[0:2000])
edges_df = data
nodes_src = pd.DataFrame({'Name': data['src'], 'Type': 'Product'})
nodes_dest = pd.DataFrame({'Name': data['dest'], 'Type': 'Manufacture'})
nodes_df = nodes_src.append(nodes_dest)
nodes_df = nodes_df.drop_duplicates(subset='Name')
try:
res = data.values.tolist()
toc = time.perf_counter()
logger.info(f'Query Execution: {toc - tic:0.02f} seconds')
logger.debug('Query Result Count: %s', len(res))
metrics['tigergraph_time'] = toc - tic
# Calculate the metrics
metrics['node_cnt'] = data.size
metrics['prop_cnt'] = (data.size * data.columns.size)
if data.size > 0:
url = plot_url(nodes_df, edges_df)
else:
url = ""
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info("Finished compute phase")
try:
pass
except RuntimeError as e:
if str(
e
) == "There is no current event loop in thread 'ScriptRunner.scriptThread'.":
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
else:
raise e
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
def main_area(num_nodes, num_edges, nodes_df, edges_df, graph_url):
#logger.debug('rendering main area, with url: %s', graph_url)
GraphistrySt().render_url(graph_url)
def main_area(edges_df, url):
logger.debug('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
def main_area(url, nodes, edges, person_a, person_b, k_hops, conn):
GraphistrySt().render_url(url)
def main_area(fdnm, conn):
file_path = os.path.dirname(os.path.realpath(__file__))
parent_path = os.path.abspath(os.path.join(file_path, os.path.pardir))
logo_its = Image.open(os.path.join(parent_path, 'logo.jpeg'))
st.image(logo_its,
caption=None,
width=250,
use_column_width='True',
clamp=False,
channels='RGB',
output_format='auto')
st.write(""" # LODHalal: Search Product """)
st.write('Search product that contains the input word.')
tic = time.perf_counter()
if conn is None:
logger.error('Cannot run tg demo without creds')
st.write(
RuntimeError(
'Demo requires a TigerGraph connection. Put creds into left sidebar, or fill in envs/tigergraph.env & restart'
))
return None
# Search Product by Name
query = "GetProductByName"
resultTG = conn.runInstalledQuery(query, params={'foodname': fdnm})
results = resultTG[0]['@@tupleRecords']
data = pd.DataFrame(results)
data = pd.DataFrame({
'Food ID': data['id'],
'Name': data['foodname'],
'Halal Certifate': data['cert'],
'Issuing Authority': data['org']
})
try:
res = data.values.tolist()
toc = time.perf_counter()
logger.info(f'Query Execution: {toc - tic:0.02f} seconds')
logger.debug('Query Result Count: %s', len(res))
metrics['tigergraph_time'] = toc - tic
# Calculate the metrics
metrics['node_cnt'] = data.size
metrics['prop_cnt'] = (data.size * data.columns.size)
if data.size > 0:
# url = plot_url(nodes_df, edges_df)
g = graphistry.edges(data).bind(source='Name', destination='Name') \
.nodes(data).bind(node='Name')
url = g.plot(render=False, as_files=True)
else:
url = ""
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info("Finished compute phase")
try:
pass
except RuntimeError as e:
if str(
e
) == "There is no current event loop in thread 'ScriptRunner.scriptThread'.":
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
else:
raise e
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)
def main_area(clusnum, conn):
file_path = os.path.dirname(os.path.realpath(__file__))
parent_path = os.path.abspath(os.path.join(file_path, os.path.pardir))
logo_its = Image.open(os.path.join(parent_path, 'logo.jpeg'))
st.image(logo_its, caption=None, width=250, use_column_width='True', clamp=False, channels='RGB', output_format='auto')
st.write(""" # LODHalal: Ingredient Cluster """)
st.write('Shows the cluster of product\'s ingredients.')
tic = time.perf_counter()
if conn is None:
logger.error('Cannot run tg demo without creds')
st.write(RuntimeError('Demo requires a TigerGraph connection. Put creds into left sidebar, or fill in envs/tigergraph.env & restart'))
return None
file_path = os.path.dirname(os.path.realpath(__file__))
if (clusnum == 2):
data = pd.read_csv(os.path.join(file_path, 'klasters3.csv'))
else:
data = pd.read_csv(os.path.join(file_path, 'klasters.csv'))
nan_value = float("NaN")
data.replace("", nan_value, inplace=True)
data.dropna(subset = ['0'], inplace=True)
cluster_num = []
for vertex in data['1']:
if int(vertex)<1:
cluster_num.append('Cluster {}'.format(int(vertex)+1))
else:
cluster_num.append('Cluster {}'.format(int(vertex)))
nodes_df = pd.DataFrame({
'Ingredient': data['0'],
'Cluster': cluster_num
})
edges_df = nodes_df
try:
res = data.values.tolist()
toc = time.perf_counter()
logger.info(f'Query Execution: {toc - tic:0.02f} seconds')
logger.debug('Query Result Count: %s', len(res))
metrics['tigergraph_time'] = toc - tic
# Calculate the metrics
metrics['node_cnt'] = data.size
metrics['prop_cnt'] = (data.size * data.columns.size)
if data.size > 0:
url = plot_url(nodes_df, edges_df)
else:
url = ""
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info("Finished compute phase")
try:
pass
except RuntimeError as e:
if str(e) == "There is no current event loop in thread 'ScriptRunner.scriptThread'.":
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
else:
raise e
except Exception as e:
logger.error('oops in TigerGraph', exc_info=True)
raise e
logger.info('rendering main area, with url: %s', url)
GraphistrySt().render_url(url)