Spaces:
Running on CPU Upgrade
Running on CPU Upgrade
Major Visual Change
Browse files
app.py
CHANGED
|
@@ -26,6 +26,15 @@ import datetime as dt
|
|
| 26 |
enableDenoise = False
|
| 27 |
earlyCleanup = True
|
| 28 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 29 |
def save_data(
|
| 30 |
config_dict: Dict[str,str], audio_paths: List[str], userid: str,
|
| 31 |
) -> None:
|
|
@@ -138,18 +147,21 @@ def analyze(inFileName):
|
|
| 138 |
currFileIndex = file_names.index(inFileName)
|
| 139 |
print(f"Found at index {currFileIndex}")
|
| 140 |
if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
|
|
|
|
|
|
|
| 141 |
# Handle
|
| 142 |
currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
|
| 143 |
speakerNames = currAnnotation.labels()
|
| 144 |
-
|
| 145 |
# Update other categories
|
| 146 |
unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
|
| 147 |
categorySelections = st.session_state["categorySelect"][currFileIndex]
|
| 148 |
-
|
| 149 |
noVoice, oneVoice, multiVoice = su.calcSpeakingTypes(currAnnotation,currTotalTime)
|
| 150 |
sumNoVoice = su.sumTimes(noVoice)
|
| 151 |
sumOneVoice = su.sumTimes(oneVoice)
|
| 152 |
sumMultiVoice = su.sumTimes(multiVoice)
|
|
|
|
| 153 |
|
| 154 |
df3 = pd.DataFrame(
|
| 155 |
{
|
|
@@ -161,6 +173,7 @@ def analyze(inFileName):
|
|
| 161 |
)
|
| 162 |
df3.name = "df3"
|
| 163 |
st.session_state.summaries[currFileIndex]["df3"] = df3
|
|
|
|
| 164 |
|
| 165 |
df4_dict = {}
|
| 166 |
nameList = st.session_state.categories
|
|
@@ -181,13 +194,17 @@ def analyze(inFileName):
|
|
| 181 |
else:
|
| 182 |
extraNames.append(sp)
|
| 183 |
extraValues.append(su.sumTimes(currAnnotation.subset([sp])))
|
|
|
|
|
|
|
| 184 |
df4_dict = {
|
| 185 |
-
"values": valueList+extraValues,
|
| 186 |
-
"names": nameList+extraNames,
|
| 187 |
}
|
| 188 |
df4 = pd.DataFrame(data=df4_dict)
|
| 189 |
df4.name = "df4"
|
| 190 |
st.session_state.summaries[currFileIndex]["df4"] = df4
|
|
|
|
|
|
|
| 191 |
|
| 192 |
speakerList,timeList = su.sumTimesPerSpeaker(oneVoice)
|
| 193 |
multiSpeakerList, multiTimeList = su.sumMultiTimesPerSpeaker(multiVoice)
|
|
@@ -228,6 +245,7 @@ def analyze(inFileName):
|
|
| 228 |
)
|
| 229 |
df5.name = "df5"
|
| 230 |
st.session_state.summaries[currFileIndex]["df5"] = df5
|
|
|
|
| 231 |
|
| 232 |
speakers_dataFrame,speakers_times = su.annotationToDataFrame(currAnnotation)
|
| 233 |
st.session_state.summaries[currFileIndex]["speakers_dataFrame"] = speakers_dataFrame
|
|
@@ -239,6 +257,7 @@ def analyze(inFileName):
|
|
| 239 |
}
|
| 240 |
df2 = pd.DataFrame(df2_dict)
|
| 241 |
st.session_state.summaries[currFileIndex]["df2"] = df2
|
|
|
|
| 242 |
except ValueError as e:
|
| 243 |
print(f"Value Error: {e}")
|
| 244 |
pass
|
|
@@ -420,9 +439,9 @@ else:
|
|
| 420 |
print(f"Took {time.time() - start_time} seconds to analyze {totalFiles} files!")
|
| 421 |
st.success(f"Took {time.time() - start_time} seconds to analyze {totalFiles} files!")
|
| 422 |
|
| 423 |
-
|
| 424 |
currFile = st.sidebar.selectbox('Current File', file_names,on_change=updateMultiSelect,key="select_currFile")
|
| 425 |
-
|
| 426 |
if currFile is None and len(st.session_state.results) > 0 and len(st.session_state.results[0]) > 0:
|
| 427 |
st.write("Select a file to view from the sidebar")
|
| 428 |
try:
|
|
@@ -430,9 +449,16 @@ try:
|
|
| 430 |
currFileIndex = file_names.index(currFile)
|
| 431 |
if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
|
| 432 |
st.header(f"Analysis of file {currFile}")
|
|
|
|
|
|
|
| 433 |
# Handle
|
| 434 |
currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
|
| 435 |
speakerNames = currAnnotation.labels()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 436 |
# Update other categories
|
| 437 |
unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
|
| 438 |
categorySelections = st.session_state["categorySelect"][currFileIndex]
|
|
@@ -450,6 +476,11 @@ try:
|
|
| 450 |
|
| 451 |
newCategory = st.sidebar.text_input('Add category', key='categoryInput',on_change=addCategory)
|
| 452 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 453 |
df4_dict = {}
|
| 454 |
nameList = st.session_state.categories
|
| 455 |
extraNames = []
|
|
@@ -472,25 +503,39 @@ try:
|
|
| 472 |
df4.name = "df4"
|
| 473 |
st.session_state.summaries[currFileIndex]["df4"] = df4
|
| 474 |
|
| 475 |
-
|
| 476 |
-
|
| 477 |
-
|
| 478 |
df3 = st.session_state.summaries[currFileIndex]["df3"]
|
| 479 |
fig1 = go.Figure()
|
| 480 |
fig1.update_layout(
|
| 481 |
title_text="Percentage of each Voice Category",
|
|
|
|
|
|
|
|
|
|
| 482 |
)
|
| 483 |
-
fig1.add_trace(go.Pie(values=df3["values"],labels=df3["names"]))
|
| 484 |
st.plotly_chart(fig1, use_container_width=True)
|
| 485 |
-
|
|
|
|
| 486 |
df4 = st.session_state.summaries[currFileIndex]["df4"]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 487 |
fig2 = go.Figure()
|
| 488 |
fig2.update_layout(
|
| 489 |
title_text="Percentage of Speakers and Custom Categories",
|
|
|
|
|
|
|
|
|
|
| 490 |
)
|
| 491 |
-
fig2.add_trace(go.Pie(values=df4["values"],labels=df4["names"]))
|
| 492 |
st.plotly_chart(fig2, use_container_width=True)
|
| 493 |
-
|
|
|
|
| 494 |
df5 = st.session_state.summaries[currFileIndex]["df5"]
|
| 495 |
fig3_1 = px.sunburst(df5,
|
| 496 |
branchvalues = 'total',
|
|
@@ -501,6 +546,7 @@ try:
|
|
| 501 |
custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
|
| 502 |
color = 'labels',
|
| 503 |
title="Percentage of each Voice Category with Speakers",
|
|
|
|
| 504 |
)
|
| 505 |
fig3_1.update_traces(
|
| 506 |
hovertemplate="<br>".join([
|
|
@@ -511,8 +557,13 @@ try:
|
|
| 511 |
'Percentage of Parent: %{customdata[4]:.2f}%'
|
| 512 |
])
|
| 513 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
| 514 |
st.plotly_chart(fig3_1, use_container_width=True)
|
| 515 |
-
|
|
|
|
| 516 |
df5 = st.session_state.summaries[currFileIndex]["df5"]
|
| 517 |
fig3 = px.treemap(df5,
|
| 518 |
branchvalues = "total",
|
|
@@ -523,6 +574,7 @@ try:
|
|
| 523 |
custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
|
| 524 |
color='labels',
|
| 525 |
title="Division of Speakers in each Voice Category",
|
|
|
|
| 526 |
)
|
| 527 |
fig3.update_traces(
|
| 528 |
hovertemplate="<br>".join([
|
|
@@ -532,17 +584,19 @@ try:
|
|
| 532 |
'Parent: %{customdata[3]}',
|
| 533 |
'Percentage of Parent: %{customdata[4]:.2f}%'
|
| 534 |
])
|
|
|
|
|
|
|
|
|
|
|
|
|
| 535 |
)
|
| 536 |
st.plotly_chart(fig3, use_container_width=True)
|
| 537 |
-
|
| 538 |
-
|
| 539 |
-
|
| 540 |
-
|
| 541 |
-
|
| 542 |
-
|
| 543 |
-
|
| 544 |
-
|
| 545 |
-
fig_la = px.timeline(speakers_dataFrame, x_start="Start", x_end="Finish", y="Resource", color="Resource",title="Timeline of Audio with Speakers")
|
| 546 |
fig_la.update_yaxes(autorange="reversed")
|
| 547 |
|
| 548 |
hMax = int(currTotalTime//3600)
|
|
@@ -561,20 +615,26 @@ try:
|
|
| 561 |
),
|
| 562 |
xaxis_title="Time",
|
| 563 |
yaxis_title="Speaker",
|
| 564 |
-
legend_title=None
|
|
|
|
|
|
|
| 565 |
)
|
| 566 |
|
| 567 |
st.plotly_chart(fig_la, use_container_width=True)
|
| 568 |
-
|
|
|
|
| 569 |
df2 = st.session_state.summaries[currFileIndex]["df2"]
|
| 570 |
fig2_la = px.bar(df2, x="values", y="names", color="names", orientation='h',
|
| 571 |
-
custom_data=["names","values"],title="Time Spoken by each Speaker"
|
|
|
|
| 572 |
fig2_la.update_xaxes(ticksuffix="%")
|
| 573 |
fig2_la.update_yaxes(autorange="reversed")
|
| 574 |
fig2_la.update_layout(
|
| 575 |
xaxis_title="Percentage Time Spoken",
|
| 576 |
yaxis_title="Speaker",
|
| 577 |
-
legend_title=None
|
|
|
|
|
|
|
| 578 |
|
| 579 |
)
|
| 580 |
fig2_la.update_traces(
|
|
@@ -587,11 +647,9 @@ try:
|
|
| 587 |
|
| 588 |
except ValueError:
|
| 589 |
pass
|
| 590 |
-
|
| 591 |
if len(st.session_state.results) > 0:
|
| 592 |
-
|
| 593 |
-
|
| 594 |
-
if st.session_state.showSummary == 'Yes':
|
| 595 |
st.header("Multi-file Summary Data")
|
| 596 |
with st.spinner(text='Processing summary results...'):
|
| 597 |
fileNames = st.session_state.file_names
|
|
|
|
| 26 |
enableDenoise = False
|
| 27 |
earlyCleanup = True
|
| 28 |
|
| 29 |
+
# [None,Low,Medium,High,Debug]
|
| 30 |
+
# [0,1,2,3,4]
|
| 31 |
+
verbosity=4
|
| 32 |
+
|
| 33 |
+
def printV(message,verbosityLevel):
|
| 34 |
+
global verbosity
|
| 35 |
+
if verbosity>=verbosityLevel:
|
| 36 |
+
print(message)
|
| 37 |
+
|
| 38 |
def save_data(
|
| 39 |
config_dict: Dict[str,str], audio_paths: List[str], userid: str,
|
| 40 |
) -> None:
|
|
|
|
| 147 |
currFileIndex = file_names.index(inFileName)
|
| 148 |
print(f"Found at index {currFileIndex}")
|
| 149 |
if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
|
| 150 |
+
|
| 151 |
+
printV(f'In if',4)
|
| 152 |
# Handle
|
| 153 |
currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
|
| 154 |
speakerNames = currAnnotation.labels()
|
| 155 |
+
printV(f'Loaded results',4)
|
| 156 |
# Update other categories
|
| 157 |
unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
|
| 158 |
categorySelections = st.session_state["categorySelect"][currFileIndex]
|
| 159 |
+
printV(f'Loaded speaker selections',4)
|
| 160 |
noVoice, oneVoice, multiVoice = su.calcSpeakingTypes(currAnnotation,currTotalTime)
|
| 161 |
sumNoVoice = su.sumTimes(noVoice)
|
| 162 |
sumOneVoice = su.sumTimes(oneVoice)
|
| 163 |
sumMultiVoice = su.sumTimes(multiVoice)
|
| 164 |
+
printV(f'Calculated speaking types',4)
|
| 165 |
|
| 166 |
df3 = pd.DataFrame(
|
| 167 |
{
|
|
|
|
| 173 |
)
|
| 174 |
df3.name = "df3"
|
| 175 |
st.session_state.summaries[currFileIndex]["df3"] = df3
|
| 176 |
+
printV(f'Set df3',4)
|
| 177 |
|
| 178 |
df4_dict = {}
|
| 179 |
nameList = st.session_state.categories
|
|
|
|
| 194 |
else:
|
| 195 |
extraNames.append(sp)
|
| 196 |
extraValues.append(su.sumTimes(currAnnotation.subset([sp])))
|
| 197 |
+
extraPairsSorted = sorted(zip(extraNames, extraValues), key=lambda pair: pair[0])
|
| 198 |
+
extraNames, extraValues = zip(*extraPairsSorted)
|
| 199 |
df4_dict = {
|
| 200 |
+
"values": valueList+list(extraValues),
|
| 201 |
+
"names": nameList+list(extraNames),
|
| 202 |
}
|
| 203 |
df4 = pd.DataFrame(data=df4_dict)
|
| 204 |
df4.name = "df4"
|
| 205 |
st.session_state.summaries[currFileIndex]["df4"] = df4
|
| 206 |
+
|
| 207 |
+
printV(f'Set df4',4)
|
| 208 |
|
| 209 |
speakerList,timeList = su.sumTimesPerSpeaker(oneVoice)
|
| 210 |
multiSpeakerList, multiTimeList = su.sumMultiTimesPerSpeaker(multiVoice)
|
|
|
|
| 245 |
)
|
| 246 |
df5.name = "df5"
|
| 247 |
st.session_state.summaries[currFileIndex]["df5"] = df5
|
| 248 |
+
printV(f'Set df5',4)
|
| 249 |
|
| 250 |
speakers_dataFrame,speakers_times = su.annotationToDataFrame(currAnnotation)
|
| 251 |
st.session_state.summaries[currFileIndex]["speakers_dataFrame"] = speakers_dataFrame
|
|
|
|
| 257 |
}
|
| 258 |
df2 = pd.DataFrame(df2_dict)
|
| 259 |
st.session_state.summaries[currFileIndex]["df2"] = df2
|
| 260 |
+
printV(f'Set df2',4)
|
| 261 |
except ValueError as e:
|
| 262 |
print(f"Value Error: {e}")
|
| 263 |
pass
|
|
|
|
| 439 |
print(f"Took {time.time() - start_time} seconds to analyze {totalFiles} files!")
|
| 440 |
st.success(f"Took {time.time() - start_time} seconds to analyze {totalFiles} files!")
|
| 441 |
|
| 442 |
+
|
| 443 |
currFile = st.sidebar.selectbox('Current File', file_names,on_change=updateMultiSelect,key="select_currFile")
|
| 444 |
+
|
| 445 |
if currFile is None and len(st.session_state.results) > 0 and len(st.session_state.results[0]) > 0:
|
| 446 |
st.write("Select a file to view from the sidebar")
|
| 447 |
try:
|
|
|
|
| 449 |
currFileIndex = file_names.index(currFile)
|
| 450 |
if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
|
| 451 |
st.header(f"Analysis of file {currFile}")
|
| 452 |
+
graphNames = ["Data","Voice Categories","Speaker Percentage","Speakers with Categories","Treemap","Timeline","Time Spoken"]
|
| 453 |
+
dataTab, pie1, pie2, sunburst1, treemap1, timeline, bar1 = st.tabs(graphNames)
|
| 454 |
# Handle
|
| 455 |
currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
|
| 456 |
speakerNames = currAnnotation.labels()
|
| 457 |
+
|
| 458 |
+
speakers_dataFrame = st.session_state.summaries[currFileIndex]["speakers_dataFrame"]
|
| 459 |
+
currDF = speakers_dataFrame
|
| 460 |
+
speakers_times = st.session_state.summaries[currFileIndex]["speakers_times"]
|
| 461 |
+
|
| 462 |
# Update other categories
|
| 463 |
unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
|
| 464 |
categorySelections = st.session_state["categorySelect"][currFileIndex]
|
|
|
|
| 476 |
|
| 477 |
newCategory = st.sidebar.text_input('Add category', key='categoryInput',on_change=addCategory)
|
| 478 |
|
| 479 |
+
catTypeColors = su.colorsCSS(3)
|
| 480 |
+
allColors = su.colorsCSS(len(speakerNames)+len(st.session_state.categories))
|
| 481 |
+
speakerColors = allColors[:len(speakerNames)]
|
| 482 |
+
catColors = allColors[len(speakerNames):]
|
| 483 |
+
|
| 484 |
df4_dict = {}
|
| 485 |
nameList = st.session_state.categories
|
| 486 |
extraNames = []
|
|
|
|
| 503 |
df4.name = "df4"
|
| 504 |
st.session_state.summaries[currFileIndex]["df4"] = df4
|
| 505 |
|
| 506 |
+
with dataTab:
|
| 507 |
+
st.dataframe(currDF)
|
| 508 |
+
with pie1:
|
| 509 |
df3 = st.session_state.summaries[currFileIndex]["df3"]
|
| 510 |
fig1 = go.Figure()
|
| 511 |
fig1.update_layout(
|
| 512 |
title_text="Percentage of each Voice Category",
|
| 513 |
+
colorway=catTypeColors,
|
| 514 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 515 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 516 |
)
|
| 517 |
+
fig1.add_trace(go.Pie(values=df3["values"],labels=df3["names"],sort=False))
|
| 518 |
st.plotly_chart(fig1, use_container_width=True)
|
| 519 |
+
|
| 520 |
+
with pie2:
|
| 521 |
df4 = st.session_state.summaries[currFileIndex]["df4"]
|
| 522 |
+
|
| 523 |
+
# Some speakers may be missing, so fix colors
|
| 524 |
+
figColors = []
|
| 525 |
+
for n in df4["names"]:
|
| 526 |
+
if n in speakerNames:
|
| 527 |
+
figColors.append(speakerColors[speakerNames.index(n)])
|
| 528 |
fig2 = go.Figure()
|
| 529 |
fig2.update_layout(
|
| 530 |
title_text="Percentage of Speakers and Custom Categories",
|
| 531 |
+
colorway=catColors+figColors,
|
| 532 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 533 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 534 |
)
|
| 535 |
+
fig2.add_trace(go.Pie(values=df4["values"],labels=df4["names"],sort=False))
|
| 536 |
st.plotly_chart(fig2, use_container_width=True)
|
| 537 |
+
|
| 538 |
+
with sunburst1:
|
| 539 |
df5 = st.session_state.summaries[currFileIndex]["df5"]
|
| 540 |
fig3_1 = px.sunburst(df5,
|
| 541 |
branchvalues = 'total',
|
|
|
|
| 546 |
custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
|
| 547 |
color = 'labels',
|
| 548 |
title="Percentage of each Voice Category with Speakers",
|
| 549 |
+
color_discrete_sequence=catTypeColors+speakerColors,
|
| 550 |
)
|
| 551 |
fig3_1.update_traces(
|
| 552 |
hovertemplate="<br>".join([
|
|
|
|
| 557 |
'Percentage of Parent: %{customdata[4]:.2f}%'
|
| 558 |
])
|
| 559 |
)
|
| 560 |
+
fig3_1.update_layout(
|
| 561 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 562 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 563 |
+
)
|
| 564 |
st.plotly_chart(fig3_1, use_container_width=True)
|
| 565 |
+
|
| 566 |
+
with treemap1:
|
| 567 |
df5 = st.session_state.summaries[currFileIndex]["df5"]
|
| 568 |
fig3 = px.treemap(df5,
|
| 569 |
branchvalues = "total",
|
|
|
|
| 574 |
custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
|
| 575 |
color='labels',
|
| 576 |
title="Division of Speakers in each Voice Category",
|
| 577 |
+
color_discrete_sequence=catTypeColors+speakerColors,
|
| 578 |
)
|
| 579 |
fig3.update_traces(
|
| 580 |
hovertemplate="<br>".join([
|
|
|
|
| 584 |
'Parent: %{customdata[3]}',
|
| 585 |
'Percentage of Parent: %{customdata[4]:.2f}%'
|
| 586 |
])
|
| 587 |
+
))
|
| 588 |
+
fig3.update_layout(
|
| 589 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 590 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 591 |
)
|
| 592 |
st.plotly_chart(fig3, use_container_width=True)
|
| 593 |
+
|
| 594 |
+
# generate plotting window
|
| 595 |
+
|
| 596 |
+
|
| 597 |
+
with timeline:
|
| 598 |
+
fig_la = px.timeline(speakers_dataFrame, x_start="Start", x_end="Finish", y="Resource", color="Resource",title="Timeline of Audio with Speakers",
|
| 599 |
+
color_discrete_sequence=speakerColors)
|
|
|
|
|
|
|
| 600 |
fig_la.update_yaxes(autorange="reversed")
|
| 601 |
|
| 602 |
hMax = int(currTotalTime//3600)
|
|
|
|
| 615 |
),
|
| 616 |
xaxis_title="Time",
|
| 617 |
yaxis_title="Speaker",
|
| 618 |
+
legend_title=None,
|
| 619 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 620 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 621 |
)
|
| 622 |
|
| 623 |
st.plotly_chart(fig_la, use_container_width=True)
|
| 624 |
+
|
| 625 |
+
with bar1:
|
| 626 |
df2 = st.session_state.summaries[currFileIndex]["df2"]
|
| 627 |
fig2_la = px.bar(df2, x="values", y="names", color="names", orientation='h',
|
| 628 |
+
custom_data=["names","values"],title="Time Spoken by each Speaker",
|
| 629 |
+
color_discrete_sequence=catColors+speakerColors)
|
| 630 |
fig2_la.update_xaxes(ticksuffix="%")
|
| 631 |
fig2_la.update_yaxes(autorange="reversed")
|
| 632 |
fig2_la.update_layout(
|
| 633 |
xaxis_title="Percentage Time Spoken",
|
| 634 |
yaxis_title="Speaker",
|
| 635 |
+
legend_title=None,
|
| 636 |
+
plot_bgcolor='rgba(0, 0, 0, 0)',
|
| 637 |
+
paper_bgcolor='rgba(0, 0, 0, 0)',
|
| 638 |
|
| 639 |
)
|
| 640 |
fig2_la.update_traces(
|
|
|
|
| 647 |
|
| 648 |
except ValueError:
|
| 649 |
pass
|
| 650 |
+
|
| 651 |
if len(st.session_state.results) > 0:
|
| 652 |
+
with st.expander("Multi-file Summary Data"):
|
|
|
|
|
|
|
| 653 |
st.header("Multi-file Summary Data")
|
| 654 |
with st.spinner(text='Processing summary results...'):
|
| 655 |
fileNames = st.session_state.file_names
|