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Clustergram: app improvements #70

Merged
merged 15 commits into from
Dec 6, 2018
Merged

Clustergram: app improvements #70

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532c2d1
Restyle app; clustergram now on right hand side and larger, and color…
Dec 3, 2018
901dc04
Begin to implement usage of dcc.Store.
Dec 4, 2018
d000684
Add some print statements for debugging
Dec 4, 2018
b93bb5b
Add fix for cases in which serialization of numpy arrays loses nan da…
Dec 4, 2018
4c75207
Remove printing of grid.
Dec 4, 2018
e04f19d
Interim solution; currently trace storage does not work, so the entir…
Dec 4, 2018
f25d173
Add some sample datasets and begin to put those in a dropdown.
Dec 5, 2018
9c0f219
Fixed bug in which correct number of header rows was not getting pass…
Dec 5, 2018
d44707c
Some bugs with loading initial data options.
Dec 5, 2018
f9761f7
Fix bug in which the datasets were not immediately calculating and di…
Dec 5, 2018
976ac95
Remove debugging print statements and add petal width to default data…
Dec 5, 2018
04391f2
Make some stylistic changes.
Dec 5, 2018
95f44a3
Add ability to hide labels for one dimension on the plot.
Dec 5, 2018
acd7949
Add mtcars dataset, fix styling, and add information for all preloade…
Dec 6, 2018
cedc546
Add symmetric values and log transforms only for uploaded data, not p…
Dec 6, 2018
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155 changes: 112 additions & 43 deletions assets/clustergram-style.css
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
top: 0px;
left: 0px;
margin: 0px;
height: 100%;
min-height: 100vh;
width: 100%;
font-family: Helvetica, sans-serif;
background:#000000;
Expand All @@ -12,81 +12,150 @@
color: #dddddd;
}

#clustergram-options::-webkit-scrollbar {
width: 2px;
background-color: #000;
}
#clustergram-body > ::-webkit-scrollbar {
width: 2px;
background-color: #3e0f2e;
margin-right:5px;
}

#clustergram-options::-webkit-scrollbar-thumb {
background: #ddd;
}
#clustergram-body > ::-webkit-scrollbar-thumb {
background: #99003d;
margin-right:5px;
}

#clustergram-header {
width: calc(100% - 40px);
height:auto;
position: static;
margin-top:0px;
margin-left:0px;
font-size:28pt;
padding: 10px;
background:blue;
color:#ffffff;
#clustergram-wrapper::-webkit-scrollbar {
display: none;
}

#clustergram-options {
width: 500px;
position: relative;
width: 200px;
min-width:75px;
float:left;
top: 10px;
border: solid 2px white;
border-radius: 5px;
display: inline-block !important;
left: 20px;
border: solid 1px #3e0f2e;
padding: 20px;
max-height:300px;
overflow:scroll;
font-size: 10pt !important;
margin-top:50px;
margin-left:20px;
margin-bottom:50px;
height: 500px;
overflow-y:scroll;
font-size: 10pt !important;
border-radius: 5px;
}

#clustergram-wrapper {
height: 600px;
width:600px;
float:left;
width: 900px;
display: inline-block !important;
float:right;
padding: 0px;
margin: 0px;
overflow-x: scroll;
margin: 0px;
}
#clustergram-body .Select, #clustergram-body .Select-control, #clustergram-body input, #clustergram-body .Select-menu-outer, #clustergram-body .Select-value-label {
background-color: black !important;
color: white !important;
border-color: #3e0f2e;
}
#clustergram-file-upload-container {
width: 450px !important;
margin-left: 10px !important;
width: 80% !important;
margin-left: 5%;
margin-top: 20px;
height:20px !important;
}
#clustergram-body .Select-control {
width: 450px;
margin-left: -100px;
width: 100%;
}

#clustergram-body .Select, #clustergram-body input {
width: 225px;
width: 100%;
margin:auto;
}
#clustergram-body button {
#clustergram-body #submit-group-marker, #clustergram-body #remove-all-group-markers {
float: left;
width:110px;
margin: 6px;
font-size:8pt !important;
padding: 0px;
margin-top: 10px;
color: white;
font-weight: 100;
border-color: #99003d;
text-align: center;
width:48% !important;
transition-duration: 500ms;
}


#clustergram-body #submit-group-marker:hover, #clustergram-body #remove-all-group-markers:hover {
border-color: white;
}

#clustergram-body #submit-group-marker {
margin-right:2%;
}
#clustergram-body #remove-all-group-markers {
margin-left: 2%;
}

#clustergram-body #group-number, #clustergram-body #color {
width: 48% !important;
}
#clustergram-body #group-number {
margin-right: 2% !important;
}
#clustergram-body #color {
margin-left: 2% !important;
}
#clustergram-body input {
float:left;
width: 70px !important;
margin: 6px !important;
width: 100%;
margin: 0px;
margin-top:5px !important;
}
#clustergram-info {
margin-top: 20px;
margin-top: 50px;
margin-left: 20px;
margin-bottom:50px;
display: inline-block;
float: left;
width: 500px;
width: calc(100% - 500px);
border-radius: 5px;
padding: 20px;
border: 1px solid white;
border: 1px solid #3e0f2e;
}

#clustergram-file-upload-container{
border: dotted 1px #99003d;
width: 80%;
border-radius: 5px;
padding: 10px;
}

#clustergram-body #file-upload-name {
display: block;
width: 80%;
margin-left: 10%;
margin-top: 10px;
font-size: 10px;
}
.clustergram-option-name {
text-align: center;
font-size: 14pt;
}
#clustergram-body .Select-value {
border-color: #320f2e;
}

#clustergram-body .Select-value-icon {
color: #99003d;
border-right: 1px solid #320f2e;
}

#clustergram-body .rc-slider-track {
background-color: #99003d;
}

#clustergram-body .rc-slider-handle {
border: solid 2px #320f2e;
background-color: #99003d;
}

54 changes: 45 additions & 9 deletions dash_bio/component_factory/_clustergram.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -356,7 +356,8 @@ def figure(
[{}, {'colspan': 2}, None, {}]
],
vertical_spacing=0,
horizontal_spacing=0
horizontal_spacing=0,
print_grid=False
)

fig['layout']['hovermode'] = 'closest'
Expand All @@ -369,22 +370,56 @@ def figure(

# for column dendrogram, leaves are at bottom (y=0)
for i in range(len(t['col'])):
xs = t['col'][i]['x']
ys = t['col'][i]['y']

# during serialization (e.g., in a dcc.Store, the NaN
# values become None and the arrays get turned into lists;
# they must be converted back
if(isinstance(xs, list)):
xs = [x if x is not None else np.nan for x in xs]
xs = np.array(xs)
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In terms of speed looping explicitely over arrays in python is slover than using pandas or numpy functions, it would only be important for superlarge datasets though

t['col'][i].update(
x=xs
)
if(isinstance(ys, list)):
ys = [y if y is not None else np.nan for y in ys]
ys = np.array(ys)
t['col'][i].update(
y=ys
)
tickvals_col += [
t['col'][i]['x'].flatten()[j]
for j in range(len(t['col'][i]['x'].flatten()))
if t['col'][i]['y'].flatten()[j] == 0.0 and
t['col'][i]['x'].flatten()[j] % 10 == 5
xs.flatten()[j]
for j in range(len(xs.flatten()))
if ys.flatten()[j] == 0.0 and
xs.flatten()[j] % 10 == 5
]
tickvals_col = list(set(tickvals_col))

# for row dendrogram, leaves are at right(x=0, since we
# horizontally flipped it)
for i in range(len(t['row'])):
xs = t['row'][i]['x']
ys = t['row'][i]['y']

if(isinstance(xs, list)):
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almost the same code as above but with 'row' instead of 'col', could be done in a function for easier maintenance

xs = [x if x is not None else np.nan for x in xs]
xs = np.array(xs)
t['row'][i].update(
x=xs
)
if(isinstance(ys, list)):
ys = [y if y is not None else np.nan for y in ys]
ys = np.array(ys)
t['row'][i].update(
y=ys
)

tickvals_row += [
t['row'][i]['y'].flatten()[j]
for j in range(len(t['row'][i]['y'].flatten()))
if t['row'][i]['x'].flatten()[j] == 0.0 and
t['row'][i]['y'].flatten()[j] % 10 == 5
ys.flatten()[j]
for j in range(len(ys.flatten()))
if xs.flatten()[j] == 0.0 and
ys.flatten()[j] % 10 == 5
]

tickvals_row = list(set(tickvals_row))
Expand Down Expand Up @@ -701,6 +736,7 @@ def _dendrogramTraces(
}
self._rowLabels = scp.array(Prow['ivl'])
trace_list['row'] = self._colorDendroClusters(Prow_tmp, 'row')

return trace_list

def _colorDendroClusters(
Expand Down
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