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GRAMEX-108 ⁃ ENH: Show TopCause results in MLHandler #467

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88 changes: 64 additions & 24 deletions gramex/apps/mlhandler/template.html
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Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@
'DecisionTreeRegressor',
'RandomForestRegressor',
'MLPRegressor'] %}
{% set GRAINSIGHT_MODELS = ['TopCause'] %}
{% set tcol = handler.get_opt('target_col', False) %}
{% set CLASSIFICTION_METRICS = {
'Accuracy': 'accuracy',
Expand Down Expand Up @@ -121,7 +122,7 @@ <h3 class="text-center">Train the Model</h3>
<div class="row pb-3 pt-3">
<div class="col">
<label for="cats">Categorical Columns:</label>
<select id="cats" class="selectpicker form-control" multiple name="cats">
<select id="cats" class="selectpicker form-control tcdisable" multiple name="cats">
{% for col in columns %}
{% set selected = "selected" if col in handler.get_opt('cats', []) else "" %}
<option value="{{ col }}" {{ selected }}>{{ col }}</option>
Expand All @@ -130,7 +131,7 @@ <h3 class="text-center">Train the Model</h3>
</div>
<div class="col">
<label for="nums">Numerical Columns:</label>
<select id="nums" class="selectpicker form-control" multiple name="nums">
<select id="nums" class="selectpicker form-control tcdisable" multiple name="nums">
{% for col in columns %}
{% set selected = "selected" if col in handler.get_opt('nums', []) else "" %}
<option value="{{ col }}" {{ selected }}>{{ col }}</option>
Expand All @@ -141,12 +142,12 @@ <h3 class="text-center">Train the Model</h3>
<div class="row pb-3 pt-3">
<div class="col">
<label for="transform">Transform:</label>
<input class="form-control" id="transform" name="data.transform" type="text"
<input class="form-control tcdisable" id="transform" name="data.transform" type="text"
value="{{ handler.get_opt('transform', '') }}">
</div>
<div class="col">
<label for="metric">Choose a Metric:</label>
<select id="metric" class="form-control selectpicker" name="metric">
<select id="metric" class="form-control selectpicker tcdisable" name="metric">
{% if handler.get_opt('class') in CLASSIFICTION_MODELS %}
{% for i, (mname, metric) in enumerate(CLASSIFICTION_METRICS.items()) %}
{% set selected = "selected" if metric == "accuracy" else "" %}
Expand Down Expand Up @@ -181,6 +182,12 @@ <h3 class="text-center">Train the Model</h3>
<option value="{{ model }}" {{ selected }}>{{ model }}</option>
{% end %}
</optgroup>
<optgroup label="GrainSight">
{% for model in GRAINSIGHT_MODELS %}
{% set selected = "selected" if model == handler.get_opt('class') else "" %}
<option value="{{ model }}" {{ selected }}>{{ model }}</option>
{% end %}
</optgroup>
</select>
</div>
</div>
Expand All @@ -190,6 +197,7 @@ <h3 class="text-center">Train the Model</h3>
</div>
</form>
<div class="text-center divider">Results</div>
<div id="tcresult" class="container"></div>
<div class="container" id="resultcnt">
<div class="row">
<div class="col">
Expand Down Expand Up @@ -234,7 +242,7 @@ <h3 class="text-center">Train the Model</h3>
<h3 class="text-center">Make Predictions</h3>
<div class="row py-2">
<div class="col">
<button type="submit" form="predictform" class="btn btn-primary">Predict</button>
<button type="submit" form="predictform" class="btn btn-primary tcdisable">Predict</button>
</div>
<div class="col">
<h4 id="predResult"></h4>
Expand All @@ -246,7 +254,7 @@ <h4 id="predResult"></h4>
<% COLS.forEach(function(col) { %>
<div class="form-group row">
<label for="<%= col.name %>" class="col-md-6"><%= col.name %></label>
<input class="form-control col-md-6" type="<%= col.type %>" name="<%= col.name %>" value="<%=row[col.name]%>">
<input class="form-control col-md-6 tcdisable" type="<%= col.type %>" name="<%= col.name %>" value="<%=row[col.name]%>">
</div>
<% }) %>
</div>
Expand Down Expand Up @@ -276,34 +284,64 @@ <h4 id="predResult"></h4>
if (s > 90) { color = '#00f700' }
return color
}
const get_score = function() {
let url = g1.url.parse(window.location)
$.ajax({
url: url + '?_action=score&_metric=' + encodeURIComponent($('#metric').val()),
method: 'POST',
success: function(resp) {
let score = Number.parseFloat(JSON.parse(resp).score * 100).toPrecision(4)
score = Number.parseFloat(score)
$('.donut-segment').attr('stroke-dasharray', `${score} ${100 - score}`)
$('tspan').html(`${score}%`)
$('.donut-segment').attr('stroke', get_score_color(score))
$('#resultcnt').show()
let inputcols = fh_meta.meta.columns.filter((col) => !$('#exclude').val().concat($('#targetcol').val()).includes(col.name))
$('#predicttabtemplate').template({COLS: inputcols.map(e => ({name: e.name, type: e.type})), row: fh_meta.formdata[0]})
}
})
const get_score = function(resp) {
if ($('#modelchoice').val() != 'TopCause') {
$('#tcresult').hide()
let url = g1.url.parse(window.location)
$.ajax({
url: url + '?_action=score&_metric=' + encodeURIComponent($('#metric').val()),
method: 'POST',
success: function(resp) {
let score = (resp.score * 100).toPrecision(4)
score = Number.parseFloat(score)
$('.donut-segment').attr('stroke-dasharray', `${score} ${100 - score}`)
$('tspan').html(`${score}%`)
$('.donut-segment').attr('stroke', get_score_color(score))
$('#resultcnt').show()
let inputcols = fh_meta.meta.columns.filter((col) => !$('#exclude').val().concat($('#targetcol').val()).includes(col.name))
$('#predicttabtemplate')
.on('template', modifyModelChoice)
.template({COLS: inputcols.map(e => ({name: e.name, type: e.type})), row: fh_meta.formdata[0]})
}
})
} else {
$('#tcresult').show()
$('#tcresult').formhandler({data: resp.result_})
}
}
const post_train = function (target_col) {
$('#resultcnt').hide()
let url = g1.url.parse(window.location)
url.hash = ''
url = url + '?_action=retrain&target_col=' + encodeURIComponent(target_col)
if ($('#modelchoice').val() != 'TopCause') {
url = url + '&_metric=' + encodeURIComponent($('#metric').val())
}
$.ajax({
url: url + '?_action=retrain&target_col=' + encodeURIComponent(target_col) + '&_metric=' + encodeURIComponent($('#metric').val()),
url: url,
method: 'POST',
success: get_score
})
}
const modifyModelChoice = function() {
$('.tcdisable').attr('disabled', $('#modelchoice').val() == 'TopCause')
$('.selectpicker').selectpicker('refresh')
if ($('#modelchoice').val() == 'TopCause') {
let url = g1.url.parse(window.location)
url.hash = ''
$.getJSON(url + '?_params').done(function(result) {
$('#tcresult').show()
$('#tcresult').formhandler({data: result.attrs.result_})
})
} else {
$('#tcresult').hide()
}
}
$(document).ready(function() {
// If TopCause is selected, enable only some inputs
$('#modelchoice').change(modifyModelChoice)
$('#modelchoice').trigger('change')

$('#downloadbtn').hide()
$('#resultcnt').hide()
let url = g1.url.parse(window.location)
Expand All @@ -312,7 +350,9 @@ <h4 id="predResult"></h4>
$('.formhandler').on('load', function(obj) {
fh_meta = obj
let inputcols = obj.meta.columns.filter((col) => !$('#exclude').val().concat($('#targetcol').val()).includes(col.name))
$('#predicttabtemplate').template({COLS: inputcols.map(e => ({name: e.name, type: e.type})), row: obj.formdata[0]})
$('#predicttabtemplate')
.on('template', modifyModelChoice)
.template({COLS: inputcols.map(e => ({name: e.name, type: e.type})), row: obj.formdata[0]})
}).formhandler({
pageSize: 5,
export: false
Expand Down
23 changes: 16 additions & 7 deletions gramex/handlers/mlhandler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
from gramex.handlers import FormHandler
from gramex.http import NOT_FOUND, BAD_REQUEST
from gramex.install import _mkdir, safe_rmtree
from gramex.ml import TopCause
from gramex import cache
import joblib
import pandas as pd
Expand Down Expand Up @@ -224,12 +225,19 @@ def _filterrows(cls, data, **kwargs):

@classmethod
def _assemble_pipeline(cls, data, force=False, mclass='', params=None):
if params is None:
params = {}
# If the model exists, return it
if op.exists(cls.model_path) and not force:
return joblib.load(cls.model_path)

model_kwargs = cls.config_store.load('model', {})
if not mclass:
mclass = model_kwargs.get('class', False)

# No pipeline for TopCause
# If preprocessing is not enabled, return the root model
if not cls.get_opt('pipeline', True):
if mclass == 'TopCause' or not cls.get_opt('pipeline', True):
return search_modelclass(mclass)(**params)

# Else assemble the preprocessing pipeline
Expand All @@ -252,8 +260,6 @@ def _assemble_pipeline(cls, data, force=False, mclass='', params=None):
[('ohe', OneHotEncoder(sparse=False), categoricals),
('scaler', StandardScaler(), numericals)]
)
model_kwargs = cls.config_store.load('model', {})
mclass = model_kwargs.get('class', False)
if mclass:
model = search_modelclass(mclass)(**model_kwargs.get('params', {}))
cls.set_opt('params', model.get_params())
Expand Down Expand Up @@ -318,8 +324,9 @@ def get(self, *path_args, **path_kwargs):
}
try:
model = cache.open(self.model_path, joblib.load)
estimator = model[-1] if hasattr(model, '__getitem__') else model
attrs = {
k: v for k, v in vars(model[-1]).items() if re.search(r'[^_]+_$', k)
k: v for k, v in vars(estimator).items() if re.search(r'[^_]+_$', k)
}
except FileNotFoundError:
attrs = {}
Expand Down Expand Up @@ -367,17 +374,19 @@ def _train(self, data=None):
data = self._filtercols(data)
data = self._filterrows(data)
self.model = self._assemble_pipeline(data, force=True)
if not isinstance(self.model[-1], TransformerMixin):
estimator = self.model[-1] if hasattr(self.model, '__getitem__') else self.model
if not isinstance(estimator, (TransformerMixin, TopCause)):
target = data[target_col]
train = data[[c for c in data if c != target_col]]
_fit(self.model, train, target, self.model_path)
result = {'score': self.model.score(train, target)}
else:
_fit(self.model, data, path=self.model_path)
target = data[target_col] if isinstance(estimator, TopCause) else None
_fit(self.model, data, target, self.model_path)
# Note: Fitted sklearn estimators store their parameters
# in attributes whose names end in an underscore. E.g. in the case of PCA,
# attributes are named `explained_variance_`. The `_train` action returns them.
result = {k: v for k, v in vars(self.model[-1]).items() if re.search(r'[^_]+_$', k)}
result = {k: v for k, v in vars(estimator).items() if re.search(r'[^_]+_$', k)}
return result

def _retrain(self):
Expand Down
2 changes: 1 addition & 1 deletion gramex/topcause.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,6 +176,6 @@ def fit(self, X, y, sample_weight=None): # noqa - capital X is a sklearn conv

results = pd.DataFrame(results).T
results.loc[results['p'] > self.max_p, ('value', 'gain')] = np.nan
self.result_ = results.sort_values('gain', ascending=False)
self.result_ = results.sort_values('gain', ascending=False).reset_index()

return self