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chore(boards): 调整mixpy下sklearn模块

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王立帮
2025-09-24 21:42:24 +08:00
parent b76967b157
commit 26461c6bd0
8 changed files with 135 additions and 49 deletions
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38
boards/default_src/python_mixpy/blocks/sklearn.js
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@@ -168,7 +168,12 @@ export const sklearn_data_target = {
this.appendDummyInput()
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.MIXLY_GET)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.EIGENVALUES, "data"], [Blockly.Msg.LABEL_VALUE, "target"], [Blockly.Msg.FEATURE, "feature_names"], [Blockly.Msg.mixpy_PYLAB_TICKS_TAG, "target_names"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.EIGENVALUES, "data"],
[Blockly.Msg.LABEL_VALUE, "target"],
[Blockly.Msg.FEATURE, "feature_names"],
[Blockly.Msg.mixpy_PYLAB_TICKS_TAG, "target_names"]
]), "type");
this.setOutput(true, null);
this.setColour(SKLEARN_HUE);
this.setTooltip("");
@@ -303,7 +308,10 @@ export const sklearn_DecisionTreeClassifier_Regressor = {
init: function () {
this.appendDummyInput()
.appendField("sklearn " + Blockly.Msg.SKLEARN_DECISIONTREE_INIT)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "DecisionTreeClassifier"], [Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "DecisionTreeRegressor"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "DecisionTreeClassifier"],
[Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "DecisionTreeRegressor"]
]), "type");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
@@ -330,7 +338,10 @@ export const sklearn_RandomForestClassifier_Regressor = {
init: function () {
this.appendDummyInput()
.appendField("sklearn " + Blockly.Msg.SKLEARN_RANDOMFOREST_INIT)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "RandomForestClassifier"], [Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "RandomForestRegressor"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "RandomForestClassifier"],
[Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "RandomForestRegressor"]
]), "type");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
@@ -365,7 +376,10 @@ export const sklearn_KNeighborsClassifier_Regressor = {
init: function () {
this.appendDummyInput()
.appendField("sklearn " + Blockly.Msg.SKLEARN_KNN_INIT)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "KNeighborsClassifier"], [Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "KNeighborsRegressor"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_CLASSIFICATION_ALGORITHM, "KNeighborsClassifier"],
[Blockly.Msg.SKLEARN_REGRESSION_ALGORITHM, "KNeighborsRegressor"]
]), "type");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
@@ -627,7 +641,10 @@ export const sklearn_coef_intercept = {
this.appendDummyInput()
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.MIXLY_GET)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_COEF, "coef_"], [Blockly.Msg.SKLEARN_INTERCEPT, "intercept_"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_COEF, "coef_"],
[Blockly.Msg.SKLEARN_INTERCEPT, "intercept_"]
]), "type");
this.setOutput(true, null);
this.setColour(SKLEARN_HUE);
this.setTooltip("");
@@ -646,7 +663,11 @@ export const sklearn_cluster_centers_labels_inertia = {
.appendField(Blockly.Msg.MODEL_NAME);
this.appendDummyInput()
.appendField(Blockly.Msg.MIXLY_GET)
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_CLUSTER_CENTER, "cluster_centers_"], [Blockly.Msg.SKLEARN_LABELS_AFTER_CLUSTERING, "labels_"], [Blockly.Msg.SKLEARN_CLUSTERING_SUM_OF_SQUARED_DISTANCES, "inertia_"]]), "type");
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_CLUSTER_CENTER, "cluster_centers_"],
[Blockly.Msg.SKLEARN_LABELS_AFTER_CLUSTERING, "labels_"],
[Blockly.Msg.SKLEARN_CLUSTERING_SUM_OF_SQUARED_DISTANCES, "inertia_"]
]), "type");
this.setInputsInline(true);
this.setOutput(true, null);
this.setColour(SKLEARN_HUE);
@@ -662,7 +683,10 @@ export const sklearn_save_load_model = {
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField("sklearn")
.appendField(new Blockly.FieldDropdown([[Blockly.Msg.SKLEARN_SAVE_MODEL, "dump"], [Blockly.Msg.SKLEARN_LOAD_MODEL, "load"]]), "type")
.appendField(new Blockly.FieldDropdown([
[Blockly.Msg.SKLEARN_SAVE_MODEL, "dump"],
[Blockly.Msg.SKLEARN_LOAD_MODEL, "load"]
]), "type")
.appendField(" " + Blockly.Msg.MODEL_NAME);
this.appendValueInput("address")
.setCheck(null)