From 9a19e419ad4b672e9b42c148530eae02abc471a3 Mon Sep 17 00:00:00 2001 From: blizhan Date: Fri, 6 Jan 2023 16:02:00 +0800 Subject: [PATCH] add: 1. moore_voting 2. xgb_boost_trees fix: conditions parse fail --- example.ipynb | 59 +++++- pycdoexpr/__init__.py | 344 ++++++++++++++++++++++------------ pycdoexpr/util.py | 137 ++++++++++++++ readme.md | 22 ++- static/model.pkl | Bin 0 -> 192076 bytes static/moore_voting.jpg | Bin 0 -> 35670 bytes static/xgb_decision_trees.jpg | Bin 0 -> 150962 bytes test/__init__.py | 0 test/test_pycdoexpr.py | 67 +++++++ 9 files changed, 497 insertions(+), 132 deletions(-) create mode 100644 pycdoexpr/util.py create mode 100644 static/model.pkl create mode 100644 static/moore_voting.jpg create mode 100644 static/xgb_decision_trees.jpg create mode 100644 test/__init__.py create mode 100644 test/test_pycdoexpr.py diff --git a/example.ipynb b/example.ipynb index e304770..58b700c 100644 --- a/example.ipynb +++ b/example.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -11,7 +11,7 @@ "\"cdo -expr,'WIND_LEVEL=((WIND>=61.3))? 18:(((WIND>=56.0))? 17:(((WIND>=50.9))? 16:(((WIND>=46.1))? 15:(((WIND>=41.4))? 14:(((WIND>=36.9))? 13:(((WIND>=32.6))? 12:(((WIND>=28.5))? 11:(((WIND>=24.5))? 10:(((WIND>=20.8))? 9:(((WIND>=17.2))? 8:(((WIND>=13.9))? 7:(((WIND>=10.8))? 6:(((WIND>=8.0))? 5:(((WIND>=5.5))? 4:(((WIND>=3.4))? 3:(((WIND>=1.6))? 2:(((WIND>=0.3))? 1:0)))))))))))))))))' infile outfile\"" ] }, - "execution_count": 3, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -58,7 +58,7 @@ "\"cdo expr,'WW=((PRE1H > 0.001))? (((TEM2 >= 3))? (((PRE1H < 0.1))? ( 51): (((PRE1H < 2.5))? ( 61): (((PRE1H < 8))? ( 62): ( 63)))): (((TEM2 >=0))? (((PRE1H < 2.5))? ( 66): ( 67)): (((PRE1H < 0.1))? ( 71): (((PRE1H < 0.2))? ( 73): ( 75))))): (((VIS > 10000))? (((TCC > 80))? ( 3): (((TCC > 40))? ( 2): ( 0))): (((VIS >= 1000))? (((RHU2 > 80))? ( 45): (((RHU2 > 50))? ( 48): ( 31))): (((WS10 < 1))? ( 45): (((RHU2 >=50))? ( 45): ( 34)))))' infile outfile\"" ] }, - "execution_count": 4, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -114,6 +114,55 @@ "expr = cexpr.conditions(s, verbose=True)\n", "f\"cdo expr,'WW={expr}' infile outfile\"\n" ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"cdo -expr,'_count=0;\\nMAJOR=0;\\n_tmp=MAJOR;\\n_tmp=((_count == 0))? ( a): ( _tmp);\\n_count=((_count == 0))? ( 1): (((MAJOR == a))? ( _count + 1): ( _count - 1));\\nMAJOR=_tmp;\\n_tmp=((_count == 0))? ( b): ( _tmp);\\n_count=((_count == 0))? ( 1): (((MAJOR == b))? ( _count + 1): ( _count - 1));\\nMAJOR=_tmp;\\n_tmp=((_count == 0))? ( c): ( _tmp);\\n_count=((_count == 0))? ( 1): (((MAJOR == c))? ( _count + 1): ( _count - 1));\\nMAJOR=_tmp;\\n' infile outfile\"" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "expr = cexpr.moore_voting(voters=['a' ,'b', 'c'], varname='MAJOR')\n", + "f\"cdo -expr,'{expr}' infile outfile\"" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"cdo -expr, '_VALUE0=((f1<127.5))? (((f7<28.5))? (((f5<45.4000015))? (((f5<30.9500008))? (-0.569032252): (((f6<0.904500008))? (((f3<5.5))? (-0.157894745): (-0.454545468)): (-0))): (0.150000006)): (((f5<26.3500004))? (((f5<20.2000008))? (-0): (-0.541463435)): (((f1<99.5))? (((f6<0.715999961))? (-0.425000012): (((f0<5.5))? (-0.200000018): (0.120000005))): (((f6<0.56099999))? 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Defaults to None then return indices. + map_indices (list, optional): map_indices list. Defaults to None then return indices. right (bool, optional): if equal operator in the right (greater than: bins[i-1]< x <=bins[i]). Defaults to False (not less than: bins[i-1]<= x str: + """parse python-syntax paragraph + + Args: + parag (str): paragraph + verbose (bool, optional): print condtion tree or not. Defaults to True. + + Returns: + str: expr + """ + sentences = [p for p in parag.split("\n") if len(p)] + kw_list, cond_list, value_list = self.parse_sentences(sentences) + root = construct_tree(kw_list, cond_list) + leaves = [i for i in root.postorder if i.value in [0, 1]] + for l, i in zip(leaves, value_list): + l.value = i.value + if verbose: + root.pprint() + expr = construct_expr(root) + return expr + + def moore_voting(self, voters:list, varname:str='MAJOR')->str: + """generate moore vote expression + + Args: + voters (list): voter varname in file + varname (str, optional): output varname. Defaults to 'MAJOR'. + + Returns: + str: expr + """ + + expr = '_count=0;\n' + expr += f'{varname}=0;\n' + expr += f'_tmp={varname};\n' + for v in voters[:]: + + tmp_expr = self.conditions( + f''' + if _count == 0: + _tmp = {v} + else: + _tmp = _tmp + ''' + ) + expr += f'_tmp={tmp_expr};\n' + count_expr = self.conditions( + f''' + if _count == 0: + _count = 1 + else: + if {varname} == {v}: + _count = _count + 1 + else: + _count = _count - 1 + ''' + ) + expr += f'_count={count_expr};\n' + expr += f'{varname}=_tmp;\n' + + return expr + - def _cond_compare_operator(self, varname:str, patt:str, bins:list,map_list:list): + + + def _cond_compare_operator( + self, varname: str, patt: str, bins: list, map_list: list + ): expr = None - assert len(bins)==len(map_list)-1 - if len(map_list)==2: - expr = patt.format(varname=varname,bin_value=bins[0],true_value=map_list[0],false_value=map_list[1]) + assert len(bins) == len(map_list) - 1 + if len(map_list) == 2: + expr = patt.format( + varname=varname, + bin_value=bins[0], + true_value=map_list[0], + false_value=map_list[1], + ) return expr else: - last_expr = self._cond_compare_operator(varname, patt, bins[1:], map_list[1:]) - expr = patt.format(varname=varname,bin_value=bins[0],true_value=map_list[0],false_value=f'({last_expr})') + last_expr = self._cond_compare_operator( + varname, patt, bins[1:], map_list[1:] + ) + expr = patt.format( + varname=varname, + bin_value=bins[0], + true_value=map_list[0], + false_value=f"({last_expr})", + ) return expr - def _nlt_cond_patt(self)->str: - return '(({varname}>={bin_value}))? {true_value}:{false_value}' + def _nlt_cond_patt(self) -> str: + return "(({varname}>={bin_value}))? {true_value}:{false_value}" - def _gt_cond_patt(self)->str: - return '(({varname}>{bin_value}))? {true_value}:{false_value}' + def _gt_cond_patt(self) -> str: + return "(({varname}>{bin_value}))? {true_value}:{false_value}" - def _lt_cond_patt(self)->str: - return '(({varname}<{bin_value}))? {true_value}:{false_value}' + def _lt_cond_patt(self) -> str: + return "(({varname}<{bin_value}))? {true_value}:{false_value}" - def _ngt_cond_patt(self)->str: - return '(({varname}<={bin_value}))? {true_value}:{false_value}' + def _ngt_cond_patt(self) -> str: + return "(({varname}<={bin_value}))? {true_value}:{false_value}" - def _cond_patt(self)->str: - return '((condition))? (true_value): (false_value)' + def _cond_patt(self) -> str: + return "((condition))? (true_value): (false_value)" - def parse_sentences(self, sentences:list)->tuple: + def parse_sentences(self, sentences: list) -> tuple: """parse sentences as keyward list, condition list and value list Args: @@ -98,139 +192,141 @@ def parse_sentences(self, sentences:list)->tuple: for s in sentences: node = self.parse_sentence(s) if node is None: - if 'else' in s: - kw_list.append('else') + if "else" in s: + kw_list.append("else") else: - if node.node_type == 'condition': - if 'elif' in s: - kw_list.append('else') - kw_list.append('if') + if node.node_type == "condition": + if "elif" in s: + kw_list.append("else") + kw_list.append("if") cond_list.append(node) else: - kw_list.append('if') + kw_list.append("if") cond_list.append(node) - elif node.node_type == 'value': + elif node.node_type == "value": value_list.append(node) return kw_list, cond_list, value_list - def parse_sentence(self, sentence:str)->cond_node: + def parse_sentence(self, sentence: str) -> decision_tree_node: """match single sentence as cond/value node Args: sentence (str): str Returns: - cond_node: conditon / value node + decision_tree_node: conditon / value node """ - cond_pattern='^([\s\t^i]+if|[\s\t^i]+elif|if|elif)\s+([^\:]+)\:' - value_pattern = '^([\s\t]+)([A-Za-z\d]+[\s=]+[A-Za-z\d\.]+)' + cond_pattern = "^([\s\t^i]+if|[\s\t^i]+elif|if|elif)\s+([^\:]+)\:" + value_pattern = "^([\s\t]+)([A-Za-z\_\d]+[\s=]+[A-Za-z\d\s\+\.\-\_]+)" match = re.match(cond_pattern, sentence) - indent_pattern = '^([\s\t]+)(if|else|^\s[A-Za-z\s\d\.=]+)' + indent_pattern = "^([\s\t]+)(if|else|^\s[A-Za-z\s\d\.=]+)" if match: match_indent = re.match(indent_pattern, match[1]) - indent = len(match_indent[1])/4 if match_indent else 0 - return cond_node(node_type='condition', value=match[2], indent=indent) + indent = len(match_indent[1]) / 4 if match_indent else 0 + return decision_tree_node(node_type="condition", value=match[2], number=indent, child_number=()) else: match = re.match(value_pattern, sentence) if match: - indent = len(match[1])/4 - return cond_node(node_type='value', value=match[2], indent=indent) + indent = len(match[1]) / 4 + return decision_tree_node(node_type="value", value=match[2], number=indent, child_number=()) return None - def _construct_tree(self,kw:list, cond:list)->Node: - """construct condition binary tree with keyword list and condition list + def parse_xgb_sentence(self, sentence: str) -> decision_tree_node: + """match single sentence as cond/value node Args: - kw (list): keyword list - cond (list): condition list + sentence (str): str Returns: - Node: binary tree root node + decision_tree_node: conditon / value node """ - if len(kw)==2 and len(cond)==1 and kw[0]=='if' and kw[1] == 'else': - left = Node(value=0) - right = Node(value=1) - root = Node(value=cond[0].value, left=left, right=right) - return root + cond_pattern = "^([\s\t]+\d+|\d+):\[([^\s]+)\]\syes=(\d+),no=(\d+),missing=(\d+)" + value_pattern = "^([\s\t]+\d+|\d+):(leaf=[^\s]+)" + match = re.match(cond_pattern, sentence) + indent_pattern = "^([\s\t]+|)(\d+)" + if match: + match_number = re.match(indent_pattern, match[1]) + number = int(match_number[2]) + child = int(match[3]), int(match[4]) + return decision_tree_node(node_type="condition", value=match[2], number=number,child_number=child) else: - stack = [] - for n,k in enumerate(kw): - if k == 'if': - stack.append(n) - elif k == 'else': - idx = stack.pop() - if len(stack) == 0: - if_index = idx - else_index = n - break - - root = Node(value=cond[if_index].value) - - if if_index+1 == else_index: - left = Node(0) - right = self._construct_tree(kw[else_index+1:],cond[if_index+1:]) - elif if_index+1 < else_index: - cond_num = kw[if_index+1:else_index-1].count('if') - left = self._construct_tree(kw[if_index+1:else_index], cond[1:cond_num+1]) - if len(kw[else_index+1:])<=1: - right = Node(1) - else: - right = self._construct_tree(kw[else_index+1:], cond[cond_num+1:]) - - root.left = left - root.right = right - return root + match = re.match(value_pattern, sentence) + if match: + match_number = re.match(indent_pattern, match[1]) + number = int(match_number[2]) + return decision_tree_node(node_type="value", value=match[2], number=number, child_number=()) + return None - def _construct_expr(self, node:Node)->str: - """construct cdo condition expr from binary tree root node + def parse_xgb_single_tree(self, xgb_tree:str) -> Node: + """parse xgb single tree text to binary tree node Args: - node (Node): root node + xgb_tree (str): str Returns: - str: expr str + Node: binary tree node """ - patt = '(({condition}))? ({true_value}): ({false_value})' - if node.max_leaf_depth == 1: - res = patt.format(condition=node.value, true_value=node.left.value.split('=')[-1], false_value=node.right.value.split('=')[-1]) - return res - else: - if node.left.max_leaf_depth>=1: - left = self._construct_expr(node.left) - else: - left = node.left.value.split('=')[-1] - if node.right.max_leaf_depth>=1: - right = self._construct_expr(node.right) - else: - right = node.right.value.split('=')[-1] - res = patt.format(condition=node.value, true_value=left, false_value=right) - return res - - def conditions(self, parag:str, verbose:bool=False)->str: - """parse python-syntax paragraph - - Args: - parag (str): paragraph - verbose (bool, optional): print condtion tree or not. Defaults to True. + sentences = xgb_tree.split('\n') + nodes = {} + for s in sentences: + n = self.parse_xgb_sentence(s) + if n is not None: + nodes[n.number] = n - Returns: - str: expr - """ - sentences = [p for p in parag.split('\n') if len(p)] - kw_list, cond_list, value_list = self.parse_sentences(sentences) - root = self._construct_tree(kw_list, cond_list) - leaves = [i for i in root.postorder if i.value in [0,1]] - for l,i in zip(leaves,value_list): - l.value = i.value - if verbose: - root.pprint() - expr = self._construct_expr(root) - return expr + root = construct_tree_with_tree_nodes(nodes) + return root + + def xgb_decision_trees(self, pkl:str, ensemble:str) -> str: + with open(pkl, 'rb') as f: + m = pickle.load(f) + booster = m.get_booster() + trees = booster.get_dump() + + result_expr = '' + ensemble_list = [] + for i,tree in enumerate(trees): + tree_root = self.parse_xgb_single_tree(tree) + expr = construct_expr(tree_root) + result_expr += f"_VALUE{i}={expr};\n" + ensemble_list.append(f"_VALUE{i}") + + if ensemble == 'averaging': + result_expr += f"VALUE=({'+'.join(ensemble_list)}) / {len(ensemble_list)};\n" + elif ensemble == 'boosting': + result_expr += f"VALUE={'+'.join(ensemble_list)};\n" + elif ensemble == 'moore_voting': + result_expr += self.moore_voting(ensemble_list, 'VALUE') + + return result_expr + def test(): e = cdoexpr() - expr = e.digitize('wind',[61.3, 56. , 50.9, 46.1, 41.4, 36.9, 32.6, 28.5, 24.5, 20.8, 17.2, 13.9, 10.8, 8. , 5.5, 3.4, 1.6, 0.3]) + expr = e.digitize( + "wind", + [ + 61.3, + 56.0, + 50.9, + 46.1, + 41.4, + 36.9, + 32.6, + 28.5, + 24.5, + 20.8, + 17.2, + 13.9, + 10.8, + 8.0, + 5.5, + 3.4, + 1.6, + 0.3, + ], + ) print(expr) -if __name__ == '__main__': - test() \ No newline at end of file + +if __name__ == "__main__": + test() diff --git a/pycdoexpr/util.py b/pycdoexpr/util.py new file mode 100644 index 0000000..3954ffc --- /dev/null +++ b/pycdoexpr/util.py @@ -0,0 +1,137 @@ +from binarytree import Node + + +def construct_tree(kw: list, cond: list) -> Node: + """construct condition binary tree with keyword list and condition list + + Args: + kw (list): keyword list + cond (list): condition list + + Returns: + Node: binary tree root node + """ + if len(kw) == 2 and len(cond) == 1 and kw[0] == "if" and kw[1] == "else": + left = Node(value=0) + right = Node(value=1) + root = Node(value=cond[0].value, left=left, right=right) + return root + else: + stack = [] + for n, k in enumerate(kw): + if k == "if": + stack.append(n) + elif k == "else": + idx = stack.pop() + if len(stack) == 0: + if_index = idx + else_index = n + break + + root = Node(value=cond[if_index].value) + + if if_index + 1 == else_index: + left = Node(0) + right = construct_tree(kw[else_index + 1 :], cond[if_index + 1 :]) + elif if_index + 1 < else_index: + cond_num = kw[if_index + 1 : else_index - 1].count("if") + left = construct_tree(kw[if_index + 1 : else_index], cond[1 : cond_num + 1]) + if len(kw[else_index + 1 :]) <= 1: + right = Node(1) + else: + right = construct_tree(kw[else_index + 1 :], cond[cond_num + 1 :]) + + root.left = left + root.right = right + return root + +def construct_tree_with_tree_nodes(nodes:dict)->Node: + """construct condition binary tree with decision tree nodes dict + + Args: + nodes (dict): decision tree node dictionary + + Returns: + Node: binary tree node + """ + + def _construct_xgb_tree_node(root_number:int)->Node: + n = nodes[root_number] + root = Node(n.value) + if len(n.child_number): + left, right = _construct_xgb_tree_node(n.child_number[0]), _construct_xgb_tree_node(n.child_number[1]) + root.left, root.right = left, right + return root + + root = _construct_xgb_tree_node(0) + return root + +def get_max_min_leaf_depth(root: Node) -> tuple: + """get max min leaf depth from root + + Args: + root (Node): _description_ + + Returns: + tuple: max_leaf_depth, min_leaf_depth + """ + + size = 0 + leaf_count = 0 + min_leaf_depth = 0 + max_leaf_depth = -1 + is_strict = True + current_nodes = [root] + + while len(current_nodes) > 0: + max_leaf_depth += 1 + next_nodes = [] + for node in current_nodes: + size += 1 + # Node is a leaf. + if node.left is None and node.right is None: + if min_leaf_depth == 0: + min_leaf_depth = max_leaf_depth + leaf_count += 1 + + if node.left is not None: + + next_nodes.append(node.left) + + if node.right is not None: + + next_nodes.append(node.right) + + # If we see a node with only one child, it is not strict + is_strict &= (node.left is None) == (node.right is None) + current_nodes = next_nodes + return max_leaf_depth, min_leaf_depth + +def construct_expr(node: Node) -> str: + """construct cdo condition expr from binary tree root node + + Args: + node (Node): root node + + Returns: + str: expr str + """ + patt = "(({condition}))? ({true_value}): ({false_value})" + if get_max_min_leaf_depth(node)[0] == 1: + res = patt.format( + condition=node.value, + true_value=node.left.value.split("=")[-1], + false_value=node.right.value.split("=")[-1], + ) + return res + else: + if get_max_min_leaf_depth(node.left)[0] >= 1: + left = construct_expr(node.left) + else: + left = node.left.value.split("=")[-1] + if get_max_min_leaf_depth(node.right)[0] >= 1: + right = construct_expr(node.right) + else: + right = node.right.value.split("=")[-1] + res = patt.format(condition=node.value, true_value=left, false_value=right) + return res diff --git a/readme.md b/readme.md index 8f746b7..251264e 100644 --- a/readme.md +++ b/readme.md @@ -19,7 +19,7 @@ from pycdoexpr import cdoexpr wind_level_bins = [ 0.3, 1.6, 3.4, 5.5, 8. , 10.8, 13.9, 17.2,\ 20.8, 24.5, 28.5, 32.6, 36.9, 41.4, 46.1, 50.9, 56. , 61.3] cexpr = cdoexpr() -cexpr.digitize(varname='WIND_LEVEL', right=False) +cexpr.digitize(varname='WIND_LEVEL', bins=wind_level_bins, right=False) ``` 2. convert multi-level conditions string in python syntax to cdo expr @@ -78,8 +78,24 @@ f"cdo expr,'WW={expr}' infile outfile" ``` ![](static/conditions.jpg) -3. convert single xgboost / sklearn tree to expr - - [ ] TODO +3. moore voting +```python + +# EX3: generate moore voting cdo expression +expr = cexpr.moore_voting(voters=['a' ,'b', 'c'], varname='MAJOR') +f"cdo -expr,'{expr}' infile outfile" +``` +![](static/moore_voting.jpg) + +4. convert multi xgboost tree to expr with ensemble method (averaging, boosting, moore_voting) *experimental* +```python + +# EX4: convert a xgb decision trees model to cdo expression + +expr = cexpr.xgb_decision_trees('./static/model.pkl',ensemble='averaging') +f"cdo -expr, '{expr}' infile outfile" +``` +![](static/xgb_decision_trees.jpg) ## Benchmark diff --git a/static/model.pkl b/static/model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..c9acf3b8cbc93282fd3ad14879633297e515f7ab GIT binary patch literal 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--git a/test/test_pycdoexpr.py b/test/test_pycdoexpr.py new file mode 100644 index 0000000..854fe79 --- /dev/null +++ b/test/test_pycdoexpr.py @@ -0,0 +1,67 @@ +from pycdoexpr import cdoexpr + +def test_digitize(): + cexpr = cdoexpr() + wind_level_bins = [ 0.3, 1.6, 3.4, 5.5, 8. , 10.8, 13.9, 17.2,\ + 20.8, 24.5, 28.5, 32.6, 36.9, 41.4, 46.1, 50.9, 56. , 61.3] + wind_level = range(0,len(wind_level_bins)+1) + expr = cexpr.digitize('WIND', wind_level_bins, wind_level, right=False) + +def test_conditions(): + cexpr = cdoexpr() + s = ''' + if PRE1H > 0.001: + if TEM2 >= 3: + if PRE1H < 0.1: + WW = 51 + elif PRE1H < 2.5: + WW = 61 + elif PRE1H < 8: + WW = 62 + else: + WW = 63 + elif TEM2 >=0: + if PRE1H < 2.5: + WW = 66 + else: + WW = 67 + else: + if PRE1H < 0.1: + WW = 71 + elif PRE1H < 0.2: + WW = 73 + else: + WW = 75 + else: + if VIS > 10000: + if TCC > 80: + WW = 3 + elif TCC > 40: + WW = 2 + else: + WW = 0 + elif VIS >= 1000: + if RHU2 > 80: + WW = 45 + elif RHU2 > 50: + WW = 48 + else: + WW = 31 + else: + if WS10 < 1: + WW = 45 + else: + if RHU2 >=50: + WW = 45 + else: + WW = 34 + ''' + expr = cexpr.conditions(s, verbose=True) + +def test_moore_voting(): + cexpr = cdoexpr() + expr = cexpr.moore_voting(['a' ,'b', 'c'], 'MAJOR') + +def test_xgb_decision_trees(): + cexpr = cdoexpr() + expr = cexpr.xgb_decision_trees('./static/model.pkl',ensemble='averaging') \ No newline at end of file