stats representation via plotly in to_viz interface #335
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,243 @@ | ||
| from abc import abstractmethod | ||
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| from ads.common.decorator.runtime_dependency import OptionalDependency | ||
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| from typing import List | ||
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| try: | ||
| import plotly | ||
| from plotly.graph_objs import Figure | ||
| import plotly.graph_objects as go | ||
| from plotly.subplots import make_subplots | ||
| except ModuleNotFoundError: | ||
| raise ModuleNotFoundError( | ||
| f"The `plotly` module was not found. Please run `pip install " | ||
| f"{OptionalDependency.FEATURE_STORE}`." | ||
| ) | ||
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| class FeatureStat: | ||
| @abstractmethod | ||
| def add_to_figure(self, fig: Figure, xaxis: int, yaxis: int): | ||
| pass | ||
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| @classmethod | ||
| @abstractmethod | ||
| def from_json(cls, json_dict: dict): | ||
| pass | ||
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| @staticmethod | ||
| def get_x_y_str_axes(xaxis: int, yaxis: int) -> (): | ||
| return ( | ||
| ("xaxis" + str(xaxis + 1)), | ||
| ("yaxis" + str(yaxis + 1)), | ||
| ("x" + str(xaxis + 1)), | ||
| ("y" + str(yaxis + 1)), | ||
| ) | ||
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| class FrequencyDistribution(FeatureStat): | ||
| CONST_FREQUENCY = "frequency" | ||
| CONST_BINS = "bins" | ||
| CONST_FREQUENCY_DISTRIBUTION_TITLE = "Frequency Distribution" | ||
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| def __init__(self, frequency: List, bins: List): | ||
| self.frequency = frequency | ||
| self.bins = bins | ||
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| @classmethod | ||
| def from_json(cls, json_dict: dict) -> "FrequencyDistribution": | ||
| if json_dict is not None: | ||
| return FrequencyDistribution( | ||
| frequency=json_dict.get(FrequencyDistribution.CONST_FREQUENCY), | ||
| bins=json_dict.get(FrequencyDistribution.CONST_BINS), | ||
| ) | ||
| else: | ||
| return None | ||
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| def add_to_figure(self, fig: Figure, xaxis: int, yaxis: int): | ||
| xaxis_str, yaxis_str, x_str, y_str = self.get_x_y_str_axes(xaxis, yaxis) | ||
| if ( | ||
| type(self.frequency) == list | ||
| and type(self.bins) == list | ||
| and 0 < len(self.frequency) == len(self.bins) > 0 | ||
| ): | ||
| fig.add_bar( | ||
| x=self.bins, y=self.frequency, xaxis=x_str, yaxis=y_str, name="" | ||
| ) | ||
| fig.layout.annotations[xaxis].text = self.CONST_FREQUENCY_DISTRIBUTION_TITLE | ||
| fig.layout[xaxis_str]["title"] = "Bins" | ||
| fig.layout[yaxis_str]["title"] = "Frequency" | ||
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| class ProbabilityDistribution(FeatureStat): | ||
| CONST_DENSITY = "density" | ||
| CONST_BINS = "bins" | ||
| CONST_PROBABILITY_DISTRIBUTION_TITLE = "Probability Distribution" | ||
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| def __init__(self, density: List, bins: List): | ||
| self.density = density | ||
| self.bins = bins | ||
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| @classmethod | ||
| def from_json(cls, json_dict: dict): | ||
| if json_dict is not None: | ||
| return cls( | ||
| density=json_dict.get(ProbabilityDistribution.CONST_DENSITY), | ||
| bins=json_dict.get(ProbabilityDistribution.CONST_BINS), | ||
| ) | ||
| else: | ||
| return None | ||
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| def add_to_figure(self, fig: Figure, xaxis: int, yaxis: int): | ||
| xaxis_str, yaxis_str, x_str, y_str = self.get_x_y_str_axes(xaxis, yaxis) | ||
| if ( | ||
| type(self.density) == list | ||
| and type(self.bins) == list | ||
| and 0 < len(self.density) == len(self.bins) > 0 | ||
| ): | ||
| fig.add_bar( | ||
| x=self.bins, | ||
| y=self.density, | ||
| xaxis=x_str, | ||
| yaxis=y_str, | ||
| name="", | ||
| ) | ||
| fig.layout.annotations[xaxis].text = self.CONST_PROBABILITY_DISTRIBUTION_TITLE | ||
| fig.layout[xaxis_str]["title"] = "Bins" | ||
| fig.layout[yaxis_str]["title"] = "Density" | ||
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| return go.Bar(x=self.bins, y=self.density) | ||
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| class TopKFrequentElements(FeatureStat): | ||
| CONST_VALUE = "value" | ||
| CONST_TOP_K_FREQUENT_TITLE = "Top K Frequent Elements" | ||
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| class TopKFrequentElement: | ||
| CONST_VALUE = "value" | ||
| CONST_ESTIMATE = "estimate" | ||
| CONST_LOWER_BOUND = "lower_bound" | ||
| CONST_UPPER_BOUND = "upper_bound" | ||
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| def __init__( | ||
| self, value: str, estimate: int, lower_bound: int, upper_bound: int | ||
| ): | ||
| self.value = value | ||
| self.estimate = estimate | ||
| self.lower_bound = lower_bound | ||
| self.upper_bound = upper_bound | ||
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| @classmethod | ||
| def from_json(cls, json_dict: dict): | ||
| if json_dict is not None: | ||
| return cls( | ||
| value=json_dict.get(cls.CONST_VALUE), | ||
| estimate=json_dict.get(cls.CONST_ESTIMATE), | ||
| lower_bound=json_dict.get(cls.CONST_LOWER_BOUND), | ||
| upper_bound=json_dict.get(cls.CONST_UPPER_BOUND), | ||
| ) | ||
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| else: | ||
| return None | ||
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| def __init__(self, elements: List[TopKFrequentElement]): | ||
| self.elements = elements | ||
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| @classmethod | ||
| def from_json(cls, json_dict: dict): | ||
| if json_dict is not None and json_dict.get(cls.CONST_VALUE) is not None: | ||
| elements = json_dict.get(cls.CONST_VALUE) | ||
| return cls( | ||
| [cls.TopKFrequentElement.from_json(element) for element in elements] | ||
| ) | ||
| else: | ||
| return None | ||
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| def add_to_figure(self, fig: Figure, xaxis: int, yaxis: int): | ||
| xaxis_str, yaxis_str, x_str, y_str = self.get_x_y_str_axes(xaxis, yaxis) | ||
| if type(self.elements) == list and len(self.elements) > 0: | ||
| x_axis = [element.value for element in self.elements] | ||
| y_axis = [element.estimate for element in self.elements] | ||
| fig.add_bar(x=x_axis, y=y_axis, xaxis=x_str, yaxis=y_str, name="") | ||
| fig.layout.annotations[xaxis].text = self.CONST_TOP_K_FREQUENT_TITLE | ||
| fig.layout[yaxis_str]["title"] = "Count" | ||
| fig.layout[xaxis_str]["title"] = "Element" | ||
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| class FeatureStatistics: | ||
|
There was a problem hiding this comment. is it possible to have box plot for other numerical variables. if not we need to settle for |
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| CONST_FREQUENCY_DISTRIBUTION = "FrequencyDistribution" | ||
| CONST_TITLE_FORMAT = "<b>{}</b>" | ||
| CONST_PLOT_FORMAT = "{}_plot" | ||
| CONST_PROBABILITY_DISTRIBUTION = "ProbabilityDistribution" | ||
| CONST_TOP_K_FREQUENT = "TopKFrequentElements" | ||
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| def __init__( | ||
| self, | ||
| feature_name: str, | ||
| top_k_frequent_elements: TopKFrequentElements, | ||
| frequency_distribution: FrequencyDistribution, | ||
| probability_distribution: ProbabilityDistribution, | ||
| ): | ||
| self.feature_name: str = feature_name | ||
| self.top_k_frequent_elements = top_k_frequent_elements | ||
| self.frequency_distribution = frequency_distribution | ||
| self.probability_distribution = probability_distribution | ||
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| @classmethod | ||
| def from_json(cls, feature_name: str, json_dict: dict) -> "FeatureStatistics": | ||
| if json_dict is not None: | ||
| return cls( | ||
| feature_name, | ||
| TopKFrequentElements.from_json(json_dict.get(cls.CONST_TOP_K_FREQUENT)), | ||
| FrequencyDistribution.from_json( | ||
| json_dict.get(cls.CONST_FREQUENCY_DISTRIBUTION) | ||
| ), | ||
| ProbabilityDistribution.from_json( | ||
| json_dict.get(cls.CONST_PROBABILITY_DISTRIBUTION) | ||
| ), | ||
| ) | ||
| else: | ||
| return None | ||
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| @property | ||
| def __stat_count__(self): | ||
| graph_count = 0 | ||
| if self.top_k_frequent_elements is not None: | ||
| graph_count += 1 | ||
| if self.probability_distribution is not None: | ||
| graph_count += 1 | ||
| if self.frequency_distribution is not None: | ||
| graph_count += 1 | ||
| return graph_count | ||
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| @property | ||
| def __feature_stat_objects__(self) -> List[FeatureStat]: | ||
| return [ | ||
| stat | ||
| for stat in [ | ||
| self.top_k_frequent_elements, | ||
| self.frequency_distribution, | ||
| self.probability_distribution, | ||
| ] | ||
| if stat is not None | ||
| ] | ||
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| def to_viz(self): | ||
| graph_count = len(self.__feature_stat_objects__) | ||
| if graph_count > 0: | ||
| fig = make_subplots(cols=graph_count, column_titles=["title"] * graph_count) | ||
| index = 0 | ||
| for stat in [ | ||
| stat for stat in self.__feature_stat_objects__ if stat is not None | ||
| ]: | ||
| stat.add_to_figure(fig, index, index) | ||
| index += 1 | ||
| fig.layout.title = self.CONST_TITLE_FORMAT.format(self.feature_name) | ||
| fig.update_layout(title_font_size=20) | ||
| fig.update_layout(title_x=0.5) | ||
| fig.update_layout(showlegend=False) | ||
|
There was a problem hiding this comment. What's the rationale behind setting There was a problem hiding this comment. it will start showing trace name in subplots for graphs which aren't related |
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| plotly.offline.iplot( | ||
| fig, | ||
| filename=self.CONST_PLOT_FORMAT.format(self.feature_name), | ||
| ) | ||
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we also might need to add integration tests so that we ensure that library is present in the conda pack