From 3bfeb4105f1269591b57030ab60779fc1c0053aa Mon Sep 17 00:00:00 2001 From: Ali Abid Date: Wed, 28 Jul 2021 11:21:28 -0700 Subject: [PATCH] timeseries commit --- demo/fraud_detector.py | 23 + frontend/package-lock.json | 5923 ++++++++++++++++++ frontend/package.json | 2 + frontend/src/components.jsx | 2 + frontend/src/interfaces/input/timeseries.jsx | 121 + frontend/src/themes/defaults.scss | 12 + frontend/src/utils.jsx | 28 + gradio.egg-info/SOURCES.txt | 4 + gradio.egg-info/requires.txt | 22 +- gradio/frontend/asset-manifest.json | 6 +- gradio/frontend/index.html | 2 +- gradio/inputs.py | 74 +- 12 files changed, 6177 insertions(+), 42 deletions(-) create mode 100644 demo/fraud_detector.py create mode 100644 frontend/src/interfaces/input/timeseries.jsx diff --git a/demo/fraud_detector.py b/demo/fraud_detector.py new file mode 100644 index 0000000000..8f476cc116 --- /dev/null +++ b/demo/fraud_detector.py @@ -0,0 +1,23 @@ +import gradio as gr +import pandas as pd +import random + +def fraud_detector(card_activity, categories, sensitivity): + activity_range = random.randint(0, 100) + return {"fraud": activity_range / 100., "not fraud": 1 - activity_range / 100.} + +iface = gr.Interface(fraud_detector, + [ + gr.inputs.Timeseries( + x="time", + y=["retail", "food", "other"] + ), + gr.inputs.CheckboxGroup(["retail", "food", "other"], default=["retail", "food", "other"]), + gr.inputs.Slider(1,3) + ], + [ + gr.outputs.Label(label="Fraud Level"), + ] +) +if __name__ == "__main__": + iface.launch() diff --git a/frontend/package-lock.json b/frontend/package-lock.json index 6f63e8b38e..a32c6d2d66 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -19,9 +19,11 @@ "fabric": "^4.5.0", "html2canvas-objectfit-fix": "^1.2.0", "jspreadsheet-ce": "^4.7.3", + "plotly.js": "^2.3.0", "react": "^17.0.2", "react-dom": "^17.0.2", "react-json-tree": "^0.15.0", + "react-plotly.js": "^2.5.1", "react-scripts": "4.0.3", "react-webcam": "^5.2.3", "sass": "^1.32.8", @@ 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"@mapbox/point-geometry": "0.1.0", + "@mapbox/vector-tile": "^1.3.1", + "pbf": "^3.2.1" + } + }, "w3c-hr-time": { "version": "1.0.2", "resolved": "https://registry.npmjs.org/w3c-hr-time/-/w3c-hr-time-1.0.2.tgz", @@ -37117,11 +43006,29 @@ "minimalistic-assert": "^1.0.0" } }, + "weak-map": { + "version": "1.0.5", + "resolved": "https://registry.npmjs.org/weak-map/-/weak-map-1.0.5.tgz", + "integrity": "sha1-eWkVhNmGB/UHC9O3CkDmuyLkAes=" + }, + "weakmap-shim": { + "version": "1.1.1", + "resolved": "https://registry.npmjs.org/weakmap-shim/-/weakmap-shim-1.1.1.tgz", + "integrity": "sha1-1lr9eEEJshZuAP9XHDMVDsKkC0k=" + }, "web-vitals": { "version": "1.1.1", "resolved": "https://registry.npmjs.org/web-vitals/-/web-vitals-1.1.1.tgz", "integrity": "sha512-jYOaqu01Ny1NvMwJ3dBJDUOJ2PGWknZWH4AUnvFOscvbdHMERIKT2TlgiAey5rVyfOePG7so2JcXXZdSnBvioQ==" }, + "webgl-context": { + "version": "2.2.0", + "resolved": "https://registry.npmjs.org/webgl-context/-/webgl-context-2.2.0.tgz", + "integrity": "sha1-jzfXJXz23xzQpJ5qextyG5TMhqA=", + "requires": { + "get-canvas-context": "^1.0.1" + } + }, "webidl-conversions": { "version": "6.1.0", "resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-6.1.0.tgz", @@ -38312,6 +44219,14 @@ "microevent.ts": "~0.1.1" } }, + "world-calendars": { + "version": "1.0.3", + "resolved": "https://registry.npmjs.org/world-calendars/-/world-calendars-1.0.3.tgz", + "integrity": "sha1-slxQMrokEo/8QdCfr0pewbnBQzU=", + "requires": { + "object-assign": "^4.1.0" + } + }, "wrap-ansi": { "version": "6.2.0", "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-6.2.0.tgz", @@ -38412,6 +44327,14 @@ "version": "0.1.0", "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==" + }, + "zero-crossings": { + "version": "1.0.1", + "resolved": "https://registry.npmjs.org/zero-crossings/-/zero-crossings-1.0.1.tgz", + "integrity": "sha1-xWK9MRNkPzRDokXRJAa4i2m5qf8=", + "requires": { + "cwise-compiler": "^1.0.0" + } } } } diff --git a/frontend/package.json b/frontend/package.json index eaf51c8a10..4d7bda59bc 100644 --- a/frontend/package.json +++ b/frontend/package.json @@ -14,9 +14,11 @@ "fabric": "^4.5.0", "html2canvas-objectfit-fix": "^1.2.0", "jspreadsheet-ce": "^4.7.3", + "plotly.js": "^2.3.0", "react": "^17.0.2", "react-dom": "^17.0.2", "react-json-tree": "^0.15.0", + "react-plotly.js": "^2.5.1", "react-scripts": "4.0.3", "react-webcam": "^5.2.3", "sass": "^1.32.8", diff --git a/frontend/src/components.jsx b/frontend/src/components.jsx index 27f047db9a..764d35f546 100644 --- a/frontend/src/components.jsx +++ b/frontend/src/components.jsx @@ -9,6 +9,7 @@ import { NumberInput, NumberInputExample } from './interfaces/input/number'; import { RadioInput, RadioInputExample } from './interfaces/input/radio'; import { SliderInput, SliderInputExample } from './interfaces/input/slider'; import { TextboxInput, TextboxInputExample } from './interfaces/input/textbox'; +import { TimeseriesInput, TimeseriesInputExample } from './interfaces/input/timeseries'; import { VideoInput, VideoInputExample } from './interfaces/input/video'; import { AudioOutput, AudioOutputExample } from './interfaces/output/audio'; @@ -36,6 +37,7 @@ let input_component_map = { "radio": [RadioInput, RadioInputExample], "slider": [SliderInput, SliderInputExample], "textbox": [TextboxInput, TextboxInputExample], + "timeseries": [TimeseriesInput, TimeseriesInputExample], "video": [VideoInput, VideoInputExample], } let output_component_map = { diff --git a/frontend/src/interfaces/input/timeseries.jsx b/frontend/src/interfaces/input/timeseries.jsx new file mode 100644 index 0000000000..489121ce0c --- /dev/null +++ b/frontend/src/interfaces/input/timeseries.jsx @@ -0,0 +1,121 @@ +import React from 'react'; +import ComponentExample from '../component_example'; +import { CSVToArray } from '../../utils'; +import Plot from 'react-plotly.js'; + +class TimeseriesInput extends React.Component { + constructor(props) { + super(props); + this.handleChange = this.handleChange.bind(this); + this.uploader = React.createRef(); + this.openFileUpload = this.openFileUpload.bind(this); + this.load_preview_from_files = this.load_preview_from_files.bind(this); + this.load_preview_from_upload = this.load_preview_from_upload.bind(this); + this.load_preview_from_drop = this.load_preview_from_drop.bind(this); + } + handleChange(data) { + this.props.handleChange(data); + } + openFileUpload() { + this.uploader.current.click(); + } + render() { + let no_action = (evt) => { + evt.preventDefault(); + evt.stopPropagation(); + } + if (this.props.value !== null) { + let file = this.props.value[0]; + return ( +
+ { + return { + x: this.props.value["data"].map(row => row[this.state.x_index]), + y: this.props.value["data"].map(row => row[y_index]), + type: 'line', + name: this.props.y[i] + } + })} + layout={{ + width: 480, + height: 320, + title: {text: "Card Activity"}, + xAxis: {title: {text: "Day"}}, + yAxis: {title: {text: "Spend"}}, + }} + /> +
) + } else { + return ( +
+
+ Upload Timeseries CSV + {this.props.x !== null ? <> +
+ X Column: {this.props.x} +
+ Y Column: {this.props.y.join(", ")} + : false} +
+ +
) + } + } + load_preview_from_drop(evt) { + this.load_preview_from_files(evt.dataTransfer.files) + } + load_preview_from_upload(evt) { + this.load_preview_from_files(evt.target.files); + } + load_file(reader) { + let lines = reader.result; + let headers = null; + let data = null; + if (lines && lines.length > 0) { + let line_array = CSVToArray(lines); + if (line_array.length === 0) { + return; + } + if (this.props.x === null) { + this.setState({ "x_index": 0, "y_indices": [1] }) + data = line_array; + } else { + let x_index = line_array[0].indexOf(this.props.x); + let y_indices = this.props.y.map(y_col => line_array[0].indexOf(y_col)); + if (x_index === -1) { + alert("Missing x column: " + this.props.x); + return; + } + if (y_indices.includes(-1)) { + alert("Missing y column: " + this.props.y[y_indices.indexOf(-1)]); + return; + } + this.setState({ "x_index": x_index, "y_indices": y_indices }) + headers = line_array[0]; + data = line_array.slice(1); + } + this.handleChange({ "headers": headers, "data": data }); + } + } + load_preview_from_files(files) { + if (!files.length || !window.FileReader) { + return; + } + this.file_data = []; + for (let file of files) { + let ReaderObj = new FileReader() + ReaderObj.readAsBinaryString(file) + ReaderObj.onloadend = this.load_file.bind(this, ReaderObj); + } + } +} + + +class TimeseriesInputExample extends ComponentExample { + render() { + return
{this.props.value}
+ } +} + +export { TimeseriesInput, TimeseriesInputExample }; diff --git a/frontend/src/themes/defaults.scss b/frontend/src/themes/defaults.scss index d82a328e2d..fe41b3e11a 100644 --- a/frontend/src/themes/defaults.scss +++ b/frontend/src/themes/defaults.scss @@ -388,6 +388,18 @@ @apply text-2xl p-2; } } + .input_timeseries { + @apply w-full h-96; + .upload_zone { + @apply border-8 border-gray-300 border-dashed w-full h-full flex justify-center items-center text-3xl text-gray-400 text-center cursor-pointer leading-10; + } + .file_preview_holder { + @apply w-full h-full flex flex-col justify-center items-center relative inline-block; + } + .js-plotly-plot, .plotly.js-plotly-plot * { + position: static !important; + } + } /* Output Components */ .output_text { word-break: break-word; diff --git a/frontend/src/utils.jsx b/frontend/src/utils.jsx index 1d8c52c34b..1af1afa4eb 100644 --- a/frontend/src/utils.jsx +++ b/frontend/src/utils.jsx @@ -107,3 +107,31 @@ export function array_compare(a1, a2) { } return true; } + +export function CSVToArray(strData, strDelimiter) { + strDelimiter = (strDelimiter || ","); + let objPattern = new RegExp( + ( + "(\\" + strDelimiter + "|\\r?\\n|\\r|^)" + + "(?:\"([^\"]*(?:\"\"[^\"]*)*)\"|" + + "([^\"\\" + strDelimiter + "\\r\\n]*))" + ), + "gi" + ); + let arrData = [[]]; + let arrMatches = null; + while (arrMatches = objPattern.exec(strData)) { + let strMatchedDelimiter = arrMatches[1]; + let strMatchedValue = []; + if (strMatchedDelimiter.length && (strMatchedDelimiter != strDelimiter)) { + arrData.push([]); + } + if (arrMatches[2]) { + strMatchedValue = arrMatches[2].replace(new RegExp("\"\"", "g"), "\""); + } else { + strMatchedValue = arrMatches[3]; + } + arrData[arrData.length - 1].push(strMatchedValue); + } + return (arrData); +} diff --git a/gradio.egg-info/SOURCES.txt b/gradio.egg-info/SOURCES.txt index e645b272dd..dd2d66f2b5 100644 --- a/gradio.egg-info/SOURCES.txt +++ b/gradio.egg-info/SOURCES.txt @@ -32,6 +32,8 @@ gradio/frontend/static/bundle.css.map gradio/frontend/static/bundle.js gradio/frontend/static/bundle.js.LICENSE.txt gradio/frontend/static/bundle.js.map +gradio/frontend/static/css/main.2056a447.css +gradio/frontend/static/css/main.2056a447.css.map gradio/frontend/static/css/main.337638fd.css gradio/frontend/static/css/main.337638fd.css.map gradio/frontend/static/css/main.347bef8c.css @@ -42,6 +44,8 @@ gradio/frontend/static/css/main.bc3b604e.css gradio/frontend/static/css/main.bc3b604e.css.map gradio/frontend/static/css/main.c7572f0f.css gradio/frontend/static/css/main.c7572f0f.css.map +gradio/frontend/static/css/main.c770ef42.css +gradio/frontend/static/css/main.c770ef42.css.map gradio/frontend/static/media/logo_loading.e93acd82.jpg test/test_demos.py test/test_inputs.py diff --git a/gradio.egg-info/requires.txt b/gradio.egg-info/requires.txt index 8e565209f9..b6135b3e41 100644 --- a/gradio.egg-info/requires.txt +++ b/gradio.egg-info/requires.txt @@ -1,15 +1,15 @@ -numpy -scipy -matplotlib -pandas -pillow +Flask-Cors>=3.0.8 +Flask-Login +Flask>=1.1.1 +analytics-python ffmpy +flask-cachebuster markdown2 +matplotlib +numpy +pandas +paramiko +pillow pycryptodome requests -paramiko -analytics-python -Flask>=1.1.1 -Flask-Cors>=3.0.8 -flask-cachebuster -Flask-Login +scipy diff --git a/gradio/frontend/asset-manifest.json b/gradio/frontend/asset-manifest.json index 4d463771db..98e5347580 100644 --- a/gradio/frontend/asset-manifest.json +++ b/gradio/frontend/asset-manifest.json @@ -1,17 +1,17 @@ { "files": { - "main.css": "/static/css/main.337638fd.css", + "main.css": "/static/css/main.c770ef42.css", "main.js": "/static/bundle.js", "main.js.map": "/static/bundle.js.map", "index.html": "/index.html", "static/bundle.css.map": "/static/bundle.css.map", "static/bundle.js.LICENSE.txt": "/static/bundle.js.LICENSE.txt", - "static/css/main.337638fd.css.map": "/static/css/main.337638fd.css.map", + "static/css/main.c770ef42.css.map": "/static/css/main.c770ef42.css.map", "static/media/logo_loading.e93acd82.jpg": "/static/media/logo_loading.e93acd82.jpg" }, "entrypoints": [ "static/bundle.css", - "static/css/main.337638fd.css", + "static/css/main.c770ef42.css", "static/bundle.js" ] } \ No newline at end of file diff --git a/gradio/frontend/index.html b/gradio/frontend/index.html index ce7a0172ee..42f88fc816 100644 --- a/gradio/frontend/index.html +++ b/gradio/frontend/index.html @@ -8,4 +8,4 @@ window.config = {{ config|tojson }}; } catch (e) { window.config = {}; - }Gradio
\ No newline at end of file + }Gradio
\ No newline at end of file diff --git a/gradio/inputs.py b/gradio/inputs.py index 4c2fdab9b7..b77ac3f9d5 100644 --- a/gradio/inputs.py +++ b/gradio/inputs.py @@ -1143,35 +1143,55 @@ class Dataframe(InputComponent): else: raise ValueError("Unknown type: " + str(self.type) + ". Please choose from: 'pandas', 'numpy', 'array'.") - # def set_interpret_parameters(self): - # """ - # Calculates interpretation score of each cell in the Dataframe by using a "leave one out" method to calculate the score of each cell by removing the cell and measuring the delta of the output value. - # """ - # return self - # def get_interpretation_neighbors(self, x): - # x = pd.DataFrame(x) - # leave_one_out_sets = [] - # shape = x.shape - # for i in range(shape[0]): - # for j in range(shape[1]): - # scalar = x.iloc[i, j] - # leave_one_out_df = x.copy() - # if is_bool_dtype(scalar): - # leave_one_out_df.iloc[i, j] = not scalar - # elif is_numeric_dtype(scalar): - # leave_one_out_df.iloc[i, j] = 0 - # elif is_string_dtype(scalar): - # leave_one_out_df.iloc[i, j] = "" - # leave_one_out_sets.append(leave_one_out_df.values.tolist()) - # return leave_one_out_sets, {"shape": x.shape} + def embed(self, x): + raise NotImplementedError("DataFrame doesn't currently support embeddings") + + def save_flagged(self, dir, label, data, encryption_key): + """ + Returns: (List[List[Union[str, float]]]) 2D array + """ + return json.dumps(data) + + def restore_flagged(self, data): + return json.loads(data) + + +class Timeseries(InputComponent): + """ + Component accepts pandas.DataFrame uploaded as a timeseries csv file. + Input type: pandas.DataFrame + """ + + def __init__(self, x=None, y=None, label=None): + """ + Parameters: + x (str): Column name of x (time) series. None if csv has no headers, in which case first column is x series. + y (Union[str, List[str]]): Column name of y series, or list of column names if multiple series. None if csv has no headers, in which case every column after first is a y series. + label (str): component name in interface. + """ + self.x = x + if isinstance(y, str): + y = [y] + self.y = y + super().__init__(label) + + def get_template_context(self): + return { + "x": self.x, + "y": self.y, + **super().get_template_context() + } + + @classmethod + def get_shortcut_implementations(cls): + return { + "timeseries": {}, + } + + def preprocess(self, x): + return pd.DataFrame(data=x["data"], columns=x["headers"]) - # def get_interpretation_scores(self, x, neighbors, scores, shape): - # """ - # Returns: - # (List[List[float]]): A 2D array where each value corrseponds to the interpretation score of each cell. - # """ - # return np.array(scores).reshape((shape)).tolist() def embed(self, x): raise NotImplementedError("DataFrame doesn't currently support embeddings")