from flask import Flask, render_template, request, redirect, url_for, flash import json import pandas as pd import numpy as np import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import matplotlib.font_manager as font_manager import re from sympy import symbols, sympify font_path = 'times_new_roman.ttf' times_new_roman = font_manager.FontProperties(fname=font_path, style='normal') """ fig = plot_data(x_data, y_data, std_dev_data, color_picker, title=plot_title, x_label=x_axis_label, y_label=y_axis_label, plot_background_color=plot_background_color, constant_line=constant_lines, enable_trendline=enable_trendline, trendline_color=color_picker_trendline) """ def plot_data(x_data, y_data, std_dev_data, color_picker, labels, df, title = "Plot", x_label = "X Axis", y_label = "Y Axis", plot_background_color="#ffffff", constant_line=[], enable_trendline=True, enable_grid=False, trendline_color="#000000", x_axis_scale="linear", y_axis_scale="linear", trendline_equation=None): fig, ax = plt.subplots(dpi=300) plots = [] for idx, _ in enumerate(x_data): x = df[x_data[idx]].astype(float) y = df[y_data[idx]].astype(float) color = color_picker[idx] data_series_title = labels[idx] if (std_dev_data[idx] != None): plot = ax.errorbar(x, y, yerr=df[std_dev_data[idx]].astype(float), fmt='o', ecolor='black', capsize=5, color=color, label=data_series_title) else: plot = ax.plot(x, y, 'o', color=color, label=data_series_title) if (type(plot) == list): plots.extend(plot) else: plots.append(plot) handles = plots if enable_trendline: if trendline_equation != None: try: x = symbols('x') p = sympify(trendline_equation) x_range = np.linspace(df[x_data[0]].astype(float).min(), df[x_data[0]].astype(float).max(), 100) y_range = [p.subs(x, i) for i in x_range] h, = ax.plot(x_range, y_range, linestyle="dashed", label="Trendline", color=trendline_color) handles.append(h) print("Valid Equation", p) except ValueError: print("Invalid Equation") else: x = df[x_data[0]].astype(float) y = df[y_data[0]].astype(float) z = np.polyfit(x, y, 2) p = np.poly1d(z) h, = ax.plot(x,p(x), linestyle="dashed", label="Trendline", color=trendline_color) handles.append(h) light_grey = 0.9 dar_grey = 0.4 for idx, line in enumerate(constant_line): val, name = line idx += 1 grey_shade = light_grey - (light_grey - dar_grey) * (idx / len(constant_line)) color = (grey_shade, grey_shade, grey_shade) h = ax.axhline(y=val, linestyle='--', color=color, label=name) handles.append(h) ax.grid(True,linestyle=(0,(1,5))) # enable_grid) ax.set_facecolor(plot_background_color) ax.set_xlabel(x_label, fontproperties=times_new_roman) ax.set_ylabel(y_label, fontproperties=times_new_roman) title = title.replace(' in ', '\nin ') ax.set_title(title, wrap=True, fontproperties=times_new_roman) for label in (ax.get_xticklabels() + ax.get_yticklabels()): label.set_fontproperties(times_new_roman) print(handles) print(handles[0]) print(handles[0].get_label()) labels = [h.get_label() for h in handles] ax.legend(handles, labels, loc='best', prop=times_new_roman) fig.patch.set_facecolor(plot_background_color) fig.tight_layout(pad=3.0) #ax.invert_xaxis() ax.set_xscale(x_axis_scale) ax.set_yscale(y_axis_scale) return fig app = Flask(__name__) def create_df_from_textarea(textarea): rows = textarea.split('\n') data = [row.split("\t") for row in rows] df = pd.DataFrame(data[1:], columns=data[0]) return df @app.route('/') def index(): return render_template('index.html') # POST for process_data @app.route('/process_data', methods=['POST']) def process_data(): print(request.form) textarea = request.form['excelData'] df = create_df_from_textarea(textarea) print(df) data_keys = f"{request.form.keys()}" xPattern = r'xColumn-\d+' yPattern = r'yColumn-\d+' stdDevPattern = r'stdDevColumn-\d+' colorPickerPattern = r'colorPicker-\d+' labelPattern = r'dataSeries-\d+' constantLinePattern = r'constantLine\d+' constantLineLabelPattern = r'constantLineLabel\d+' # match in data_keys string x_data_matches = re.findall(xPattern, data_keys) y_data_matches = re.findall(yPattern, data_keys) std_dev_data_matches = re.findall(stdDevPattern, data_keys) color_picker_matches = re.findall(colorPickerPattern, data_keys) label_matches = re.findall(labelPattern, data_keys) constant_line_matches = re.findall(constantLinePattern, data_keys) constant_line_label_matches = re.findall(constantLineLabelPattern, data_keys) x_data = [] for x in x_data_matches: val = request.form.get(x) if val != '': x_data.append(df.columns[int(val)]) else: x_data.append(None) y_data = [] for y in y_data_matches: val = request.form.get(y) if val != '': y_data.append(df.columns[int(val)]) else: y_data.append(None) std_dev_data = [] for std_dev in std_dev_data_matches: val = request.form.get(std_dev) if val != '': std_dev_data.append(df.columns[int(val)]) else: std_dev_data.append(None) color_picker = [] for color in color_picker_matches: val = request.form.get(color) if val != '': color_picker.append(val) else: color_picker.append(None) data_series_label = [] for label in label_matches: val = request.form.get(label) if val != '': data_series_label.append(val) else: data_series_label.append("Data") constant_lines = [] for idx, val in enumerate(constant_line_matches): val = request.form.get(val) if val != '': label = request.form.get(constant_line_label_matches[idx]) or "Constant Line" val = float(val) constant_lines.append((val, label)) x_axis_label = request.form.get('xTitle', 'X Axis') y_axis_label = request.form.get('yTitle', 'Y Axis') plot_title = request.form.get('plotTitle', 'Plot Title') plot_background_color = request.form.get('colorPickerPlotBackground', '#ffffff') color_picker_trendline = request.form.get('colorPickerTrendline', '#00ff00') x_axis_scale = request.form.get('xAxisScale', 'linear') y_axis_scale = request.form.get('yAxisScale', 'linear') calc_trendline = request.form.get('calcTrendline', 'off') if calc_trendline == 'on': enable_trendline = True else: enable_trendline = False trendline_equation = request.form.get('trendlineEquation', None) if trendline_equation == "": trendline_equation = None fig = plot_data(x_data, y_data, std_dev_data, color_picker, data_series_label, df, title=plot_title, x_label=x_axis_label, y_label=y_axis_label, plot_background_color=plot_background_color, constant_line=constant_lines, enable_trendline=enable_trendline, trendline_color=color_picker_trendline, x_axis_scale=x_axis_scale, y_axis_scale=y_axis_scale, trendline_equation=trendline_equation) # Return plot as image from io import BytesIO import base64 buffer = BytesIO() fig.savefig(buffer, format='png') buffer.seek(0) image_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8').replace('\n', '') # Embed base64 image in HTML return ''.format(image_base64) if __name__ == '__main__': app.run(port=8080,debug=True)