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from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import StreamingResponse
from io import BytesIO
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import numpy as np
import pandas as pd
from pydantic import BaseModel, Field
from sympy import symbols, sympify
font_path = 'times_new_roman.ttf'
times_new_roman = font_manager.FontProperties(fname=font_path, style='normal')
class PlotDataRequest(BaseModel):
x_data: list[float] = Field(..., title="X Data", description="Data Series for the X axis")
y_data: list[float] = Field(..., title="Y Data", description="Data Series for the Y axis")
std_dev_data: list[float] = Field([], title="Error Bars Data", description="Data Series for calculating error bars")
label: list[str] = Field("Dataseries", title="Label", description="Label for the data series")
color_picker: list[str] = Field(["#000000"], title="Color Picker", description="List of colors to use for the data series")
x_label: str = Field("X Axis", title="X Axis Label", description="Label for the X axis")
y_label: str = Field("Y Axis", title="Y Axis Label", description="Label for the Y axis")
title: str = Field("Plot", title="Title", description="Title of the plot")
enable_trendline: bool = Field(True, title="Enable Trendline", description="Enable trendline")
enable_grid: bool = Field(False, title="Enable Grid", description="Enable grid")
x_axis_scale: str = Field("linear", title="X Axis Scale", description="Scale of the X axis")
y_axis_scale: str = Field("linear", title="Y Axis Scale", description="Scale of the Y axis")
trendline_equation: str = Field(None, title="Trendline Equation", description="Manually specify the equation for the trendline")
constant_line_vals: list[float] = Field([], title="Constant Line Values", description="List of values for the constant line")
constant_line_name: list[str] = Field([], title="Constant Line Names", description="List of names for the constant line")
app = FastAPI()
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="dotted", label="Trendline", color=trendline_color)
handles.append(h)
except:
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="dotted", 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='dashed', dashes=(idx,2) , 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.post("/post")
async def create_plot(request: PlotDataRequest, data: Request):
print(data)
if len(request.x_data) != len(request.y_data):
raise HTTPException(status_code=400, detail="X and Y data must be the same length")
if len(request.constant_line_vals) != len(request.constant_line_name):
raise HTTPException(status_code=400, detail="Constant line values and names must be the same length")
constant_line = list(zip(request.constant_line_vals, request.constant_line_name))
# Create DF from request.x_data and request.y_data -> assign column header as x_data and y_data
df = pd.DataFrame(list(zip(request.x_data, request.y_data)), columns=["X", "Y"])
# if request.std_dev_data exists, add to df
if len(request.std_dev_data) > 0:
df["STD_DEV"] = request.std_dev_data
x_data = ["X"]
y_data = ["Y"]
if len(request.std_dev_data) > 0:
std_dev_data = ["STD_DEV"]
else:
std_dev_data = [None]
labels = request.label
fig = plot_data(x_data, y_data, std_dev_data, request.color_picker, labels, df,
title=request.title, x_label=request.x_label, y_label=request.y_label,
enable_trendline=request.enable_trendline, enable_grid=request.enable_grid,
constant_line=constant_line,
x_axis_scale=request.x_axis_scale, y_axis_scale=request.y_axis_scale, trendline_equation=request.trendline_equation)
buf = BytesIO()
fig.savefig(buf, format="png")
buf.seek(0)
return StreamingResponse(buf, media_type="image/png")
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