Creating a contour-enhanced funnel plot in Python

Question

I want to create a Contour-Enhanced funnel plot (not a funnel chart),to test the small-study effect in meta-analysis like the following:

The above plot was created in R, which has several packages for doing this. However, I want to create it in Python, using matplotlib and pandas. How can I do this? I have tried Pythonmeta package and got this funnel plot

This is the source code of the package:

    def __init__(self,size=[6,6],dpi=80): #set figure
        self.size=size #inchs
        self.dpi=dpi   #default:80pts
        self.title="Meta-analysis Results "  
        self.nototal=False
        plt.rcParams['font.sans-serif']=['SimHei'] 
        plt.rcParams['axes.unicode_minus']=False
        logger.info("Load Fig().")
    def funnel (self,effs):
        myfig = Fig_Funnel (self.size,self.dpi,effs)
        return myfig```
    def Fig_Funnel (size,dpi,effs):
        myfig = plt.figure(linewidth=1,figsize=size,dpi=dpi)
        myfig.set_size_inches(size)
        x=[];y=[]
        for i in range(1,len(effs)):
            x.append(effs[i][1])
            y.append(effs[i][6])
        lbl,=plt.plot(x,y,"o", lw=1)

    
        ymax=max(y)+0.2
        plt.ylim(ymax,0)
        plt.plot([effs[0][1],effs[0][1]],[0,ymax],color="blue", linestyle="--",
        lw=1)
        plt.plot([effs[0][1],effs[0][1]-1.96*ymax],[0,ymax],color="blue",
        linestyle="--", lw=1)
        plt.plot([effs[0][1],effs[0][1]+1.96*ymax],[0,ymax],color="blue",
        linestyle="--", lw=1)
        ax = gca()
        ax.spines['right'].set_color('none')
        ax.spines['top'].set_color('none')
        ax.xaxis.set_ticks_position('bottom')
        ax.yaxis.set_ticks_position('left')

        plt.xlabel("Effect Size")
        plt.ylabel("Standard Error")
        myfig.tight_layout() 
        return myfig

Answer 1

Finally, I created it myself.:)

First of all, to understand the concept of a Contour-enhanced funnel plot, I recommend reading Jaime L Peters paper.

To create the plot, I used the following code

def CEfunnelplot(rults):      #to draw contour enhanced funnel plot

fig=plt.figure(figsize=(9,8))
ax=gca()
x=logES(rults)
y=SE(rults)      

plt.xlim(min(x)-5,max(x)+2)  #the xlim can change manually
plt.ylim(max(y)+0.1,0)
ax.set_facecolor(color="whitesmoke")
tes=(rults[0][1])
logtes=math.log(rults[0][1])


plt.plot ([0,(-2.58*max(y))],[0,max(y)], linestyle="None", lw=1)
plt.plot ([0,(2.58*max(y))],[0,max(y)], linestyle="None", lw=1)

trianglex = [ -2.58*max(y), 0, 2.58*max(y)] 
triangley = [ max(y),0, max(y)] 
for i in range(3):
    plt.plot(trianglex, triangley,color="lightgray")
plt.fill(trianglex, triangley,"lightgray")

plt.plot ([0,(-1.96*max(y))],[0,max(y)], linestyle="None", lw=1)
plt.plot ([0,(1.96*max(y))],[0,max(y)], linestyle="None", lw=1)

trianglex = [ -1.96*max(y), 0,1.96*max(y)] 
triangley = [ max(y),0, max(y)] 
for i in range(3):
    plt.plot(trianglex, triangley,color="darkgrey")
plt.fill(trianglex, triangley,"darkgrey")


plt.plot ([0,(-1.65*max(y))],[0,max(y)], linestyle="None", lw=1)
plt.plot ([0,(1.65*max(y))],[0,max(y)], linestyle="None", lw=1)

trianglex = [ -1.65*max(y), 0,1.65*max(y)] 
triangley = [ max(y),0, max(y)] 
for i in range(3):
    plt.plot(trianglex, triangley,color="white")
plt.fill(trianglex, triangley,"white")

plt.plot ([logtes,logtes],[0,max(y)],color="blue", linestyle="--", lw=1)
plt.plot ([logtes,logtes-1.96*max(y)],[0,max(y)],color="blue", linestyle="--", lw=1)
plt.plot ([logtes,logtes+1.96*max(y)],[0,max(y)],color="blue", linestyle="--", lw=1)
plt.plot(x,y,"o",lw=1,color="k")

ax = gca()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
colors = ['whitesmoke', 'lightgray', 'darkgrey',"white"]
lines =[Line2D([0], [0], color=c, linewidth=3, linestyle='solid') for c in colors]
labels = ["p < 1%","1%< p <5%","5%< p <10%","p > 10%"]
plt.legend(lines, labels,shadow=True)    

plt.xlabel("logRR",fontsize=14 )
plt.ylabel("Standard Error",fontsize=14,rotation=90 )
plt.savefig("Contour Enhanced Funnel plot.jpg")

I used This sample code for creating the legend and This code to color the plot. The result is as below:

If you like to change the marker of legend to "square", you can change the code as below

lines =[Line2D([0], [0],color=c,linewidth=3,linestyle='None',marker="s") for c in colors]

Answer 2

So, based on @Safoora 's solution I created a function which generates a simplified funnel plot similar to what we can obtain in R. The input parameter is a Pandas DataFrame with effect sizes and variability columns. It also allows to customize the plot. I have compared the result with that from R jamovi MAJOR module and it looks very similar. Feel free to make any necessary changes.

def funnel_plot(data, mid_value=0, es='g', var='SE', figsize=(9, 6),
                x_adj=(1.5, 1), y_adj=(0.01, -0.01), xlabel="Observed Outcome",
                ylabel="Standard Error", colors=['whitesmoke','lightgray','darkgrey',"white"], 
                gridcol='white', filename='funnel1', filetype='png',
                filedpi=100)->None:
    
    """Function to create a funnel plot for publication bias analysis.
       
       Parameters
       ----------
       data: DataFrame, required
           Includes columns with effect sizes and variability
           specified as column names in parameters 'es' and 'var'
       mid_value: float, optional
           This can be an estimate of the overall effect
       ... 
    """

    fig, ax = plt.subplots(figsize=figsize)

    # Prepare data
    x = data[es].to_numpy()
    y = np.round(data[var].to_numpy(), 3)
    mid = mid_value

    ax.set_xlim(np.min(x) - x_adj[0], np.max(x) + x_adj[1])
    ax.set_ylim(np.max(y) + y_adj[0], y_adj[1])
    ax.set_facecolor(color=colors[0])
    
    ax.grid(axis='y', zorder=0, color=gridcol)

    # Contours
    ax.plot ([mid,(-2.58 * np.max(y))+mid],[0, np.max(y)+mid], linestyle="none", lw=1)
    ax.plot ([mid,(2.58 * np.max(y))+mid],[0, np.max(y)+mid], linestyle="none", lw=1)

    trianglex = [ -2.58 * np.max(y)+mid, mid, 2.58 * np.max(y)+mid]
    triangley = [ np.max(y), 0, np.max(y)]
    for i in range(3):
        ax.plot(trianglex, triangley,color=colors[1], zorder=3)
    ax.fill(trianglex, triangley, colors[1], zorder=3)

    ax.plot ([mid,(-1.96 * np.max(y))+mid], [0, np.max(y)+mid], linestyle="None", lw=1)
    ax.plot ([mid,(1.96 * np.max(y))+mid], [0, np.max(y)+mid], linestyle="None", lw=1)

    trianglex = [ -1.96 * np.max(y)+mid, mid, 1.96 * np.max(y)+mid]
    triangley = [ np.max(y), 0, np.max(y)]
    for i in range(3):
        ax.plot(trianglex, triangley,color=colors[2], zorder=3)
    ax.fill(trianglex, triangley, colors[2], zorder=3)

    ax.plot ([0,(-1.65 * np.max(y))+mid],[0, np.max(y)+mid], linestyle="None", lw=1)
    ax.plot ([0,(1.65 * np.max(y))+mid],[0, np.max(y)+mid], linestyle="None", lw=1)

    trianglex = [ -1.65 * np.max(y)+mid, mid, 1.65 * np.max(y)+mid]
    triangley = [ np.max(y), 0, np.max(y)]
    for i in range(3):
        ax.plot(trianglex, triangley,color=colors[3], zorder=3)
    ax.fill(trianglex, triangley, colors[3], zorder=3)

    ax.axvline(x=mid, color='black', linestyle='dotted', linewidth=0.8, ymin=0, ymax=1, zorder=3)

    # Actual data plotting
    ax.scatter(x, y, marker="o", color="black", zorder=3)

    ax.spines[['top', 'right']].set_visible(False)
    ax.set_xlabel(xlabel, fontsize=12)
    ax.set_ylabel(ylabel, fontsize=12)
    plt.show()

    # Save image
    if filename and filetype:
        fig.savefig(f"{filename}.{filetype}", dpi=filedpi, format=filetype)
        print('Saving image file')

    return None

Then:

funnel_plot(df, mid_value=my_overall_effect)

and the result: enter image description here