python old_gaze_plotting_functions AM

Posted 2021-05-08

def gaze_plot(df_list):

    middle = 2048/2.0
    quarter = (1304-744)/4.0

    fig = plt.figure()
    ax1 = fig.add_subplot(111, aspect='equal')

    for x in df_list:
        if x['Cued Side'].all()=='>' and x['Cued Category'].all()=='Place':
            color='green'
        elif x['Cued Side'].all()=='>' and x['Cued Category'].all()=='Face':
            color='blue'
        elif x['Cued Side'].all()=='<' and x['Cued Category'].all()=='Place':
            color='orange'
        else:
            color='red'

        x['Color']=color

        ax1.plot(x['av_x_coord'], x['av_y_coord'], '.', color=color)
        #props.append(x.loc[(x['av_x_coord']>middle-quarter) & (x['av_x_coord']<middle+quarter)])

    rect1 = patches.Rectangle(((59.8/2.0)-8-3.5,(33.6/2)-3.5),7,7,linewidth=1,edgecolor='black',facecolor='none')
    rect2 = patches.Rectangle(((59.8/2.0)+8-3.5,(33.6/2)-3.5),7,7,linewidth=1,edgecolor='black',facecolor='none')

    # Add the patch to the Axes
    ax1.add_patch(rect1)
    ax1.add_patch(rect2)

    # plt.legend(loc='upper left');
    plt.ylim(0, 33.6)
    plt.xlim(0, 59.8)
    plt.show()

    return(fig)



def gaze_box(trial, center, dims):
    '''
    inputs:  center - tuple indicating center of ROI (x,y)
             dims - tuple indicating dimensions of rectangle (width, height)
             trial - dataframe for single presentation trial (or block)

    outputs: box_num - raw number of gazepoints within box (int)
             proportion - proportion of this trial's gaze points within box (float)
             df - dataframe of all gazepoints within the box, including timestamps
    '''

    total_num = trial.shape[0]

    trial = trial[(trial['av_y_coord']>=(center[1]-dims[1]/2))&
                  (trial['av_y_coord']<=(center[1]+dims[1]/2))&
                  (trial['av_x_coord']>=(center[0]-dims[0]/2))&
                  (trial['av_x_coord']<=(center[0]+dims[0]/2))]

    df = trial

    if total_num>0:
        box_num = trial.shape[0]
        proportion = box_num/total_num
    else:
        box_num = np.nan
        proportion = np.nan

    return(box_num, proportion, df)