numpy utility snippets

numpy utility snippets.py

def find_nearest(array, value):
    array = np.asarray(array)
    idx = (np.abs(array - value)).argmin()
    return idx,array[idx] #return in x,y format x is index, y is value


[print (i,v/1e9) for i,v in enumerate(x)] #print index and value of elements in list


def avg_dB(dB):
    """
    average in linear domain for dB data
    """
    lin=np.power(10,dB/10)
    return (10*np.log10(np.mean(lin)))

def drop_peak(x,y,nbins=1):
    """
    drops the nbinsx2 surrounding the peak of spectrum trace of x , y values 
    """
    idx_max_power=np.argmax(y)
    y=list(y[0:idx_max_power-nbins]) + list(y[idx_max_power+nbins:])
    x=list(x[0:idx_max_power-nbins]) +list(x[idx_max_power+nbins:])
    return (np.array(x),np.array(y))

#find closest yvalue point in xy trace in plotly fig
def xy_point (yval,fig,trace_index=0):
    """ return x,y values and index for point closest to yval
    """
    x=fig.data[trace_index].x
    y=fig.data[trace_index].y
    idx=np.where(y<yval)

    imax=y[idx].argmax() #highest y value < yval
    xv=x[imax];yv=y[imax]

    return (xv,yv,imax)

def xy_points (yval,x,y):
    """ returns list of indices where y is closest to yval and index of max y val by splitting into 2 regions around max point
    """ 
    #split into two ranges above , below max point and find y points < yval in both subsets
    max_y_index=find_nearest(y,np.max(y))[0]
    p1=xy_point(yval,x[0:max_y_index],y[0:max_y_index])
    p2=xy_point(yval,x[max_y_index:],y[max_y_index:])
    idx=[0]*2 #init with size 2
    idx[0]= p1[2]; idx[1]=p2[2]+max_y_index
    #idx1;idx2;x[idx1];y[idx1];x[idx2];y[idx2]
    return (idx,max_y_index)

def find_nearest(array, value):
    array = np.asarray(array) #in case input is a list
    idx = (np.abs(array - value)).argmin()
    return idx,array[idx] #return in x,y format x is index, y is value

def xy_annotate (fig2, trace_index=0, y_vals=[],text_in='',angle=0):
    """ annotates the closest point on the xy trace of plotly graph object fig2
    """
    #print ('text in', text_in)
    d=fig2.data[trace_index] # first trace
    for y_val in y_vals:
        x=d.x[find_nearest(d.y,y_val)[0]] #find index,val nearest to y_val
        y= find_nearest(d.y,y_val)[1]  #index 1 is y value, index 0 is array index
       # print ('xy',x,y)
       # print ('text ..', text_in)
        if text_in=='': #use x y coordinates as text if text is not specified
            text=f'{x:0.2G} {y:0.2f}'
        else:
            text=text_in
        #print ('text',text)
        fig2=fig2.add_annotation(x=x,y=y,text=text,visible=True)
        #xshift and yshift move the entire text and arrow units pixels
        fig2=fig2.update_annotations(font_size=10,textangle=angle,standoff=0,xshift=1,yshift=-1)
        # standoff
        # print ('xy',x,y)
    return (fig2)


def xy_point_plotly (yval,fig,trace_index=0):
    """ return x,y values and indices for point closest to yval
    """
    x=fig.data[trace_index].x
    y=fig.data[trace_index].y
    idx=np.where(y<yval)
    
    imax=y[idx].argmax() #highest y value < yval
    xv=x[imax];yv=y[imax]

    return (xv,yv,imax)

def xy_point (yval,x,y):
    idx=np.where(y<yval)

    imax=find_nearest(y,yval)[0]
   
   # print ("index",imax)
    xv=x[imax];yv=y[imax]
    return (xv,yv,imax)


def xy_points (yval,x,y):
    """ returns list of indices where y is closest to yval including index of max y val by splitting into 2 regions around max point
    """ 
    #split into two ranges above , below max point and find y points < yval in both subsets
    max_y_index=find_nearest(y,np.max(y))[0]
    p1=xy_point(yval,x[0:max_y_index],y[0:max_y_index])
    p2=xy_point(yval,x[max_y_index:],y[max_y_index:])
    idx=[0]*3 #init with size 2
    idx[0]= p1[2];idx[1]=max_y_index; idx[2]=p2[2]+max_y_index
    #idx1;idx2;x[idx1];y[idx1];x[idx2];y[idx2]
    return (idx)