As I mentioned in my previous experiment, it has been a busy and difficult semester for me for family reasons. Accordingly, I am two and a half months behind schedule delivering my 12th and final experiment for this grant cycle. Additionally, I feel like my work for the past few months on this process has been a bit underwhelming, but unfortunately this work what my current bandwidth allows for. I hope to make up for it in the next year or so.
Anyway, the experiment for this month is similar to the one done for experiment 11. However, in this experiment I am generate vector images that reference maps of Boston’s subway system (the MBTA). Due to the complexity of the MBTA system I’ve created four different algorithms, reducing the visual data at any time to one quadrant of the map, thus, the individual programs are called: MBTA NW, MBTA NE, MBTA SE, & MBTA SW.
Since all four algorithms are basically the same, I’ll use MBTA – NE as an example. For each example Knob 5 was used for the background color. There were far more attributes I wanted to control than knobs I had at my disposal, so I decided to link them together. Thus, for MBTA – NE knob 1 controls red line attributes, knob 2 controls the blue and orange line attributes, knob 3 controls the green line attributes, and knob 4 controls the silver line attributes. Each of the four programs assigns the knobs to different combinations of colored lines based upon the complexity of the MBTA map in that quadrant.
The attributes that knobs 1-4 control include: line width, scale (amount of wiggle), color, and number of superimposed lines. The line width ranges from one to ten pixels, and is inversely proportional to the number of superimposed lines which ranges from on to eight. Thus, the more lines there are, the thinner they are. The scale, or amount of wiggle is proportional to the line width, that is the thicker the lines, the more they can wiggle. Finally, color is defined using RGB numbers. In each case, only one value (the red, the green, or the blue) changes with the knob values. The amount of change is a twenty point range centered around the optimal value. We can see this implemented below in the initialization portion of the program.
RElinewidth = int (1+(etc.knob1)*10)
BOlinewidth = int (1+(etc.knob2)*10)
GRlinewidth = int (1+(etc.knob3)*10)
SIlinewidth = int (1+(etc.knob4)*10)
etc.color_picker_bg(etc.knob5)
REscale=(55-(50*(etc.knob1)))
BOscale=(55-(50*(etc.knob2)))
GRscale=(55-(50*(etc.knob3)))
SIscale=(55-(50*(etc.knob4)))
thered=int (89+(10*(etc.knob1)))
redcolor=pygame.Color(thered,0,0)
theorange=int (40+(20*(etc.knob2)))
orangecolor=pygame.Color(99,theorange,0)
theblue=int (80+(20*(etc.knob2)))
bluecolor=pygame.Color(0,0,theblue)
thegreen=int (79+(20*(etc.knob3)))
greencolor=pygame.Color(0,thegreen,0)
thesilver=int (46+(20*(etc.knob4)))
silvercolor=pygame.Color(50,53,thesilver)
j=int (9-(1+(7*etc.knob1)))
The value j stands for the number of superimposed lines. This then transitions into the first of four loops, one for each of the groups of lines. Below we see the code for red line portion of program. The other three loops are fairly much the same, but are much longer due to the complexity of the MBTA map. An X and a Y coordinate are set inside this loop for every point that will be used. REscale is multiplied by a value from etc.audio_inwhich is divided by 33000 in order to change that audio level into a decimal ranging from 0 to 1 (more or less). This scales the value of REscale down to a smaller value, which is added to the numeric value. It is worth noting that because audio values can be negative, the numeric value is at the center of potential outcomes. Scaling the index number of etc.audio_in by (i*11), (i*11)+1, (i*11)+2, & (i*11)+3 lends a suitable variety of wiggles for each instance of a line.
j=int (9-(1+(7*etc.knob1)))
for i in range(j):
AX=int (320+(REscale*(etc.audio_in[(i*11)]/33000)))
AY=int (160+(REscale*(etc.audio_in[(i*11)+1]/33000)))
BX=int (860+(REscale*(etc.audio_in[(i*11)+2]/33000)))
BY=int (720+(REscale*(etc.audio_in[(i*11)+3]/33000)))
pygame.draw.line(screen, redcolor, (AX,AY), (BX, BY), RElinewidth)
I arbitrarily limited each program to 26 points (one for each letter of the alphabet). This really causes the vector graphic to be an abstraction of the MBTA map. The silver line in particular gets quite complicated, so I’m never really able to fully represent it. That being said, I think that anyone familiar with Boston’s subway system would recognize it if the similarity was pointed out to them. I also imagine any daily commuter on the MBTA would probably recognize the patterns in fairly short order. However, in watching my own video, which uses music generated by a PureData algorithm that will be used to write a track for my next album, I noticed that the green line in the MBTA – NE and MBTA – SW needs some correction.
The EYESY has been fully incorporated into my live performance routine as Darth Presley. You can see below a performance at the FriYay series at the New Bedford Art Museum. You’ll note that the projection is the Random Lines algorithm that I wrote. Likewise graduating senior Edison Roberts used the EYESY for his capstone performance as the band Geepers! You’ll see a photo of him below with a projection using the Random Concentric Circles algorithm that I wrote. I definitely have more ideas of how to use the EYESY in live performance. In fact, others have started to use ChatGPT to create EYESY algorithms.
Ultimately my work on this grant project has been fruitful. To date the algorithms I’ve written for the Organelle and EYESY have been circulated pretty well on Patchstorage.com (clearly the Organelle is the more popular format of the two) . . .
February was a very busy month for me for family reasons, and it’ll likely be that way for a few months. Accordingly, I’m a bit late on my February experiment, and will likely be equally late with my final experiment as well. I have also stuck with programming for the EYESY, as I have kind of been on a roll in terms of coming up with ideas for it.
This month I created twelve programs for the EYESY, each of which displays a different constellation from the zodiac. I’ve named the series Constellations and have uploaded them to patchstorage. Each one works in exactly the same manner, so we’ll only look at the simplest one, Aries. The more complicated programs simply have more points and lines in them with different coordinates and configurations, but are otherwise are identical.
Honestly, one of the most surprising challenges of this experiment way trying to figure out if there’s any consensus for a given constellation. Many of the constellations are fairly standardized, however others are fairly contested in terms of which stars are a part of the constellation. When there were variants to choose from I looked for consensus, but at times also took aesthetics into account. In particular I valued a balance between something that would look enticing and a reasonable number of points.
I printed images of each of the constellations, and traced them onto graph paper using a light box. I then wrote out the coordinates for each point, and then scaled them to fit in a 1280×720 resolution screen, offsetting the coordinates such that the image would be centered. These coordinates then formed the basis of the program.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
linewidth = int (1+(etc.knob4)*10)
etc.color_picker_bg(etc.knob5)
offset=(280*etc.knob1)-140
scale=5+(140*(etc.knob3))
r = int (abs (100 * (etc.audio_in[0]/33000)))
g = int (abs (100 * (etc.audio_in[1]/33000)))
b = int (abs (100 * (etc.audio_in[2]/33000)))
if r>50:
rscale=-5
else:
rscale=5
if g>50:
gscale=-5
else:
gscale=5
if b>50:
bscale=-5
else:
bscale=5
j=int (1+(8*etc.knob2))
for i in range(j):
AX=int (offset+45+(scale*(etc.audio_in[(i*8)]/33000)))
AY=int (offset+45+(scale*(etc.audio_in[(i*8)+1]/33000)))
BX=int (offset+885+(scale*(etc.audio_in[(i*8)+2]/33000)))
BY=int (offset+325+(scale*(etc.audio_in[(i*8)+3]/33000)))
CX=int (offset+1165+(scale*(etc.audio_in[(i*8)+4]/33000)))
CY=int (offset+535+(scale*(etc.audio_in[(i*8)+5]/33000)))
DX=int (offset+1235+(scale*(etc.audio_in[(i*8)+6]/33000)))
DY=int (offset+675+(scale*(etc.audio_in[(i*8)+7]/33000)))
r = r+rscale
g = g+gscale
b = b+bscale
thecolor=pygame.Color(r,g,b)
pygame.draw.line(screen, thecolor, (AX,AY), (BX, BY), linewidth)
pygame.draw.line(screen, thecolor, (BX,BY), (CX, CY), linewidth)
pygame.draw.line(screen, thecolor, (CX,CY), (DX, DY), linewidth)
In these programs knob 1 is used to offset the image. Since only one offset is used, rotating the knob moves the image on a diagonal moving from upper left to lower right. The second knob is used to control the number of superimposed versions of the given constellation. The scale of how much the image can vary is controlled by knob 3. Knob 4 controls the line width, and the final knob controls the background color.
The new element in terms of programing is a for statement. Namely, I use for i in range (j) to create several superimposed versions of the same constellation. As previously stated, the amount of these is controlled by knob 2, using the code j=int (1+(8*etc.knob2)). This allows for anywhere from 1 to 8 superimposed images.
Inside this loop, each point is offset and scaled in relationship to audio data. We can see for any given point the value is added to the offset. Then the scale value is multiplied by data from etc.audio_in. Using different values within this array allows for each point in the constellation to react differently. Using the variable i within the array also allows for differences between the points in each of the superimposed versions. The variable scale is always set to be at least 5, allowing for some amount of wiggle given all circumstances.
Originally I had used data from etc.audio_in inside the loop to set the color of the lines. This resulted in drastically different colors for each of the superimposed constellations in a given frame. I decided to tone this down a bit, by using etc.audio_in data before the loop started allowing each version of the constellation within a given frame to be largely the same color. That being said, to create some visual interest, I use rscale, gscale, and bscale to move the color in a direction for each superimposed version. Since the maximum amount of superimposed images is 8, I used the value 5 to increment the red, green, and blue values of the color. When the original red, green, or blue value was less than 50 I used 5, which moves the value up in value. When the original red, green, or blue value was more than 50 I used -5, which moves the value down in value. The program chooses between 5 and -5 using if :else statements.
The music used in the example videos are algorithms that will be used to generate accompaniment for a third of my next major studio album. These algorithms grew directly out of my work on these experiments. I did add one little bit of code the these puredata algorithms however. Since I have 6 musical examples, but 12 EYESY patches, I added a bit of code that randomly chooses between 1 of 2 EYESY patches and sends out a program (patch) change to the EYESY on MIDI channel 16 at the beginning of each phrase.
While I may not use these algorithms for the videos for the next studio album, I will likely use them in live performances. I plan on doing a related set of EYESY programs for my final experiment next month.
I kind of hit a wall of the Organelle. I feel like in order to advance my skills I have a bit of a hurdle between where my programming skills are at, and where they would need to be to do something more advanced that the recent experiments I have completed. Accordingly for this month I decided to shift my focus to the EYESY. Last month I made significant progress in understanding Python programming for the EYESY, and that allowed me to come up with five ideas for algorithms in short order. The music for all five mini-experiments comes from PureData algorithms I will be using for my next major album. All five of these algorithms are somewhat derived from my work on my last album.
The two realizations that allowed me to make significant progress on EYESY programming is that Python is super picky about spaces, tabs, and indentations, and that while the EYESY usually gives little to no feedback when a program has an error in it, you can use an online Python compiler to help figure out where your error is (I had mentioned the latter in last month’s experiment). Individuals who have a decent amount of programming experience may scoff at the simplicity of the programs that follow, but for me it is a decent starting place, and it is also satisfying to me to see how such simple algorithms can generate such gratifying results.
Random Lines is a patch I wrote that draws 96 lines. In order to do this in an automated fashion, I have to use a loop, in this case I use for i in range(96):. The five lines that follow are all executed in this loop. Before the loop commences, we choose the color using knob 4 and the background color using knob 5. I use knob 3 to set the line width, but I scale it by multiplying the knob’s value, which will be between 0 and 1, by 10, and adding 1, as line widths cannot have a value of 0. I also have to cast the value as an integer. I set an x offset value using knob 1. Multiplying by 640 and then subtracting 320 will yield a result between -320 and 320. Likewise, a y offset value is set using knob 2, and the scaling results in a value between -180 and 180.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
color = etc.color_picker(etc.knob4)
linewidth = int (1+ (etc.knob3)*10)
etc.color_picker_bg(etc.knob5)
xoffset=(640*etc.knob1)-320
yoffset=(360*etc.knob2)-180
for i in range(96):
x1 = int (640 + (xoffset+(etc.audio_in[i])/50))
y1 = int (360 + (yoffset+(etc.audio_in[(i+1)])/90))
x2 = int (640 + (xoffset+(etc.audio_in[(i+2)])/50))
y2 = int (360 + (yoffset+(etc.audio_in[(i+3)])/90))
pygame.draw.line(screen, color, (x1,y1), (x2, y2), linewidth)
Within the loop, I set two coordinates. The EYESY keeps track of the last hundred samples using etc.audio_in[]. Since these values use sixteen bit sound, and sound has peaks (represented by positive numbers) and valleys (represented by negative numbers), these values range between -32,768 and 32,787. I scale these values by dividing by 50 for x coordinates. This will scale the values to somewhere between -655 and 655. For y coordinates I divide by 90, which yields values between -364 and 364.
In both cases, I add these values to the corresponding offset value, and add the value that would normally, without the offsets, place the point in the middle of the screen, namely 640 (X) and 360 (Y). A negative value for the xoffset or the scaled etc.audio_in value would move that point to the left, while a positive value would move it to the right. Likewise, a negative value for the yoffset or the scale etc.audio_in value would move the point up, while a positive value would move it down.
Since subsequent index numbers are used for each coordinate (that is i, i+1, i+2, and i+3), this results in a bunch of interconnected lines. For instance when i=0, the end point of the drawn line (X2, Y2) would become the starting point when i=2. Thus, the lines are not fully random, as they are all interconnected, yielding a tangled mass of lines.
Random Concentric Circles uses a similar methodology. Again, knob five is use to control the background color, while knobs 1 and 2 are again scaled to provide an X and Y offset. The line width is shifted to knob 4. For this algorithm the loop happens 94 times. The X and Y value for the center of the circles is determined the same way as was done in Random Lines. However, we now need a radius and we need a color for each circle.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
linewidth = int (1+(etc.knob4)*9)
etc.color_picker_bg(etc.knob5)
xoffset=(640*etc.knob1)-320
yoffset=(360*etc.knob2)-180
for i in range(94):
x = int (640 + xoffset+(etc.audio_in[i])/50)
y = int (360 + yoffset+(etc.audio_in[(i+1)])/90)
radius = int (11+(abs (etc.knob3 * (etc.audio_in[(i+2)])/90)))
r = int (abs (100 * (etc.audio_in[(i+3)]/33000)))
g = int (abs (100 * (etc.audio_in[(i+4)]/33000)))
b = int (abs (100 * (etc.audio_in[(i+5)]/33000)))
thecolor=pygame.Color(r,g,b)
pygame.draw.circle(screen, thecolor, (x,y), radius, linewidth)
We have knob 3 available to help control the radius of the circle. Here I multiply knob 3 by a scaled version of etc.audio_in[(i+2)]. I scale it by dividing by 90 so that the largest possible circle will mostly fit on the screen if it is centered in the screen. Notice that when we multiply knob 3 by etc.audio_in, there’s a 50% chance that the result will be a negative number. Negative values for radii don’t make any sense, so I take the absolute value of this outcome using abs. I also add this value to 11, as a radius of 0 makes no sense, and a radius of less than 10, as having a line width that is larger than the radius will cause an error.
For this algorithm I take a set forward by giving each circle its own color. In order to do this I have to set the value for red, green, and blue separately, and then combine them together using pygame.Color(). For each of the three values (red, green, and blue) I divide a value of etc. audio_in by 33000, which will yield a value between 0 and 1 (more or less), and then multiply this by 100. I could have done the same thing by simply dividing etc.audio_in by 330, however, at the time this process made the most sense to me. Again, this process could result in a negative number and / or a fractional value, so I cast the result as an integer after getting its absolute value.
Colored Rectangles has a different structure than the previous two examples. Rather than have all the objects cluster around a center point I wanted to create an algorithm that spaces all of the objects out evenly throughout the screen in a grid like pattern. I do this using an eight by eight grid of 64 rectangles. I accomplish the spacing using modulus mathematics as well as integer division. The X value is obtained by multiplying 160 times i%8. In a similar vein, the Y values is set to 90 times i//8. Integer division in Python is accomplished through the use of two slashes. Using this operator will return the integer value of a division problem, omitting the fractional portion. Both the X and the Y values have an additional offset value. The X is offset by (i//8)*(80*etc.knob1), so this offset increases as knob 1 is turned up, with a maximum offset of 80 pixels per row. The value i//8 essentially multiplies that offset by the row number. That is the rows shift further towards the right.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
etc.color_picker_bg(etc.knob5)
for i in range(64):
x=(i%8)*160+(i//8)*(80*etc.knob1)
y=(i//8)*90+(i%8)*(45*etc.knob2)
thewidth=int (abs (160 * (etc.knob3) * (etc.audio_in[(i)]/33000)))
theheight=int (abs (90 * (etc.knob4) * (etc.audio_in[(i+1)]/33000)))
therectangle=pygame.Rect(x,y,thewidth,theheight)
r = int (abs (100 * (etc.audio_in[(i+2)]/33000)))
g = int (abs (100 * (etc.audio_in[(i+3)]/33000)))
b = int (abs (100 * (etc.audio_in[(i+4)]/33000)))
thecolor=pygame.Color(r,g,b)
pygame.draw.rect(screen, thecolor, therectangle, 0)
Likewise, the Y offset is determined by (i%8)*(45*etc.knob2). As the value of knob 2 increases, the offset moves towards a maximum value of 45. However, as the columns shift to the right, those offsets compound due to the fact that they are multiplied by (i%8).
A rectangle can be defined in pygame by passing an X value, a Y value, width, and height to pygame.Rect. Thus, the next step is to set the width and height of the rectangle. In both cases, I set the maximum value to 160 (for width) and 90 (for height). However, I scaled them both by multiplying by a knob value (knob 3 for width and knob 4 for height). These values are also scaled by an audio value divided by 33,000. Since negative values are possible from audio values, and negative widths and heights don’t make much sense, I took the absolute value of each. If I were to rewrite this algorithm (perhaps I will), I would set a minimum value for width and height such that widths and heights of 0 were not possible.
I set the color of each rectangle using the same method as I did in Random Concentric Circles. In order to draw the rectangle you pass the screen, the color, the rectangle (as defined by pygame.Rect), as well as the line width to pygame.draw.rect. Using a line width of 0 means that the rectangle will be filled in with color.
Random Rectangles is a combination of Colored Rectangles and Random Lines. Rather than use pygame’s Rect object to draw rectangles on the screen, I use individual lines to draw the rectangles (technically speaking they are quadrilaterals). Knob 4 is used here to set the foreground color, knob 5 is used here to set the background color, knob 3 is used to set the linewidth.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
color = etc.color_picker(etc.knob4)
etc.color_picker_bg(etc.knob5)
linewidth = int (1+ (etc.knob3)*10)
for i in range(64):
x=(i%8)*160+(i//8)*(80*etc.knob1)+(40*(etc.audio_in[(i)]/33000))
y=(i//8)*90+(i%8)*(45*etc.knob2)+(20*(etc.audio_in[(i+1)]/33000))
x1=x+160+(40*(etc.audio_in[(i+2)]/33000))
y1=y+(20*(etc.audio_in[(i+3)]/33000))
x2=x1+(40*(etc.audio_in[(i+4)]/33000))
y2=y1+90+(20*(etc.audio_in[(i+5)]/33000))
x3=x+(40*(etc.audio_in[(i+6)]/33000))
y3=y+90+(20*(etc.audio_in[(i+7)]/33000))
pygame.draw.line(screen, color, (x,y), (x1, y1), linewidth)
pygame.draw.line(screen, color, (x1,y1), (x2, y2), linewidth)
pygame.draw.line(screen, color, (x2,y2), (x3, y3), linewidth)
pygame.draw.line(screen, color, (x3,y3), (x, y), linewidth)
Within the loop, I use a similar method of setting the initial X and Y coordinates. That being said, I separate out the use of knobs and the use of audio input. In the case of the X coordinated, I use (i//8)*(80*etc.knob1) to control the amount of x offset for each row, with a maximum offset of 80. The audio input then offsets this value further using (40*etc.audio_in[(i+2)]/33000). This moves the x value by a value of plus or minus 40 (remember that audio values can be negative. Likewise, knob 2 offsets the Y value for every row by a maximum of 45, and the audio input further offsets this value by plus or minus 20.
Since it takes four points to define a quadrilateral, we need three more points, which we will call (x1, y1), (x2, y2), and (x3, y3). These are all interrelated. The value of X is used to define X1 and X3, while X2 is based off of X1. Likewise, the value of Y helps define Y1 and Y3, with Y2 being based off of Y1. In the case X1 and X2 (which is based on X1) we add 160 to X, giving a default width, but these values are again scaled by etc.audio_in. Similarly, we add 90 to Y1 and Y3 to determine a default height of the quadrilaterals, but again, all points are further offset by etc.audio_in, resulting in quadrilaterals, rather than rectangles with parallel sides. If I were to revise this algorithm I would likely make each quadrilateral a different color.
Frankly, I was not as pleased with the results of Colored Rectangles and Random Rectangles, so I decided to go back create an algorithm that was an amalgam of Random Lines and Random Concentric Circles, namely Random Radii. This program creates 95 lines, all of which have the same starting point, but different end points. Knob 5 sets the background color, while knob 4 sets the line width.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
linewidth = int (1+ (etc.knob4)*10)
etc.color_picker_bg(etc.knob5)
xoffset=(640*etc.knob1)-320
yoffset=(360*etc.knob2)-180
X=int (640+xoffset)
Y=int (360+yoffset)
for i in range(95):
r = int (abs (100 * (etc.audio_in[(i+2)]/33000)))
g = int (abs (100 * (etc.audio_in[(i+3)]/33000)))
b = int (abs (100 * (etc.audio_in[(i+4)]/33000)))
thecolor=pygame.Color(r,g,b)
x2 = int (640 + (xoffset+etc.knob3*(etc.audio_in[(i)])/50))
y2 = int (360 + (yoffset+etc.knob3*(etc.audio_in[(i+1)])/90))
pygame.draw.line(screen, thecolor, (X,Y), (x2, y2), linewidth)
Knob 1 & 2 are used for X and Y offsets (respectively) of the center point. Using (640*etc.knob1)-320 means that the X value will move plus or minus 320. Similarly, (360*etc.knob2)-180 permits the Y value to move up or down by 180. As is the case with Random Concentric Circles, the color of each line is defined by etc.audio_in. Knob 3 is used to scale the end point of each line. In the case of both the X and Y values, we start from the center of the screen (640, 360) add the offset defined by knobs 1 or 2, and then use knob 3 to scale a value derived from etc.audio_in. Since audio values can be positive or negative, these radii shoot outward from the offset center point in all directions.
As suggested earlier, I am very gratified with these results. Despite the simplicity of the Python code, the results are mostly dynamic and compelling (although I am somewhat less than thrilled with Colored Rectangles and Random Rectangles). The user community for the EYESY is much smaller than that of the Organelle. The EYESY user’s forum has only 13% the activity of that of the Organelle. I seem to have inherited being the administrator of the ETC / EYESY Video Synthesizer from Critter&Guitari group on Facebook. Likewise, I am the author of the seven most recent patches for the EYESY on patchstorage. Thus, this month’s experiment sees me shooting to the top to become the EYESY’s most active developer. The start of the semester has been very busy for me. I am somewhat doubting that I will be coming up with an Organelle patch next month, but I equally suspect that I will continue to develop more algorithms of the EYESY.
This month’s experiment is a considerable step forward on three fronts: Organelle programming, EYESY programming, and computer assisted composition. In terms of Organelle programming, rather than taking a pre-existing algorithm and altering it (or hacking it) to do something different, I decided to create a patch from scratch. I first created it in PureData, and then reprogrammed it to work specifically with the Organelle. Creating it in PureData first meant that I used horizontal sliders to represent the knobs, and that I sent the output to the DAC (digital to analog converter). When coding for the Organelle, you use a throw~ object to output the audio.
The patch I wrote, Wavetable Sampler, reimagines a digital sampler, and in doing so, basically reinvents wavetable synthesis. The conventional approach to sampling is to travel through the sound in a linear fashion from beginning to end. The speed at which we travel through the sound determines both its length and its pitch, that is faster translates to shorter and higher pitched, while slower means longer and lower pitched.
I wanted to try using an LFO (low frequency oscillator) to control where we are in a given sample. Using this technique the sound would go back and forth between two points in the sample continuously. In my programming I quickly learned that two parameters are strongly linked, namely the frequency of this oscillator and the amplitude of the oscillator, which becomes the distance travelled in the sample. If you want the sample to be played at a normal speed, that is we recognize the original sample, those two values need to be proportional. To describe this simply, a low frequency would require the sample to travel farther while a higher frequency would need a small amount of space. Thus, we see the object expr (44100 / ($f1)), with the number 44,100 being the sample rate of the Organelle. Dividing the sample rate by the frequency of the oscillator yields the number of samples that make up a cycle of sound at that frequency.
Obviously, a user might want to specifically move at a different rate than what would be normal. However, making that a separate control prevents the user from having to mentally calculate what would be an appropriate sample increment to have the sample play back at normal speed. I also specified that a user will want to control where we are in a much longer sample. For instance, the sample I am using with this instrument is quite long. It is an electronic cello improvisation I did recently that lasts over four minutes.
The sound I got out of this instrument was largely what I expected. However, there was one aspect that stood out more than I thought it would. I am using a sine wave oscillator in the patch. This means that the sound travels quickly during the rise and fall portion of the waveform, but as it approaches the peak and trough of the waveform it slows down quite dramatically. At low frequencies this results in extreme pitch changes. I could easily have solved this issue by switching to a triangle waveform, as speed would be constant using such a waveform. However, I decided that the oddness of these pitch changes were the feature of the patch, and not the bug.
While I intended the instrument to be used at low frequencies, I found that it was actually far more practical and conventionally useful at audio frequencies. Human hearing starts around 20Hz, which means if you were able to clap your hands 20 times in a second you would begin to hear it as a very low pitch rather than a series of individual claps. One peculiarity of sound synthesis is that if you repeat a series of samples, no mater how random they may be, at a frequency that lies within human hearing, you will hear it as a pitch that has that frequency. The timbre between two different sets of samples at the same frequency may vary greatly, but we will hear them as being, more or less, the same pitch.
Thus, as we move the frequency of the oscillator up into the audio range, it turns into somewhat of a wavetable synthesizer. While wavetable synthesis was created in 1958, it didn’t really exist in its full form until 1979. At this point in the history of synthesis it was an alternative to FM synthesis, which could offer robust sound possibilities but was very difficult to program, and digital sampling, which could recreate any sound that could be recorded but was extremely expensive due to the cost of memory. In this sense wavetable synthesis is a data saving tool. If you imagine a ten second recording of a piano key being struck and held, the timbre of that sound changes dramatically over those ten seconds, but ten seconds of sampling time in 1980 was very expensive. Imagine if instead we can digitize individual waveforms at five different locations in the ten second sample, we can then gradually interpolate between those five waveforms to create a believable (in 1980) approximation of the original sample. That being said, wavetable synthesis also created a rich, interesting approach to synthesizing new sounds such that the technique is still somewhat commonly used today.
When we move the oscillator for Wavetable Sampler into the audio range, we are essentially creating a wavetable. The parameter that effects how far the oscillator travels through the sample creates a very interesting phenomenon at audio rates. When that value is very low, the sample values vary very little. This results in waveforms that approach a sine wave in their simplicity and spectrum. As this value increases more values are included, which may differ greatly from each other. This translates into adding harmonics into the spectrum. Which harmonics are added are dependent up the wavetable, or snippet of a sample, in question. However, as we turn up the value, it tends to add harmonics from lower ones to higher ones. At extreme values, in this case ten times a normal sample increment, the pitch of the fundamental frequency starts to be over taken by the predominant frequencies in that wavetable’s spectrum. One final element of interest with the construction of the instrument in relation to wavetable synthesis is related to the use of a sine wave for the oscillator. Since the rate of change speeds up during the rise and fall portion of the waveform and slows down near the peak and the valley of the wave, that means there are portions of the waveform that rich in change while other portions where the rate of change is slow.
Since the value that the oscillator travels seems to be analogous to increasing the harmonic spectrum, I decided to put that on knob four, as that is the knob I have been controlling via breath pressure with the WARBL. On the Organelle I set knob one to set the index of where we are in the four minute plus sample. The frequency of the oscillator is set by the key that is played, but I use the second knob as a multiplier of this value. This knob is scaled from .001, which will yield a true low frequency oscillator, to 1, which will be at the pitch played (.5 will be down an octave, .25 will be down two octaves, etc.). As stated earlier, the fourth knob is used to modify the amplitude of the oscillator, affecting the range of samples that will be cycled through. This left the third knob unused, so I decided to use that as a decay setting.
The PureData patch that was used to generate the accompaniment for this experiment was based upon the patch created for last month’s experiment. As a reminder, this algorithm randomly chooses between one of four musical meters, 4/4, 3/4, 7/8, and 5/8, at every new phrase. I altered this algorithm to fit a plan I have for six of the tracks on my next studio album, which will likely take three or four years to complete. Rather than randomly selecting them, I define an array of numbers that represent the meters that should be used in the order that they appear. At every phrase change I then move to the next value in the array, allowing the meters to change in a predetermined fashion.
I put the piece of magic that allows this to happen in pd phrasechange. The inlet to this subroutine goes to a sel statement that contains the numbers of new phrase numbers expressed in sixteenth notes. When those values are reached a counter is incremented, a value from the table meter is read, which is sent to the variable currentmeter and the phrase is reset. This subroutine has four outlets. The first starts a blinking light that indicates that the piece is 1/3 finished, the second outlet starts a blinking light that starts when the piece is 2/3 of the way finished. The third outlet starts a blinking light that indicates the piece is on its final phrase. The fourth outlet stops the algorithm, bringing a piece to a close. Those blinking lights are on the right hand side of the screen, located near the buttons that indicate the current meter and the current beat. A performer can then, with some practice watch the computer screen to see what the current meter is, what the current beat is, and to have an idea of where you are in form of the piece.
This month I created my first program for the EYESY, Basic Circles. The EYESY manual includes a very simple example of a program. However, it is too simple it just displays a circle. The circle doesn’t move, none of the knobs change anything, and the circle isn’t even centered. With very little work I was able to center the circle, and change it so that the size of the circle was controlled by the volume of the audio. Likewise, I was able to get knob four to control the color of the circle, and the fifth knob to control the background color.
However, I wanted to create a program that used all five knobs on the EYESY. I quickly came up with the idea of using knob two to control the horizontal positioning, and the third knob to control the vertical positioning. I still had one knob left, and only a simple circle in the middle of the screen to show for it. I decided to add a second circle, that was half the size of the first one. I used knob five to set the color for this second circle, although oddly it does not result in the same color as the background. Yet, this still was not quite visually satisfying, so I set knob one to set an offset from the larger circle. Accordingly, when knob one is in the center, the small circle is centered within the larger one. As you turn the knob to the left the small circle moves to the upper left quadrant of the screen. As you turn the knob to the right the smaller circle moves towards the lower right quadrant. This is simple, but offers just enough visual interest to be tolerable.
import os
import pygame
import time
import random
import math
def setup(screen, etc):
pass
def draw(screen, etc):
size = (int (abs (etc.audio_in[0])/100))
size2 = (int (size/2))
position = (640, 360)
color = etc.color_picker(etc.knob4)
color2 = etc.color_picker(etc.knob5)
X=(int (320+(640*etc.knob2)))
X2=(int (X+160-(310*etc.knob1)))
Y=(int (180+(360*etc.knob3)))
Y2=(int (Y+90-(180*etc.knob1)))
etc.color_picker_bg(etc.knob5)
pygame.draw.circle(screen, color, (X,Y), size, 0)
pygame.draw.circle(screen, color2, (X2,Y2), size2, 0)
While the program, listed above, is very simple, it was my first time programming in Python. Furthermore, targeting the EYESY is not the simplest thing to do. You have plug a wireless USB adapter into the EYESY, connect to the EYESY via a web browser, upload your program as a zip file, unzip the file, and then delete the zip file. You then have to restart the video on the EYESY to see if the patch works. If there is an error in your code, the program won’t load, which means you cannot trouble shoot it, you just have to look through your code line by line and figure it out. Although, I learned to use an online Python compiler to check for basic errors. If you have a minor error in your code the EYESY will sometimes load the program and display a simple error message onscreen, which will allow you to at least figure where the error is.
I’m very pleased with the backing track, and given that it is my first program for the EYESY, with the visuals. I’m not super pleased with the audio from the Organelle. Some of this is due to my playing. For this experiment I used a very limited set of pitches in my improvisation, which made the fingering easier than it has been in other experiments. Also, I printed out a fingering chart and kept it in view as I played. Part of it is due to my lack of rhythmic accuracy. I am still getting used to watching the screen in PureData to see what meter I am in and what the current beat is. I’m sure I’ll get the hang of it with some practice.
One fair question to ask is do I continue to use the WARBL to control the Organelle if I consistently find it so challenging? The simple answer is that consider a wind controller to be the true test of the expressiveness of a digital musical instrument. I should be able to make minute changes to the sound by slight changes in breath pressure. After working with the Organelle for nine months, I can say that it fails this test. The knobs on the Organelle seem to quantize at a low resolution. As you turn a knob you are changing the resistance in a circuit. The resulting current is then quantized, that is its absolute value is rounded to the nearest digital value. I have a feeling that the knobs on the Organelle quantize to seven bits in order to directly correspond to MIDI, which is largely a seven bit protocol. Seven bits of data only allow for 128 possible values. Thus, we hear discrete changes rather than continual ones as we rotate a knob. For some reason I find this short coming is amplified rather than softened when you control the Organelle with a wind controller. At some point I should do a comparison where I control a PureData patch on my laptop using the WARBL without using the Organelle.
I recorded this experiment using multichannel recording, and I discovered something else that is disappointing about the Organelle. I found that there was enough background noise coming from the Organelle that I had to use a noise gate to clean up the audio a bit. In fact, I had to set the threshold at around -35 dB to get rid of the noise. This is actually pretty loud. The Volca Keys also requires a noise gate, but a lower threshold of -50 or -45 dB usually does the trick with it.
Perhaps this noise is due to a slight ground loop, a small short in the cable, RF interference, or some other problem that does not originate in the Organelle, but it doesn’t bode well. Next month I may try another FM or additive instrument. I do certainly have a good head start on the EYESY patch for next month.
As was the case with Experiment 4, this month’s experiment has been a big step forward, even if the music may not seem to indicate an advance. This is due to the fact that this is the first significant Organelle patch that I’ve created, and that I’ve figured out how to connect the EYESY to wifi, allowing me to transfer files to and from the unit. The patch I created, 2opFM, is based upon Node FM by m.wisniowski.
As the name of the patch suggests it is a two operator FM synthesizer. For those who are unfamiliar with FM synthesis, one of the two operators is a carrier, which is an audible oscillator. The other operator is an oscillator that modulates the carrier. In its simplest form, we can think of FM synthesis as being like vibrato. One oscillator makes sound, while the other oscillator changes the pitch of the carrier. We can think of two basic controls that affect the nature of the vibrato, the speed (frequency) of the modulating oscillator, and the depth of modulation, that is how far away from the fundamental frequency does the pitch move.
What makes FM synthesis different from basic vibrato is that typically the modulating oscillator is operating at a frequency within the audio range, often at a frequency that is higher in pitch than that of the carrier. Thus, when operating at such a high frequency, the modulator doesn’t change the pitch of the carrier. Rather it functions to shape the waveform of the carrier. FM Synthesis is most often accomplished using sine waves. Accordingly, as one applies modulation we start to add harmonics, yielding more complex timbres.
Going into detail about how FM synthesis shapes waveforms is well beyond the scope of this entry. However, it is worth noting that my application of FM synthesis here is very rudimentary. The four parameters controlled by the Organelle’s knobs are: transposition level, FM Ratio, release, and FM Mod index. Transposition is in semitones, allowing the user to transpose the instrument up to two octaves in either direction (up or down). FM Ratio only allows for integer values between 1 and 32. The fact that only integers are used here means that the result harmonic spectra will all conform to the harmonic series. Release refers to how long it will take a note to go from its operating volume to 0 after a note ends. The FM Mod index is how much modulation is applied to the carrier, with a higher index resulting in more harmonics added to a given waveform. I put this parameter on the leftmost knob, so that when I control the organelle via my wind controller, a WARBL, increases in air pressure will result in richer waveforms.
As can be seen in the screenshot of main.pd above, 2opFM is an eight voice synthesizer. Eight voice means that eight different notes can be played simultaneously when using a keyboard instrument. Each individual note is passed to the subroutine voice. Determining the frequency of the modulator involves three different parameters: the MIDI note number of the incoming pitch, the transposition level, and the FM ratio. We see the MIDI note number coming out of the left outlet of upack 0 0 on the right hand side, just below r notesIN-$0. For the carrier, we simply add this number to the transposition level, and then convert it to a frequency by using the object mtof, which stands for MIDI to frequency. This value is then, eventually passed to the carrier oscilator. For the modulator, we have to add the MIDI note number to the transposition level, convert it to a frequency, again using mtof, and multiplying this value by the FM Ratio.
In order to understand the flow of this algorithm, we first have to understand the difference between control signals and audio signals. Audio signals are exactly what they sound like. In order to have high quality sound audio signals are calculated at the sample rate, which is 44,100 samples per section by default. In Pure Data, calculations that happen at this rate are indicated by a tilde following the object name. In order to save on processor time, calculations that don’t have to happen so quickly are control signals, which are denoted by a lack of a tilde after the object name. These calculations typically happen once every 64 samples, so approximately 689 times per second.
Knowing the difference between audio signals and control signals, we can now introduce two other objects. The object sig~ converts a control signal into an audio signal. Likewise, i converts a float (decimal value) to an integer, by truncating the value towards zero, that is positive values are rounded down, while negative values are rounded up.
Keep in mind the loadbang portion of voice.pd is used to initialize the values. Here we see the transposition level set at zero, the FM ratio set to one, and the FM Mod index set to 1000. The values from the knobs come in as floats between 0 and 1 inclusive. Thus, typically in order to get useable values we have to perform mathematical operations to rescale them. Under knob 1, we see the transposition level multiplied by 48, and then we subtract 24 from that value. This will yield a value between -24 (two octaves down) and +24 (two octaves up). Under knob 2, we see the FM ratio multiplied by 31, and then we add one to this value, resulting in a value between 1 and 32 inclusive. Both of these values are converted to integers using i.
The scaled value of knob 1 (transposition level) is then added to the MIDI note number, and then turned into a frequency using mtof and converted to an audio signal using sig~. This is now the fundamental frequency of carrier oscillator. In order to get the frequency of the modulator, we need to multiply this value to the scaled value of knob 2. This frequency is then fed to the leftmost inlet of the modulating oscillator (osc~). The output of the modulating oscillator is then multiplied by the scaled output of knob 4 (0 to 12,000 inclusive), which is then in turn multiplied by the fundamental frequency of the carrier oscillator before being fed to the leftmost inlet of the carrier oscillator (osc~). While there is more going on in this subroutine, this explains how the core elements of FM synthesis are accomplished in this algorithm.
The algorithm that is used to generate the accompaniment is largely the same as the one used for Experiment 4 with a couple of changes. First, after completing Experiment 4 I realized I had to find a way to set the sixteenth note counter to zero every time the meter is changed. Otherwise, occasionally when changing from one meter to another there may be one or two extra beats. However, reseting the counter to zero ruins the subroutine that sends automation values. Thus, I had to use two counters, one that keeps counting without being reset (on the right) and one that gets reset every time the meter changes (on the left).
Initially I made a mistake by choosing the new meter at the beginning of a phrase. This caused a problem called a stack overflow. At the beginning of a phrase you’d chose a new meter, which would cause the phrase to reset, which would a new meter to be chosen, which then repeats in an endless loop. Thus, I had chose a new meter at the end of a phrase.
Inside pd choosemeter, we see the phrase counter being sent to two spigots. This spigots are turned on or off from depending on the value of currentmeter. The value 0 under r channel sets the meter for the first phrase to 4/4. Using the nomenclature of r channel is a bit confusing, as s channel is included in loadbang, and was simply included to initialize the MIDI channel numbers for the algorithm. In a future iteration of this program, I may retitle these values as s initializevalues and r initializevalues to make more sense.
Underneath the two spigots, we see sel 64 and sel 48, This finds the end of the phrase when we are in 4/4 (64) or 3/4 (48). Originally I had used the values 63 and 47 as these would be the numbers of the last sixteenth note of each phrase. However, when I did that I found that the algorithm skipped the last sixteenth note of the phrase. Thus, by using 64 and 48 I actually am choosing the meter at the start of a phrase, but now reseting the counter to zero no longer triggers a recursive loop. Regardless, whenever either sel statement is triggered the next meter is chosen randomly, with zero corresponding to 4/4 and 1 corresponding to 3/4. This value is then sent to other parts of the algorithm using send currentmeter, and the phrase is reset by sending a bang to send phrasereset.
As previously noted, I figured out how to connect the EYESY to wifi, allowing me to transfer files two and from the unit. Amongst other things, this allows me to download new EYESY programs from patchstorage.com and add them to my EYESY. I downloaded a patch called Image Shadow Grid, which was developed by dudethedev. This algorithm randomly grabs images stored inside a directory, adds them to the screen, and manipulates them in the process.
I was able to customize this program without changing any of the code simply by changing out the images in the directory. I added images related to a live performance of a piece from my forthcoming album (as Darth Presley). However, up to this point I’d been using the EYESY to respond mainly to audio volume. Some algorithms, such as Image Shadow Grid, use triggers to incite changes in the video output. The EYESY has several trigger modes. I chose to use the MIDI note trigger mode. However, in order to trigger the unit I now have to send MIDI notes to the EYESY.
This constitute the other significant change to the algorithm that generates the accompaniment. I added a subroutine that sends notes to the EYESY. Since the pitch of the notes don’t matter, I simply send the number for middle C (60) to the unit. Otherwise the subroutine which determines whether a note should be sent to the EYESY functions just like those used to generate any rhythm, that is it selects between one of three rhythmic patterns for each of the two meters, each pattern of which is stored as an array.
As with last month, the significant weakness in this month’s experiment is my lack of practice on the WARBL. Likewise, it would have been useful if I had the opportunity to add a third meter to the algorithm that generates the accompaniment. The Organelle program 2opFM is not quite as expressive with the WARBL as it had been in experiment 2 and 4. Changes in the FM Mod Index aren’t as smooth as I had hoped they’d be. Perhaps if I were to expand the patch further, I’d want to add a third operator, and separate the FM Mod Index into two parts, one where you set the maximum level of the index, and another where you set the current level, so you can set it where the maximum breath pressure on the WARBL only yields a subtle amount of modulation.
In terms of the EYESY, I doubt I will begin writing programs for it next month, I may experiment with already existing algorithms that allow the EYESY to use a webcam. However, hopefully by October I can be hacking some Python code for the EYESY. My current plan is to experiment with some additive synthesis next month, so stay tuned.
June has been busy for me. I’m behind where I wanted to be at this point in my research. This is due in part to not having a USB WiFi adapter to transfer files onto the Organelle and the EYESY. Accordingly, this month’s post will be light on programming, focusing on the Pure Data object route. I’ll be ordering one later this week, and will hopefully be able to take a significant step forward in July.
Accordingly, my third experiment in my project funded by Digital Innovation Lab at Stonehill College investigates the use of the preset patch Deterior (designed by Critter and Guitari). Deterior is an audio looper combined with audio effects in a feedback loop. In this experiment I run audio from a lap steel guitar.
The auxiliary key is used in conjunction with the black keys of the keyboard to select various functions. The lowest C# toggles loop recording on or off , the next D# stores the recording, the F# reverts to the most recent recording (removing any effects), the G# empties the loop, while A# toggles the input monitor. The upper five black keys of the instrument toggle on or off the five different effects that are available: noise (C#), clip (D#), silence (F#), pitch shift (G#), and filter (A#). The parameters of these effects cannot be changed from the Organelle, they can only be turned on or off. The routing of these auxiliary keys is accomplished through the subroutine shortcut.pd, using the statement route 61 63 66 68 70 73 75 78 80 82. Note that these numbers correspond to the MIDI note numbers for the black keys from C#4 to A#5.
A similar technique is used with the white keys of the instrument. These keys are used as storage slots for recorded loops, which can be recalled at any time once they are stored. This is initiated in pd slots, using route 60 62 64 65 67 69 71 72 74 76 77 79 81 83. These numbers correspond to the white keys from C4 to B5.
In this experiment I start using only filtering. Eventually I added silence, clipping, noise, and finally pitch shifting. Specifically, you can hear noise entering at 5:09. After adding all the effects in I stopped playing new audio, and instead focused on performing the knobs of the Organelle. Near the end of the experiment I start looping and layering a chord progression: Am, Dm, C#m, to Bm. When I introduce this progression I add one chord from this progression at a time.
In terms of the EYESY, I ran the recording through it so I would have my hands free to perform the settings. Again, I used a preset as I did not have a wireless USB connection to transfer files between my laptop and the EYESY. Hopefully next month I should be able to do deeper work with the EYESY.
Like Experiment 1, I had a lot of 60 cycle hum in the recording, which I tried to minimize by turning down the volume on the lap steel when I’m not recording sound. That process created it’s own distracting aspect of having the 60 cycle hum fade in and out in a repeating loop.
The first experiment in my project funded by Digital Innovation Lab at Stonehill College investigates the use of the preset patch Granular Freezer (designed by Critter and Guitari) to process audio . In this case the audio is coming from a lap steel guitar. In that I’m just getting used to both the Organelle and the EYESY, I will simply be improvising using a preset with the EYESY.
While describing his concept of stochastic music, composer Iannis Xenakis essentially also described the idea of granular synthesis in his book Formalized Music: Thought and Mathematics in Music . . .
“Other paths also led to the same stochastic crossroads . . . natural events such as the collision of hail or rain with hard surfaces, or the song of cicadas in a summer field. These sonic events are made out of thousands of isolated sounds; this multitude of sounds, seen as a totality, is a new sonic event. . . . Everyone has observed the sonic phenomena of a political crowd of dozens or hundreds of thousands of people. The human river shouts a slogan in a uniform rhythm. Then another slogan springs from the head of the demonstration; it spreads towards the tail, replacing the first. A wave of transition thus passes from the head to the tail. The clamor fills the city, and the inhibiting force of voice and rhythm reaches a climax. It is an event of great power and beauty in its ferocity. Then the impact between the demonstrators and the enemy occurs. The perfect rhythm of the last slogan breaks up in a huge cluster of chaotic shorts, which also spreads to the tail. Imagine, in addition, the reports of dozens of machine guns and the whistle of bullets adding their punctuations to this total disorder. The crowd is then rapidly dispersed, and after sonic and visual hell follows a detonating clam, full of despair, dust, and death.”
This passage by Xenakis goes into dark territory very quickly, but it is a scenario that harkened back to the composer’s past when he lost an eye during a conflict with occupying British tanks during the Greek Civil War.
Granular synthesis was theorized before it was possible. Its complexity requires computer technology that at the time it was theorized was not yet powerful enough. Granular synthesis takes an audio waveform, sample, or audio stream and chops it into grains and then resynthesizes the sound by combining them into clouds. The synthesist can often control aspects such as grain length, grain playback speed, cloud density, as well as others. Since the user can control playback speed of grains independently of the speed to which a sound travels through a group of grains, granular synthesis allows one to stretch or compress the timing of sound without affecting pitch, as well as being able to change the pitch of a sound without affecting the duration of a sound.
Granular Freezer is sort of a budget version of Mutable Instruments Clouds. I call it a budget version, as Clouds allows for the control of more than a half dozen parameters of the sound, while Granular Freezer gives the user control of four parameters, namely grain size, spread, cloud density, and wet / dry mix. These four parameters correspond to the four prominent knobs on the Organelle. Spread can be thought of as a window, that kind of functions like a delay time. In other words it is a window of past audio that the algorithm draws from to create grains. As you turn the spread down the sound starts to sound like an eccentric slap (short) delay. Wet / dry mix is a very standard parameter in audio processing. It is the ratio of processed sound to original sound that is sent to the output. The Aux button can be used to freeze the sound, that is hold the current spread in memory until the sound is unfroze. You may also use a pedal to trigger this function. One feature of the algorithm that I didn’t use was using the MIDI keyboard to transpose the audio.
Since this is my first experiment with the Organelle, I’m not going to go through the algorithm in great detail, but I will give it an overview. All patches for the Organelle use a patch called a mother patch. The mother patch should never be altered. This controls input to and output from the Organelle. Such values are passed to and from the mother patch in order to avoid input and output errors. You can download the mother patch so you can develop instruments on a computer without having access to an Organelle. This is also a good way to check for coding errors before you upload a patch to your Organelle.
If we double click on the subroutine pd MIDI, we can see, amongst other things how the Organelle translates incoming MIDI controller data (controller numbers 21, 22, 23, & 24) to knob data . .
When we double click on pd audioIO, we can see how the mother patch handles incoming audio (left) as well as outgoing audio (right) . . .
Any given Organelle patch typically consists of a main program (by convention, named main.pd), as well as a number of self contained subpatches called abstractions. In the case of Granular Freezer, in addition to the main program there are three abstrations: latch-notes.pd, grain.pd, and grainvoice.pd. Given the complexity of the program, I will only go over main.pd.
In the upper right hand quadrant we see the portion of the algorithm that handles input and output. It also controls the ability to freeze the audio (pd freezer). The objects catch~ grainoutL and catch~ grainoutR receive the granularly processed audio from grainvoice.pd. The object r wetdry receives data from knob 4, allowing the user to control the ratio of unprocessed sound to processed sound.
The lower half of main.pd sets the numerical range for each of the four knobs, sends the data to wherever it is needed (as was done with wetdry), and sets & sends the text to be displayed on the Organelle’s screen. This last item causes the function of each knob to be displayed along with its current status. In the message box at the bottom of the screen, we see a similar item related to the aux key screenLine5. The part of the program that updates the display for screenLine5 is in pd freezer.
In the improvisation I run a six string lap steel using C6 tuning through a volume pedal, and then into the Organelle. I also use a foot switch to trigger the freeze function on the patch. Musically, I spend the bulk of the time improvising over an E pedal provided by an eBow on the open low E string. A lot of the improvisation is devoted to arpeggiating Am, C#m, and Em chords on the upper three strings of the instrument. During the beginning of the improvisation the mix is at 80% (only 20% of the original sound). I quickly move to 100% mix. Near the end I move to sliding pitches with the eBow. During this portion of the improvisation I experiment with the spread, and there’s a portion where I move the spread close to its minimal amount, which yields that eccentric slap delay sound (starts around 8:28). As I move the spread towards its upper end, I can use it as a harmonizer, as the spread holds the previous pitch in its memory as I move onto a new harmonizing pitch. At the end (around 9:15) I move the grain size down to the bottom (1 millisecond), and then turn the cloud density down to the bottom to function as a fade out.
With the EYESY I simply improvised the video using the audio of the video recording I made. With the mode I was using the first two knobs seemed to control the horizontal and vertical configuration of the polygons. These controls allow you to position them in rows, or in a diamond lattice configuration. You can even use these controls to get the polygons to superimpose to an extent. The middle knob seems to increase the size of the polygons, making them overlap a considerable amount. The two knobs on the right control the colors for the polygons and the background respectively. I used these to start from a green on black configuration in honor of the Apple IIe computer.
The video below will allow you to watch the EYESY improvisation and the musical improvisation simultaneously . . .
As I mentioned earlier, I consider Granular Freezer to be a budget version of Clouds. I have the CalSynth clone of Clones, Monsoon, in a synthesizer rack I’m assembling. It is a wonderful, expressive instrument that creates wonderful sounds. While Granular Freezer is a more limited instrument, it is still capable of creating some wonderful sounds. There are already a couple variants of Granular Freezer posted on PatchStorage. As I get more familiar with programming for the Organelle, I should be able to create a version of the patch that allows for far greater control of parameters.
All in all, I feel this was a successful experiment. I should be able to reuse the audio for other musical projects. However, there was some room for improvement. There was a little bit of 60 cycle hum that was coming through the system. This was likely due to a cheap pickup in my lap steel. Likewise, it would be nice if I cleaned up my studio so it would make for a less cluttered YouTube video. As I mentioned earlier it would be good to add more parameters to the Granular Freezer patch. I used Zoom to capture the video created by the EYESY, and it added my name to the lower left hand corner of the screen. Next time I may try using QuickTime for video capture to avoid that issue. By the end of the summer I hope to develop some PureData algorithms to control the EYESY to perform the video in an automated fashion. See you all back here next month for the next installment.
I am proud to announce that I have received a Digital Innovation Grant from the Digital Innovation Lab at the MacPháidín Library. The project will be centered on learning sound synthesis in Pure Data using Critter & Guitari’sOrganelle. An additional component of the project will be in using video synthesis using the EYESY (also made by Critter & Guitari). The EYESY generates video in real-time that reacts to MIDI data, and / or audio. Programs for the EYESY can be written in Python or openFrameworks/LUA.
The format of this project will be a series of monthly experiments that will include both the Organelle and EYESY. Some of these will use the Organelle as an audio processor (similar to a guitar effects pedal), while others will use it as a synthesizer / sampler using a variety of approaches to sound synthesis / sampling. Many of these experiments will make use of computer-assisted composition algorithms created in Pure Data, building off of research I’ve been doing already over the past year. Each experiment will also be a brief musical composition inspired by the Experimental Music as defined by Lejaren Hiller in his seminal book Experimental Music: Composition with an Electronic Computer.
The outcome of these experiments will be monthly informal reports made through this blog, as well as a series of YouTube videos of the works themselves, which will be embedded into the blog entries. A year from now, once I’ve created 12 such musical experiments, I will give a lecture recital that presents these experiments. One final outcome will be to consider adding Pure Data oriented assignments to VPM 248: Sound Synthesis. I look forward to working on this project, and will commence working on it once the materials come in.
