I have a KY-022 IR module that I can't get to work on my NodeMCU. I've been searching for some code samples in Lua on the internet with no luck. Can anyone point me in the right direction? Any code samples would be greatly appreciate it.
At the moment I have the following code:
local pin = 4
gpio.mode(pin, gpio.OPENDRAIN, gpio.PULLUP)
gpio.trig(pin, "down", function (level, micro)
print(gpio.read(pin), level, micro)
end)
When I press a button on the remote, I get something like this:
0 0 571940709
0 0 571954086
0 0 571955257
1 0 571958694
1 0 571963275
1 0 571969917
0 0 571974347
0 0 571980989
1 0 571983203
1 0 571987709
0 0 571993359
1 0 572000078
0 0 572004508
0 0 572047513
0 0 572058674
So, how do I get from that to figuring out which key was pressed on the remote?
After a month or so i've reopened this project and played around with it some more. As piglet suggested, I started listening for both high and low signals. The data is still very inconsistent and can't get a stable reading.
(And by the way, thanks for the vote-down piglet, that was greatly appreciated. I wish you could have seen my search history before you decided that i'm ignorant)
I'm going to post my curent code maybe somebody can point out what I'm doing wrong here.
local pin = 4
local prevstate = false
local prevmicro = 0
local prevtime = 0
local count = 0
gpio.mode(pin, gpio.INT)
gpio.trig(pin, "both", function (level, micro)
--local state = gpio.read(pin)
local state = level
if (micro - prevmicro) > 90000 then
prevmicro = 0
prevstate = false
count = 0
print("\n#", "st", "lv", "microtime", "timing")
end
if prevstate ~= state then
time = math.floor((micro - prevmicro)/100)
prevstate = state
prevmicro = micro
if time > 3 and time < 1000 then
if prevtime > 80 and prevtime < 100 then
if time > 17 and time < 25 then
print('Repeat')
elseif time > 40 and time < 50 then
print('Start')
end
else
print(count, gpio.read(pin), level, micro, time)
count = count + 1
end
prevtime = time
end
end
end)
and here are some sample readouts from pushing the same button:
# st lv microtime timing
1 1 1 1504559531 16
2 1 0 1504566995 74
3 0 1 1504567523 5
4 1 0 1504573619 60
5 0 1 1504587422 138
6 1 0 1504588011 5
7 1 1 1504604250 162
8 1 0 1504605908 16
9 1 1 1504659929 540
10 1 0 1504662154 22
# st lv microtime timing
1 1 1 1505483535 16
2 1 0 1505491003 74
3 0 1 1505491558 5
4 1 0 1505497627 60
5 0 1 1505511409 137
6 1 0 1505512023 6
7 1 1 1505518186 61
8 1 0 1505527733 95
9 1 0 1505586167 22
10 1 1 1505586720 5
# st lv microtime timing
1 1 1 1507990937 16
2 1 0 1507998405 74
3 0 1 1507998934 5
4 1 0 1508005029 60
5 0 1 1508018811 137
6 1 0 1508019424 6
7 1 1 1508035641 162
8 1 0 1508037322 16
9 1 1 1508091345 540
10 1 0 1508093570 22
As it turns out, the Lua code required for this is actually quite simple.
Where the code above is falling over is actually the print statements. These are extremely expensive and basically, kill your sampling resolution until it's useless.
You are in essence, writing an interrupt service routine, you have a limited time budget before you have to read the next edge change and if it happens before you are done processing, tough luck! So you need to make the ISR as efficient as you can.
In the example below, we listen to the "both" edge event, when one occurs, we simply record an indication of which edge and what duration.
Periodically (using a timer) we print out the contents of the waveform.
This perfectly matches the waveform on my logic analyzer, you still have the challenge of decoding the signal. Though, there are lots of great protocol docs that explain how to take accurate waveform data and use it to determine the signal being sent. I found that a lot of cheap "brand x" remotes appear to be using the NEC protocol, so this might be a good place to start depending on your project.
IR transmission because of its nature is not completely error-free so you may get a spurious edge signal from time to time but the code below is pretty stable and runs quite well in isolation, I have yet to test it when the Microcontroller is under more load than just listening for IR.
It may turn out that using Lua for this purpose is not the best due to the fact that it is an interpreted language (each command issued is parsed and then executed at runtime, this is not at all efficient.) But I will see how far I can get before I decide to write a c module.
local irpin = 2
local lastTimestamp = 0
local waveform = {}
local i = 1
gpio.mode(irpin,gpio.INT)
gpio.trig(irpin, "both", function(level, ts)
onEdge(level, ts)
end)
function onEdge(level, ts)
waveform[i] = level
waveform[i+1] = ts - lastTimestamp
lastTimestamp = ts
i = i+2
end
-- Print out the waveform
function showWaveform ()
if table.getn(waveform) > 65 then
for k,v in pairs(waveform) do
print(k,v)
end
i = 1;
waveform = {}
end
end
tmr.alarm(0, 1000, 1, showWaveform)
print("Ready")
The following code works for my 17 key remote which came with my cheap KY-022 module. I just finished it and haven't had time to clean it up nor to optimize it, so bear with me.
local IR = 2
local lts, i, wave = 0, 0, {}
local keys = {}
keys['10100010000000100000100010101000'] = '1'
keys['10001010000000100010000010101000'] = '2'
keys['10101010000000100000000010101000'] = '3'
keys['10000010000000100010100010101000'] = '4'
keys['10000000000000100010101010101000'] = '5'
keys['10101000000000100000001010101000'] = '6'
keys['10101010000000000000000010101010'] = '7'
keys['10100010001000000000100010001010'] = '8'
keys['10100000100000000000101000101010'] = '9'
keys['10100000101000000000101000001010'] = '0'
keys['10001010001000000010000010001010'] = '*'
keys['10100010100000000000100000101010'] = '#'
keys['10000000101000000010101000001010'] = 'U'
keys['10000000100000000010101000101010'] = 'L'
keys['10001000101000100010001000001000'] = 'R'
keys['10001000001000100010001010001000'] = 'D'
keys['10000010101000000010100000001010'] = 'OK'
local function getKey()
local data = ''
local len = table.getn(wave)
if len >= 70 then
local pkey = 0
local started = false
for k, v in pairs(wave) do
v = math.floor(v/100)
if (pkey == 87 or pkey == 88 or pkey == 89) and (v > 40 and v < 50) then
started = true
end
pkey = v
if started then
if v > 300 then
started = false
end
--this is just to fix some random skipped edges
if (v > 20 and v < 25) or v == 11 then
if v > 20 and v < 25 then
d = 17
else
d = 6
end
v1 = v - d
data = data .. '' .. math.floor(v1/10)
v2 = v - (v - d)
data = data .. '' .. math.floor(v2/10)
else
if v < 40 then
data = data .. '' .. math.floor(v/10)
end
end
end
end
control = data:sub(0, 32)
if control == '00000000000000000101010101010101' then
data = data:sub(32, 63)
print(len, data, keys[data] or '?')
end
end
lts, i, wave = 0, 0, {}
end
local function onEdge(level, ts)
local time = ts - lts
wave[i] = time
i = i + 1
if time > 75000 then
tmr.alarm(0, 350, 0, getKey)
end
lts = ts
end
gpio.mode(IR,gpio.INT)
gpio.trig(IR, "both", onEdge)
I'm putting this asside and start working on some other parts of my project for the moment, but if anyone has any suggestions on how I could improve it, make it faster, smaller even, leave a comment.
PS: for those that are going to complain about not working for them, you need to adjust the if statement values for the started variable based on your remote timings. In my case it's always 88 or 89 followed by 44.
You have to get the sequence sent by the remote for each button.
Record the IR emitter's on-off sequence by logging the time stamps for high-low and low-high transitions.
Note the various patterns for each button you want to use or emulate.
Here's a in-depth tutorial http://www.instructables.com/id/How-To-Useemulate-remotes-with-Arduino-and-Raspber/
You can find this and similar resources using www.google.com
Related
My issue is, i don't know how to use the output of a function properly. The output contains multiple lines (j = column , i = testresult)
I want to use the output for some other rules in other functions. (eg. if (i) testresult > 5 then something)
I have a function with two loops. The function goes threw every column and test something. This works fine.
def test():
scope = range(10)
scope2 = range(len(df1.columns))
for (j) in scope2:
for (i) in scope:
if df1.iloc[:,[j]].shift(i).loc[selected_week].item() > df1.iloc[:,[j]].shift(i+1).loc[selected_week].item():
i + 1
else:
print(j,i)
break
Output:
test()
1 0
2 3
3 3
4 1
5 0
6 6
7 0
8 1
9 0
10 1
11 1
12 0
13 0
14 0
15 0
I tried to convert it to list, dataframe etc. However, i miss something here.
What is the best way for that?
Thank you!
A fix of your code would be:
def test():
out = []
scope = range(10)
scope2 = range(len(df1.columns))
for j in scope2:
for i in scope:
if df1.iloc[:,[j]].shift(i).loc[selected_week].item() <= df1.iloc[:,[j]].shift(i+1).loc[selected_week].item():
out.append([i, j])
return pd.DataFrame(out)
out = test()
But you probably don't want to use loops as it's slow, please clarify what is your input with a minimal reproducible example and what you are trying to achieve (expected output and logic), we can probably make it a vectorized solution.
This is the R script that I am attempting to recreate using a CASE WHEN statement in SQL:
dat[ ,X_1_7_Spline := pmax(1,pmin(ifelse(is.na(X),1,X),7))]
It seems that this command is telling the parser to return the parallel maxima of a vector containing a conditional statement as long as the value of variable X lies between 1 and the parallel minima of some value and 7 (as long as the value is not null). It then seems to join the new column containing these values back to the original dataset (dat). I am having some troubles representing the "pmax(1,pmin(ifelse(is.na(X),1,X),7))" portion of the code in my SQL query and would appreciate any ideas on how I might be able to do this effectively.
I have something very remedial right now, which I know does not express this above statement properly:
CASE WHEN MAX(IF(ISNOTNULL(X) AND MIN(X)=1 AND MAX(X)=7) then 1 else X end as X_1_7_Spline
Any thoughts/feedback would be greatly appreciated as I am still trying to understand the R script. Thanks in advance for any insight on this issue.
ifelse(is.na(X),1,X) can be translated into SQL's COALESCE(X, 1); and
pmin and pmax logic can be placed in a CASE WHEN (as you've started)
Perhaps this?
CASE WHEN X < 1 THEN 1
WHEN X > 7 THEN 7
ELSE coalesce(X, 1) END as NewX
We don't need to worry about coalesceing the X < 1 or X > 7 because null < 1 does not resolve as true, so it does not accept that case.
Demo in R using sqldf:
library(data.table)
dat <- data.table(X = c(-1,5,9,NA))
dat[, X_1_7_Spline := pmax(1,pmin(ifelse(is.na(X),1,X),7)) ]
sqldf::sqldf("select *, (CASE WHEN X < 1 THEN 1 WHEN X > 7 THEN 7 ELSE coalesce(X,1) END) as NewX from dat")
# X X_1_7_Spline NewX
# 1 -1 1 1
# 2 5 5 5
# 3 9 7 7
# 4 NA 1 1
My code uses a column called booking status that is 1 for yes and 0 for no (there are multiple other columns that information will be pulled from dependant on the booking status) - there are lots more no than yes so I would like to take a sample with all the yes and the same amount of no.
When I use
samp = rslt_df.sample(n=298, random_state=1, weights='bookingstatus')
I get the error:
ValueError: Fewer non-zero entries in p than size
Is there a way to do this sample this way?
If our entire dataset looks like this:
print(df)
c1 c2
0 1 1
1 0 2
2 0 3
3 0 4
4 0 5
5 0 6
6 0 7
7 1 8
8 0 9
9 0 10
We may decide to sample from it using the DataFrame.sample function. By default, this function will sample without replacement. Meaning, you'll receive an error by specifying a number of observations larger than the number of observations in your initial dataset:
df.sample(20)
ValueError: Cannot take a larger sample than population when 'replace=False'
In your situation, the ValueError comes from the weights parameter:
df.sample(3,weights='c1')
ValueError: Fewer non-zero entries in p than size
To paraphrase the DataFrame.sample docs, using the c1 column as our weights parameter implies that rows with a larger value in the c1 column are more likely to be sampled. Specifically, the sample function will not pick values from this column that are zero. We can fix this error using either one of the following methods.
Method 1: Set the replace parameter to be true:
m1 = df.sample(3,weights='c1', replace=True)
print(m1)
c1 c2
0 1 1
7 1 8
0 1 1
Method 2: Make sure the n parameter is equal to or less than the number of 1s in the c1 column:
m2 = df.sample(2,weights='c1')
print(m2)
c1 c2
7 1 8
0 1 1
If you decide to use this method, you won't really be sampling. You're really just filtering out any rows where the value of c1 is 0.
I was able to this in the end, here is how I did it:
bookingstatus_count = df.bookingstatus.value_counts()
print('Class 0:', bookingstatus_count[0])
print('Class 1:', bookingstatus_count[1])
print('Proportion:', round(bookingstatus_count[0] / bookingstatus_count[1], 2), ': 1')
# Class count
count_class_0, count_class_1 = df.bookingstatus.value_counts()
# Divide by class
df_class_0 = df[df['bookingstatus'] == 0]
df_class_0_under = df_class_0.sample(count_class_1)
df_test_under = pd.concat([f_class_0_under, df_class_1], axis=0)
df_class_1 = df[df['bookingstatus'] == 1]
based on this https://www.kaggle.com/rafjaa/resampling-strategies-for-imbalanced-datasets
Thanks everyone
I have a dataframe as shown below
Inspector_ID Sector Waste Fire Traffic
1 A 7 2 1
1 B 0 0 0
1 C 18 2 0
2 A 1 6 3
2 B 1 4 0
2 C 4 14 2
3 A 0 0 0
3 B 2 6 12
3 C 0 1 4
From the above dataframe I would like to calculate the Inspector's expertise score in raising issues in a domain (waste, Fire and Traffic).
For example the the score of inspector-1 for waste is (((7/8)*2) + ((18/22)*3)/2)/2
I1W = Inspector-1 similarity in waste.
Ai = No. of waste issues raised by inspector-1 in sector i
Ti = Total no. of waste issues in sector i
Ni = No of inspectors raised issues in sector i(if all zero then only it is considered as not raised)
TS1 = Total no of sectors the inspector-1 visited.
I1W = Sum((Ai/Ti)*Ni)/TS1
The expected output is below dataframe
Inspector_ID Waste Fire Traffic
1 I1W I1F I1T
2 I2W I2F I2T
3 I3W I3F I3T
TBF = To be filled
You could look into something along the lines of:
newData = []
inspector_ids = df['Inspector_ID'].unique().tolist()
for id in inspector id:
current_data = df.loc[df['Inspector_id'] == id]
#With the data of the current inspector you get the desired values
waste_val = 'I1W'
fire_val = 'I1F'
traffic_val = 'I1T'
newData.append([id,waste_val, fire_val, traffic_val])
new_df = pd.DataFrame(newData, columns = ['Inspector_ID','Waste','Fire','Traffic'])
Some ideas for getting the values you need
#IS1 = Sectors visited by inspector 1.
#After the first loc that filters the inspector
sectors_visited = len(df['Sector'].unique().tolist())
#Ai = No. of waste issues raised by inspector-1 in sector i
waste_Issues_A = current_data.loc[current_data['Sector' == A].value_counts()
#Ti = Total no. of waste issues in sector i
#You can get total number of issues by sector with
df['Sector'].value_counts()
#Ni = No of inspectors raised issues in sector i(if all zero then only it is considered as not raised)
#I dont know if i understand this one correctly, I guess its the number
#of inspectors that raised issues on a sector
inspectors_sector_A = len(df.loc[df['Sector'] == A]['Inspector_ID'].unique().tolist())
The previous was done by memory so take the code with a grain of salt (Specially the Ni one).
I have a text file with a header of information followed by lines with just numbers, which are the data to be read.
I don't know how many lines are there in the header, and it is a variable number.
Here is an example:
filehandle: 65536
total # scientific data sets: 1
file description:
This file contains a Northern Hemisphere polar stereographic map of snow and ice coverage at 1024x1024 resolution. The map was produced using the NOAA/NESDIS Interactive MultisensorSnow and Ice Mapping System (IMS) developed under the directionof the Interactive Processing Branch (IPB) of the Satellite Services Division (SSD). For more information, contact: Mr. Bruce Ramsay at bramsay#ssd.wwb.noaa.gov.
Data Set # 1
Data Label:
Northern Hemisphere 1024x1024 Snow & Ice Chart
Coordinate System: Polar Stereographic
Data Type: BYTE
Format: I3
Dimensions: 1024 1024
Min/Max Values: 0 165
Units: 8-bit Flag
Dimension # 0
Dim Label: Longitude
Dim Format: Device Coordinates
Dim Units: Pixels
Dimension # 1
Dim Label: Latitude
Dim Format: Device Coordinates
Dim Units: Pixels
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
3 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
..........................
I open the file using:
open(newunit=U, file = ValFile, STATUS = 'OLD', ACCESS = 'SEQUENTIAL', ACTION = 'READ')
Then, I read the file line by line and test for the type of line: header line or data line:
ios = 0
do while ( .NOT. is_iostat_end(ios) )
read(U, '(A)', iostat = ios, advance = 'NO') line ! Shouldn't advance to next line
if (is_iostat_end(ios)) stop "End of file reached before data section."
tol = getTypeOfLine(line, nValues) ! nValues = 1024, needed to test if line is data.
if ( tol > 0 ) then ! If the line holds data.
exit ! Exits the loop
else
read(U, '(A)', iostat = ios, advance = 'YES') line ! We advance to the next line
end if
end do
But the first read in the loop, always advances to the next line, and this is a problem.
After exiting the above loop, enter a new loop to read the data:
read(U, '(1024I1)', iostat = ios) Values(c,:)
The 1024 set of data can span some lines, but each set is a row in the matrix "Values".
The problem is that this second loop doesn't read the last line read in the testing loop (which is the first line of data).
A possible solution is to read the lines in the testing loop, without advancing to the next line. I used for this, advance='no', but it still advances to the next line, Why?.
A non-advancing read will still set the file position to before start of the next record if the end of the current record is encountered while reading from the file to satisfy the items in the output item list of the read statement - non-advancing doesn't mean "never-advancing". You can use the value assigned to the variable nominated in an iostat specifier for the read statement to see if the end of the current record was reached - use the IS_IOSTAT_EOR intrinsic or test against the equivalent value from ISO_FORTRAN_ENV.
(Implicit in the above is the fact that a non-advancing read still advances over the file positions that correspond to items actually read... hence once that getTypeOfLine procedure decides that it has a line of data at least part of that line has already been read. Unless you reposition the file subsequent "data" read statements will miss that part.)