x = fopen('pm10_data.txt');
fseek(x, 8,0);
dat = fscanf (x,'%f',[2,1000]);
dat = transpose(dat);
a = dat(:,1);
b = dat(:,2);
[r,p] = cor_test (a,b)
fclose(x);
r
p
this is what i got,
r =
scalar structure containing the fields:
method = Pearson's product moment correlation
params = 76
stat = 6.2156
dist = t
pval = 2.5292e-08
alternative = !=
Run error
error: element number 2 undefined in return list
error: called from
tester.octave at line 7 column 6
Presumably you're referring to the cor_test function from the statistics package, even though you don't show loading this in your workspace.
According to the documentation of cor_test:
The output is a structure with the following elements:
PVAL The p-value of the test.
STAT The value of the test statistic.
DIST The distribution of the test statistic.
PARAMS The parameters of the null distribution of the test statistic.
ALTERNATIVE The alternative hypothesis.
METHOD The method used for testing.
If no output argument is given, the p-value is displayed.
This seems to be what you're getting too.
If you want the p value explicitly from that structure, you can access that as r.pval
The syntax [a, b, ...] = functionname( args, ... ) expects the function to return more than one argument, and capture all the returned arguments into the named variables (i.e. a, b, etc).
In this case, cor_test only returns a single argument, even though that argument is a struct (which means it has fields you can access).
The error you're getting effectively means you requested a second output argument p, but the function you're using does not return a second output argument. It only returns that struct you already captured in r.
Related
R = [cos(pi/3) sin(pi/3); -sin(pi/3) cos(pi/3)]
[i,j]=round([1 1] * R)
returns
i =
-0 1
error: element number 2 undefined in return list
While I want i=0 and j=1
Is there a way to work around that? Or just Octave being stupid?
Octave is not being stupid; it's just that you expect the syntax [a,b] = [c,d] to result in 'destructuring', but that's not how octave/matlab works. Instead, you are assigning a 'single' output (a matrix) to two variables. Since you are not generating multiple outputs, there is no output to assign to the second variable you specify (i.e. j) so this is ignored.
Long story short, if you're after a 'destructuring' effect, you can convert your matrix to a cell, and then perform cell expansion to generate two outputs:
[i,j] = num2cell( round( [1 1] * R ) ){:}
Or, obviously, you can collect the output into a single object, and then assign to i, and j separately via that object:
[IJ] = round( [1 1] * R ) )
i = IJ(1)
j = IJ(2)
but presumably that's what you're trying to avoid.
Explanation:
The reason [a,b] = bla bla doesn't work, is because syntactically speaking, the [a,b] here isn't a normal matrix; it represents a list of variables you expect to assign return values to. If you have a function or operation that returns multiple outputs, then each output will be assigned to each of those variables in turn.
However, if you only pass a single output, and you specified multiple return variables, Octave will assign that single output to the first return variable, and ignore the rest. And since a matrix is a single object, it assigns this to i, and ignores j.
Converting the whole thing to a cell allows you to then index it via {:}, which returns all cells as a comma separated list (this can be used to pass multiple arguments into functions, for instance). You can see this if you just index without capturing - this results in 'two' answers, printed one after another:
num2cell( round( [1 1] * R ) ){:}
% ans = 0
% ans = 1
Note that many functions in matlab/octave behave differently, based on whether you call them with 1 or 2 output arguments. In other words, think of the number of output arguments with which you call a function to be part of its signature! E.g., have a look at the ind2sub function:
[r] = ind2sub([3, 3], [2,8]) % returns 1D indices
% r = 2 8
[r, ~] = ind2sub([3, 3], [2,8]) % returns 2D indices
% r = 2 2
If destructuring worked the way you assumed on normal matrices, it would be impossible to know if one is attempting to call a function in "two-outputs" mode, or simply trying to call it in "one-output" mode and then destructure the output.
I have three float arrays of data (A,B,C) that I want to send it to event hub.
The issue here is that the classes are nested and I can't figure out how to shape the data to be able to send successfully.
Here is the code that I am trying
logger = logging.getLogger("azure")
ADDRESS = ""
USER = ""
KEY = ""
try:
if not ADDRESS:
raise ValueError("No EventHubs URL supplied.")
# Create Event Hubs client
client = EventHubClient(ADDRESS, debug=False, username=USER, password=KEY)
sender = client.add_sender(partition="0")
client.run()
x_value = np.arange(100)
try:
start_time = time.time()
for i in range(100000):
A = np.asarray([1,2,3,4])
B = np.asarray([2,3,4,5])
C = np.asarray([3,4,5,6])
message = [A, B, C]
sender.send(EventData(body = message))
time.sleep(1)
except:
raise
finally:
end_time = time.time()
client.stop()
run_time = end_time - start_time
logger.info("Runtime: {} seconds".format(run_time))
except KeyboardInterrupt:
pass
In this way, I am seeing the error 'ValueBody' object has no attribute 'append'
I think by types, the class encodes the message differently.
Instead of sending a single message with a serial string, I want to send the message in a parallel way, and receive them something like this:
Receive one eventdata with the form of the list [A,B,C]
Receive three eventdata A, B, C separately, like calling three different objects basis.
For the second way, I am not sure if it would work since I am using only one partition and that may have the three eventdata A, B, C mixed when I receive them and I do not want that.
I have confirmed with ms support, the feedback is that: it only works for a list of string or bytes, but does not work for a list of int.
And also you should note that, even it sends a list of string, when receive the list, it will concatenate the all elements of the list to compose a single message. For example, if there is a list ["a","b","c","d"] for sending, when receive it, it will show this "abcd" as a whole string.
I have tested it by myself, the above information is correct.
So for your case, you should consider change the list to a string or json string. when receiving it, you can format the data to what you need.
Hope it helps.
This is my first time participating in a kaggle competition and I'm having trouble submitting my result table. I made my model using gbm and made a prediction table like below. the submission file has 2 column named 'fullVisitorId' and 'PredictedLogRevenue') as any other kaggle competition cases.
pred_oob = predict(object = model_gbm, newdata = te_df, type = 'response')
mysub = data.frame(fullVisitorId = test$fullVisitorId, Pred = pred_oob)
mysub = mysub %>%
group_by(fullVisitorId) %>%
summarise(Predicted = sum(Pred))
submission = read.csv('sample_submission.csv')
mysub = submission %>%
left_join(mysub, by = 'fullVisitorId')
mysub$PredictedLogRevenue = NULL
names(mysub) = names(submission)
But when I try to submit the file, I got the 'fail' message saying ...
ERROR: The value '8.893887e+17' in the key column 'fullVisitorId' has already been defined (Line 549026, Column 1)
ERROR: The value '8.895317e+18' in the key column 'fullVisitorId' has already been defined (Line 549126, Column 1)
ERROR: The value '8.895317e+18' in the key column 'fullVisitorId' has already been defined (Line 549127, Column 1)
Not just 3 lines, but 8 more lines like this.
I have no idea what I did wrong. I also checked other kernels but couldn't find the answer. Please...help!!
This issue was because fullVisitorId was numeric instead of character, so It dropped all the leading zeros. Therefore, using read.csv() with colClases argument or fread() can make it work.
I left this just because there could be someone else who are having the similar trouble like me
For creating submission dataframe, the easiest way is this
subm_df = pd.read_csv('../input/sample_submission.csv')
subm_df['PredictedLogRevenue'] = <your prediction array>
subm_df.to_csv('Subm_1.csv', index=False)
Noe this is assuming your sample_submission.csv has all fullVisitorId, which it usually does in Kaggle. Following this, I have never faced any issues.
The following code examples both result in this run-time error:
Unable to create a constant value of type 'System.Object'. Only primitive types or enumeration types are supported in this context.
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName).SingleOrDefault();
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName).FirstOrDefault();
Removing "SingleOrDefault()" (or FirstOrDefault) results in this compile-time error:
Cannot implicitly convert type 'System.Linq.IQueryable' to 'string'
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName);
I want to return the text from the field VenueName (it is in SQL Server DB with data type = nvarchar(75)). PropGroupID is currently unique (but that is not enforced). Suggestions?
You can get the value from:
var venueName = db.Venues
.Where(x => x.PropGroupId.Equals(propgroup))
.FirstOrDefault(x => x.VenueName);
About removing the "FirstOrDefault", you can get more information about lazy loading:
Entity Framework Loading Related
Entities
LINQ To Entities and Lazy
Loading
The use of the command "return" has always been bothering me since I started learning Python about a month ago(completely no programming background)
The function "double()" seems working fine without me have to reassign the value of the list used as an argument for the function and the value of the elements processed by the function would double as planned. Without the need to assign it outside the function.
However, the function "only_upper()" would require me to assign the list passed as argument through the function in order to see the effect of the function. I have to specify t=only_upper(t) outside of the function to see the effect.
So my question is this: Why are these two seemingly same function produces different result from the use of return?
Please explain in terms as plain as possible due to my inadequate programming skill. Thank you for your input.
def double(x):
for i in range(len(x)):
x[i] = int(x[i])*2
return x
x = [1, 2, 3]
print double(x)
def only_upper(t):
res = []
for s in t:
if s.isupper():
res.append(s)
t = res
return t
t = ['a', 'B', 'C']
t = only_upper(t)
print t
i am assuming that this is your first programming language hence the problem with understanding the return statement found in the functions.
The return in our functions is a means for us to literally return the values we want from that given 'formula' AKA function. For example,
def calculate(x,y):
multiply = x * y
return multiply
print calculate(5,5)
the function calculate defines the steps to be executed in a chunk. Then you ask yourself what values do you want to get from that chunk of steps. In my example, my function is to calculate the multiplied value from 2 values, hence returning the multiplied value. This can be shorten to the following
def calculate(x,y):
return x * y
print calculate(5,5)