i am new with using pyomo and mindtpy solver, and have a very basic question.
how can i set the iteration limit for a subsolver in mindtpy? I want to set the iteration limit of ipopt, but it seems like it is not possible.
I treid the following code:
result = opt.solve(model, strategy='OA', init_strategy='FP', iteration_limit=100000, time_limit=36000, constraint_tolerance=10e-5, fp_iteration_limit=10000, fp_mipgap=10e-3, mip_solver='cplex', heuristic_nonconvex=True, mip_solver_args={'timelimit': 36000, 'warmstart': True}, mip_solver_mipgap=0.001, nlp_solver='ipopt', nlp_solver_args={'timelimit': 36000, 'maxiter': 10000}, tee=True, mip_solver_tee=True, nlp_solver_tee=True)
Setting the timelimit works and iteration limit not! I also tried it with iteration_limit instead of maxiter or max_iter.
I always get the error: ValueError: ProblemWriter_nl passed unrecognized io_options: maxiter = 10000
Thank you very much!
Kind regards
Related
I have written a pipeline in Snakemake. It's an ATAC-seq pipeline (bioinformatics pipeline to analyze genomics data from a specific experiment). Basically, until merging alignment step I use {sample_id} wildcard, to later switch to {sample} wildcard (merging two or more sample_ids into one sample).
working DAG here (for simplicity only one sample shown; orange and blue {sample_id}s are merged into one green {sample}
Tha all rule looks as follows:
configfile: "config.yaml"
SAMPLES_DICT = dict()
with open(config['SAMPLE_SHEET'], "r+") as fil:
next(fil)
for lin in fil.readlines():
row = lin.strip("\n").split("\t")
sample_id = row[0]
sample_name = row[1]
if sample_name in SAMPLES_DICT.keys():
SAMPLES_DICT[sample_name].append(sample_id)
else:
SAMPLES_DICT[sample_name] = [sample_id]
SAMPLES = list(SAMPLES_DICT.keys())
SAMPLE_IDS = [sample_id for sample in SAMPLES_DICT.values() for sample_id in sample]
rule all:
input:
# FASTQC output for RAW reads
expand(os.path.join(config['FASTQC'], '{sample_id}_R{read}_fastqc.zip'),
sample_id = SAMPLE_IDS,
read = ['1', '2']),
# Trimming
expand(os.path.join(config['TRIMMED'],
'{sample_id}_R{read}_val_{read}.fq.gz'),
sample_id = SAMPLE_IDS,
read = ['1', '2']),
# Alignment
expand(os.path.join(config['ALIGNMENT'], '{sample_id}_sorted.bam'),
sample_id = SAMPLE_IDS),
# Merging
expand(os.path.join(config['ALIGNMENT'], '{sample}_sorted_merged.bam'),
sample = SAMPLES),
# Marking Duplicates
expand(os.path.join(config['ALIGNMENT'], '{sample}_sorted_md.bam'),
sample = SAMPLES),
# Filtering
expand(os.path.join(config['FILTERED'],
'{sample}.bam'),
sample = SAMPLES),
expand(os.path.join(config['FILTERED'],
'{sample}.bam.bai'),
sample = SAMPLES),
# multiqc report
"multiqc_report.html"
message:
'\n#################### ATAC-seq pipeline #####################\n'
'Running all necessary rules to produce complete output.\n'
'############################################################'
I know it's too messy, I should only leave the necessary bits, but here my understanding of snakemake fails cause I don't know what I have to keep and what I should delete.
This is working, to my knowledge exactly as I want.
However, I added a rule:
rule hmmratac:
input:
bam = os.path.join(config['FILTERED'], '{sample}.bam'),
index = os.path.join(config['FILTERED'], '{sample}.bam.bai')
output:
model = os.path.join(config['HMMRATAC'], '{sample}.model'),
gappedPeak = os.path.join(config['HMMRATAC'], '{sample}_peaks.gappedPeak'),
summits = os.path.join(config['HMMRATAC'], '{sample}_summits.bed'),
states = os.path.join(config['HMMRATAC'], '{sample}.bedgraph'),
logs = os.path.join(config['HMMRATAC'], '{sample}.log'),
sample_name = '{sample}'
log:
os.path.join(config['LOGS'], 'hmmratac', '{sample}.log')
params:
genomes = config['GENOMES'],
blacklisted = config['BLACKLIST']
resources:
mem_mb = 32000
message:
'\n######################### Peak calling ########################\n'
'Peak calling for {output.sample_name}\n.'
'############################################################'
shell:
'HMMRATAC -Xms2g -Xmx{resources.mem_mb}m '
'--bam {input.bam} --index {input.index} '
'--genome {params.genome} --blacklist {params.blacklisted} '
'--output {output.sample_name} --bedgraph true &> {log}'
And into the rule all, after filtering, before multiqc, I added:
# Peak calling
expand(os.path.join(config['HMMRATAC'], '{sample}.model'),
sample = SAMPLES),
Relevant config.yaml fragments:
# Path to blacklisted regions
BLACKLIST: "/mnt/data/.../hg38.blacklist.bed"
# Path to chromosome sizes
GENOMES: "/mnt/data/.../hg38_sizes.genome"
# Path to filtered alignment
FILTERED: "alignment/filtered"
# Path to peaks
HMMRATAC: "peaks/hmmratac"
This is the error* I get (It goes on for every input and output of the rule). *Technically it's a warning but it halts execution of snakemake so I am calling it an error.
File path alignment/filtered//mnt/data/.../hg38.blacklist.bed.bam contains double '/'. This is likely unintended. It can also lead to inconsistent results of the file-matching approach used by Snakemake.
WARNING:snakemake.logging:File path alignment/filtered//mnt/data/.../hg38.blacklist.bed.bam contains double '/'. This is likely unintended. It can also lead to inconsistent results of the file-matching approach used by Snakemake.
It isn't actually ... - I just didn't feel safe providing an absolute path here.
For a couple of days, I have struggled with this error. Looked through the documentation, listened to the introduction. I understand that the above description is far from perfect (it is huge bc I don't even know how to work it down to provide minimal reproducible example...) but I am desperate and hope you can be patient with me.
Any suggestions as to how to google it, where to look for an error would be much appreciated.
Technically it's a warning but it halts execution of snakemake so I am calling it an error.
It would be useful to post the logs from snakemake to see if snakemake terminated with an error and if so what error.
However, in addition to Eric C.'s suggestion to use wildcards.sample instead of {sample} as file name, I think that this is quite suspicious:
alignment/filtered//mnt/data/.../hg38.blacklist.bed.bam
/mnt/ is usually at the root of the file system and you are prepending to it a relative path (alignment/filtered). Are you sure it is correct?
I am going to create end to end(e2e) test using protractor with jasmine and angular 6. I have written some test cases almost 10 cases. That's all working fine, but always some cases become fails. And its failed because of jasmine timeout. I have configure timeout value like below. But I am not getting consistant result. sometimes a test cases is success but at next run it will goes to success or fail. I have searched on google but I have not found any useful solution.
I have defined some common properties for wait
waitForElement(element: ElementFinder){
browser.waitForAngularEnabled(false);
browser.wait(() => element.isPresent(), 100000, 'timeout: ');
}
waitForUrl(url: string){
browser.wait(() => protractor.ExpectedConditions.urlContains(url), 100000, 'timeout')
}
And protractor.conf.js file I have defined that
jasmineNodeOpts: {
showColors: true,
includeStackTrace: true,
defaultTimeoutInterval: 20000,
print: function () {
}
}
I am getting below error
- Error: Timeout - Async callback was not invoked within timeout specified by jasmine.DEFAULT_TIMEOUT_INTERVAL.
- Failed: stale element reference: element is not attached to the page document
(Session info: chrome=76.0.3809.100)
(Driver info: chromedriver=76.0.3809.12 (220b19a666554bdcac56dff9ffd44c300842c933-refs/branch-heads/3809#{#83}),platform=Windows NT 10.0.17134 x86_64)
I have got the solution:
I have configured waiting timeout 100000 ms for individual element find where whole script timeout was 20000 ms. So I have follow below process:
Keep full spec timeout below than sum of all elements find timeouts. I have configured defaultTimeoutInterval at jasmineNodeOpts greater than sum of value for all test cases timeout. And then add a large value to allScriptsTimeout: 2000000 inside of export.config. Its resolved my problem.
NB: I gave this answer because I think it may help others who will face this kind of problem.
I am trying to do a hyperparameter tuning using GridSearchCV on XGBoost.But, I'm getting the following error.
/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.if diff:
This keeps on running forever. Given below is the code.
classifier = xgb.XGBClassifier()
from sklearn.grid_search import GridSearchCV
n_estimators=[10,50,100,150,200,250,300]
max_depth=[2,3,4,5,6,7,8,9,10]
learning_rate=[0.1,0.01,0.09,0.08,0.07,0.001]
colsample_bytree=[0.5,0.6,0.7,0.8,0.9]
min_child_weight=[1,2,3,4,5,6,7,8,9,10]
gamma=[0.001,0.01,0.1,0.2,0.3,0.4,0.5,1]
subsample=[0.5,0.6,0.7,0.8,0.9]
param_grid=dict(n_estimators=n_estimators,max_depth=max_depth,learning_rate=learning_rate,colsample_bytree=colsample_bytree,min_child_weight=min_child_weight,gamma=gamma,subsample=subsample)
grid = GridSearchCV(classifier, param_grid, cv=10, scoring='accuracy')
grid.fit(X, Y)
grid.grid_scores_
print(grid.best_score_)
print(grid.best_params_)
print(grid.best_estimator_)
# Predicting the Test set results
Y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm = confusion_matrix(Y_test, Y_pred)
I am using python3.5, XGBOOT and gridsearch library has already been preloaded. I am running this on google collaboratory.
Please suggest what is going wrong ?
When I try to solve this first ode by using Sympy as it shows below:
import sympy
y = sympy.Function('y')
t = sympy.Symbol('t')
ode = sympy.Eq(y(t).diff(t),(1/y(t))*sympy.sin(t))
sol = sympy.dsolve(ode,y(t))
csol=sol.subs([(t,0),(y(0),-4)]) # the I.C. is y(0) = 1
ode_sol= sol.subs([(csol.rhs,csol.lhs)])
print(sympy.pprint(ode_sol))
It gives me this error:
Traceback (most recent call last):
File "C:/Users/Mohammed Alotaibi/AppData/Local/Programs/Python/Python35/ODE2.py", line 26, in <module>
csol=sol.subs([(t,0),(y(0),-4)]) # the I.C. is y(0) = 1
AttributeError: 'list' object has no attribute 'subs'
Your problem is that this ODE does not have a unique solution. Thus it returns a list of solution, which you can find out from the error message and by printing sol.
Do the evaluation in a loop,
for psol in sol:
csol = psol.subs([(t,0),(y(0),-4)]);
ode_sol = psol.subs([(csol.rhs,csol.lhs)]);
print(sympy.pprint(ode_sol))
to find the next error, that substituting does not solve for the constant. What works is to define C1=sympy.Symbol("C1") and using
ode_sol= psol.subs([(C1, sympy.solve(csol)[0])]);
but this still feels hacky. Or better to avoid error messages for the unsolvability of the second case:
C1=sympy.Symbol("C1");
for psol in sol:
csol = psol.subs([(t,0),(y(0),-4)]);
for cc1 in sympy.solve(csol):
ode_sol= psol.subs([(C1, cc1)]);
print(sympy.pprint(ode_sol))
I was successful using Runningvalue here:
=FormatPercent(Runningvalue(Count(Fields!id.Value),Sum,"Tablix1")/
Count(Fields!id.Value,"Tablix1"),)
But when I try the next step to only capture the status "A"'s and determine the runningvalue
=Runningvalue(Sum(iif(Fields!status.Value = "A", 1, 0),Sum,"Tablix1")
/ Count(Fields!status.Value, "Tablix1"),)
I'm getting an error: "Has an incorrect number of parameters for the function 'Runningvalue'. I've tried this a number of ways and can't get it to work.
The following expression run without error at least:
=Runningvalue(iif(Fields!status.Value = "A", 1, 0),Sum,"Tablix1")
/ Count(Fields!status.Value, "Tablix1")
There were a few issues with extra commas/parentheses and key words.