Someone please help me to integrate a_z as shown in the picture using Python2.7
Is there any predefined method to perform the action.Thank you
Try this:
http://docs.scipy.org/doc/scipy/reference/tutorial/integrate.html
for numerical integration.
In your particular example, a_z is a linear function of t and thus you dont need any numerical methods, you can do a symbolic integral and just compute the resultant function, which is much more efficient.
In fact, the solution is already printed there, so not sure what else you need to know?
Related
I'm integrating a project in GCP-Workflows with GCP-Admin, but I'm having trouble working with some data, when extracting a date it is delivered in this format: 2020-12-28T11: 20: 05.000Z, so I can't turn the string into int, and apparently there is no function in GCP like substring() either. I need to use the date with an IF, checking if it is greater or less than the reference.
How can I do this?
There is some lack of function implementation for now in Workflows. New ones are coming very soon. But I don't know if they will solve your problem
Anyway, with workflows, the correct pattern, if a built-in function isn't implemented, is to call an endpoint, for example a Cloud Function or a Cloud Run, which perform the transformation for you and return the expected result.
Quite boring to do, but don't hesitate to open feature request on the issues tracker product team is very reactive and love user feedbacks!
The Workflows standard library now includes a text module with functions for searching (including regular expressions), splitting, substrings and case transformations.
Is there a way to output the final tableau in python with docplex library? If not, is there a work around?
I want to use dual simplex method to solve linear programming problem with newly added constraints. So, I would need to access the final tableau to decide which variable to exit the basis, without having to re-solve the problem from scratch.
This sort of low level interaction cannot be done at the docplex level. In order to do this you can use Model.get_cplex() to get a reference to the underlying engine object. With this you can then get additional information. You can find the reference documentation for this class here. You probably want to look at the solution, solution.basis, solution.advanced properties. This should give you all the information you need.
Note that the engine works with an index oriented model in which every variable or constraint is just a number. You can convert docplex variable objects by using Model.get_var_by_index().
I also wonder whether you may want drop docplex and instead directly use the CPLEX Python API. You can find documentation of this here.
I'm using the SymPy function integral_steps to build a tool that, just like SymPy Gamma, reveals the integration steps when you ask it to integrate a function. My work-in-progress is available at https://lem.ma/1YH.
What I can't quite figure out is how to obtain the result of applying a particular rule. For example, consider the substitution rule
URule(u_var=_u, u_func=sin(x), constant=1, substep=ExpRule(base=E, exp=_u, context=exp(_u), symbol=_u), context=exp(sin(x))*cos(x), symbol=x)
The context field tells that the function being integrated is exp(sin(x))*cos(x) and that the rule uses a particular substitution - but what's the result of the integration so I can report to the user the same way SymPy Gamma does it. What I currently do is call integrate at every step, but that seems quite inefficient.
Perhaps there's an option that one can pass to integral_steps to make that information available?
SymPy Gamma is open source as SymPy itself. Looking at its module intsteps I see lines like
self.append("So, the result is: {}".format(
self.format_math(_manualintegrate(rule))))
So, the way to obtain the outcome of a rule from the rule is to call _manualintegrate(rule), which needs to be imported as
from sympy.integrals.manualintegrate import _manualintegrate
I imagine reading the rest of intsteps.py will be useful as well.
Is tf.py_func allowed at online prediction time?
If yes any examples of how to use it?
Does the answer change if I need to install additional pip packages?
My use-case: I work with text, I need to do word stemming (using porter stemmer), I know how to do it using python, tensorflow doesn't have Ops for that. I would like to use the same text processing at training and prediction time - thus I would like to encode it all into a tensorflow graph.
https://www.tensorflow.org/api_docs/python/tf/py_func comes with known limitations and I would like to know if it will work during training and online prediction before I invest more time into it.
Thanks
Unfortunately, no. Py_func can not be restored from a saved model. However, since your use case involves pre-processing, just invoke the py_func explicitly in all three (train, eval, serving) input functions. This won't work if the py_func is in the middle of your graph, but for stemming, it should work just fine.
I will first describe the problem and then what I currently look at, in terms of libraries.
In my application, we have a set of variables that are always available. For example: TOTAL_ITEMS, PRICE, CONTRACTS, ETC (we have around 15 of them). A clients of the application would like to have certain calculations performed and displayed, using those variables. Up until now, I have been constantly adding those calculations to the app. It's pain in the butt, and I would like to make it more generic by way of creating a template, where the user can specify a set of formulas that the application will parse and calculate.
Here is one case:
total_cost = CONTRACTS*PRICE*TOTAL_ITEMS
So, want to do something like that for the user to define in the template file:
total_cost = CONTRACTS*PRICE*TOTAL_ITEMS and some meta-date, like screen to display it on. Hence they will be specifying the formula with a screen. And the file will contain many formulas of this nature.
Right now, I am looking at two libraies: Spirit and matheval
Would anyone make recommendations what's better for this task, as well as references, examples, links?
Please let me know if the question is unclear, and I will try to further clarify it .
Thanks,
Sasha
If you have a fixed number of variables it may be a bit overkill to invoke a parser. Though Spirit is cool and I've been wanting to use it in a project.
I would probably just tokenize the string, make a map of your variables keyed by name (assuming all your variables are ints):
map<const char*,int*> vars;
vars["CONTRACTS"] = &contracts;
...
Then use a simple postfix calculator function to do the actual math.
Edit:
Looking at MathEval, it seems to do exactly what you want; set variables and evaluate mathematical functions using those variables. I'm not sure why you would want to create a solution at the level of a syntax parser. Do you have any requirements that MathEval does not fulfill?
Looks like it shouldn't be too hard to generate a simple parser using yacc and bison and integrate it into your code.
I don't know about matheval, but boost::spirit can do that for you pretty efficiently : see there.
If you're into template metaprogramming, you may want to have a look into Boost::Proto, but it will take some time to get started using it.