how to plott several curves after while loop in function - python-3.x

def a(t, A, B, C, At, Bt):
while:
calculations
return t, A, B, C, At, Bt
print(def(t, A, B, C, At, Bt))
I return several numpy.arrays. and wanna plot them in the form
B, = plt.plot(t, B)
C, = plt.plot(t, C)
plt.legend(handles=[ B, C, A],
labels=[ 'B', 'C', 'A'])

Use the object-oriented interface to matplotlib:
from matplotlib import pyplot
t, A, B, C, At, Bt = a(t, A, B, C, At, Bt)
fig, ax = pyplot.subplots()
for array, label in zip([A, B, C], ['A', 'B', 'C']):
ax.plot(t, array, label=label)
ax.legend()

Related

ES6 multiple assignments/updates in one line [duplicate]

Can anyone explain, why the following happens with ES6 array destructuring?
let a, b, c
[a, b] = ['A', 'B']
[b, c] = ['BB', 'C']
console.log(`a=${a} b=${b} c=${c}`)
// expected: a=A b=BB c=C
// actual: a=BB b=C c=undefined
http://codepen.io/ronkot/pen/WxRqXg?editors=0011
As others have said, you're missing semicolons. But…
Can anyone explain?
There are no semicolons automatically inserted between your lines to separate the "two" statements, because it is valid as a single statement. It is parsed (and evaluated) as
let a = undefined, b = undefined, c = undefined;
[a, b] = (['A', 'B']
[(b, c)] = ['BB', 'C']);
console.log(`a=${a} b=${b} c=${c}`);
wherein
[a, b] = …; is a destructuring assignment as expected
(… = ['BB', 'C']) is an assignment expression assigning the array to the left hand side, and evaluating to the array
['A', 'B'][…] is a property reference on an array literal
(b, c) is using the comma operator, evaluating to c (which is undefined)
If you want to omit semicolons and let them be automatically inserted where ever possible needed, you will need to put one at the start of every line that begins with (, [, /, +, - or `.
You've fallen into a trap of line wrapping and automatic semicolon insertion rules in JavaScript.
Take this example:
let x = [1, 2]
[2, 1]
It's the interpreted as:
let x = [1, 2][2, 1] // === [1, 2][(2, 1)] === [1, 2][1] === 2
That weird [(2, 1)] thing above is related to how Comma Operator works.
Thus, your example:
let a, b, c
[a, b] = ['A', 'B']
[b, c] = ['BB', 'C']
console.log(`a=${a} b=${b} c=${c}`)
Is interpreted as:
let a, b, c
[a, b] = ['A', 'B'][b, c] = ['BB', 'C']
console.log(`a=${a} b=${b} c=${c}`)
Now, if you insert a semicolon, it will work as you intended:
let a, b, c
[a, b] = ['A', 'B']; // note a semicolon here
[b, c] = ['BB', 'C']
console.log(`a=${a} b=${b} c=${c}`)
Also, it's a good idea to check your code by pasting it into Babel repl to see the generated output:
'use strict';
var a = void 0,
b = void 0,
c = void 0;
var _ref = ['A', 'B'][(b, c)] = ['BB', 'C'];
a = _ref[0];
b = _ref[1];
console.log('a=' + a + ' b=' + b + ' c=' + c);
I believe you have forgotten the line breaks ';'. Below is the corrected code. Please try:
let a,b,c
[a, b] = ['A', 'B'];
[b, c] = ['BB', 'C'];
console.log(`a=${a} b=${b} c=${c}`)
let a, b, c
[a, b] = ['A', 'B']***;***
[b, c] = ['BB', 'C']
console.log(`a=${a} b=${b} c=${c}`)
console: a=A b=BB c=C

Mixing non-overlapping everygrams in order

I'm looking for a method to generate sequences from every-grams up to length n that match an input sentence:
Given a sentence: "Break this into sequences" and n = 3
I want to create the sequences:
("Break", "this", "into", "sequences")
("Break", "this", "into sequences")
("Break", "this into", "sequences")
("Break this", "into", "sequences")
("Break this", "into sequences")
("Break", "this into sequences")
("Break this into", "sequences")
nltk has the everygram package, but I'm not quite sure how I'd use it toward my goal.
I've tried adapting the problem to focus on characters for simplicity, i.e.,
It may be helpful to consider these as character-grams (and, as rici suggested, spacing out characters [with and without spacing shown for clarity]):
abcd goes to:
(a, b, c, d) (a, b, c, d)
(a, b, c d) (a, b, cd)
(a, b c, d) (a, bc, d)
(a b, c, d) (ab, c, d)
(a b, c d) (ab, cd)
(a, b c d) (a, bcd)
(a b c, d) (abc, d)
For clarity, this should generalize for any length, given a n as the maximum-sized n-gram; so, for abcde with n=3 we'd have:
(a, b, c, d, e) (a, b, c, d, e)
(a, b, c, d e) (a, b, c, de)
(a, b, c d, e) (a, b, cd, e)
(a, b c, d e) (a, bc, d, e)
(a b, c, d, e) (ab, c, d, e)
(a, b c, d e) (a, bc, de)
(a b, c, d e) (ab, c, de)
(a b, c d, e) (ab, cd, e)
(a, b, c d e) (a, b, cde)
(a, b c d, e) (a, bcd, e)
(a b c, d, e) (abc, d, e)
(a b, c d e) (ab, cde)
(a b c, d e) (abc, de)
I'm thinking I may need to generate a grammar, something like:
exp ::= ABC, d | a, BCD
ABC ::= AB, c | A, BC
BCD ::= BC, d | b, CD
AB ::= A, b | a, B
BC ::= B, c | b, C
CD ::= C, d | c, D
A ::= a
B ::= b
C ::= c
D ::= d
and find all parses of the sentence, but certainly there must be a procedural way to go about this?
Maybe it would be helpful to space your example out a bit:
(a , b , c , d)
(a , b , c d)
(a , b c , d)
(a b , c , d)
(a b , c d)
(a , b c d)
(a b c , d)
(a b c d) # added for completeness
Looking at that, it's evident that what differentiates the rows is the presence or absence of commas, a typical binary choice. There are three places a comma could go, so there are eight possibilities, corresponding to the eight binary numbers of three digits.
The easiest way to list these possibilities is to count from 0 0 0 to 1 1 1.
For your modified question, in which there is a maximum length of a part, one simple recursive solution in Python is:
def kgram(k, v):
'Generate all partitions of v with parts no larger than k'
def helper(sfx, m):
if m == 0: yield sfx
else:
for i in range(1, min(k, m)+1):
yield from helper([v[m-i:m]]+sfx, m-i)
yield from helper([], len(v))
Here's a quick test:
>>> for p in gram(3, 'one two three four five'.split()): print(p)
...
[['one'], ['two'], ['three'], ['four'], ['five']]
[['one', 'two'], ['three'], ['four'], ['five']]
[['one'], ['two', 'three'], ['four'], ['five']]
[['one', 'two', 'three'], ['four'], ['five']]
[['one'], ['two'], ['three', 'four'], ['five']]
[['one', 'two'], ['three', 'four'], ['five']]
[['one'], ['two', 'three', 'four'], ['five']]
[['one'], ['two'], ['three'], ['four', 'five']]
[['one', 'two'], ['three'], ['four', 'five']]
[['one'], ['two', 'three'], ['four', 'five']]
[['one', 'two', 'three'], ['four', 'five']]
[['one'], ['two'], ['three', 'four', 'five']]
[['one', 'two'], ['three', 'four', 'five']]

How to represent a flat graph in Java Spark using Dataset

Given a Dataset with two columns such as:
FatherNode, ChildNode
A, B
A, C
B, D
B, F
C, G
H, I
H, L
M, I
M, B
F, J
Z, K
I want to build a new Dataset that represents a Flat Graph, i.e. a representation of the all possible destinations of each node, so, in this example, the new Dataset should be:
Node, PossibleDestinations
A, [B, C, D, F, J]
B, [D, F, J]
C, [G]
H, [I, L]
M, [I, B, D, F, J]
F, [J]
Z, [K]
For example, A could reach B, C, D, F and J: doesn't matter the path.
My simple code (implemented) is:
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import static org.apache.spark.sql.functions.array;
import static org.apache.spark.sql.functions.col;
public class FlatGraph {
public static void main(String[] args) {
SparkSession spark = SparkSession.builder().appName("Flat Graph").getOrCreate();
Dataset<Row> csvData = spark.read().option("header", "true").csv("data.csv").cache();
csvData.show();
Dataset<Row> flatGraph = [...]; // What operations could be performed here?
flatGraph.show();
spark.stop();
}
}

How to make X number of random sets of 3 from pandas column?

I have a dataframe column that looks like this (roughly 200 rows):
col1
a
b
c
d
e
f
I want to create a new dataframe with one column and 15 sets of 3 random combinations of the items in the pandas column. for example:
new_df
combinations:
(a,b,c)
(a,c,d)
(a,d,c)
(b,a,d)
(d,a,c)
(a,d,f)
(e,a,f)
(a,f,e)
(b,e,f)
(f,b,e)
(c,b,e)
(b,e,a)
(a,e,f)
(e,f,a)
Currently the code I have creates a combination of every possible combination and runs out of memory when I try to append the results to another dataframe:
import pandas as pd
from itertools import permutations
df = pd.read_csv('')
combo = df['col1'].tolist()
perm = permutations(combo,3)
combinations = pd.DataFrame(columns=['combinations'])
list_ = []
for i in list(perm):
combinations['combinations'] = i
list_.append(i)
How do I stop the sets of random combinations to stop at any X number of set or in this case 15 combinations of 3?
The reason your code runs out of memory is specifically because of the part where you call list(perm). doing this will generate EVERY permutation possible. So when you do
for i in list(perm):
...
You're telling python to create a list of all permutations, then try to iterate over that list. Instead, if you iterate over the generator that calling permutations creates (e.g. for i in perm: instead of for i in list(perm):), you can simply iterate over each permutation without storing them all into memory at once. So if you break your for loop after it loops 15 times, you can achieve your desired result.
However, since we're using itertools, we can vastly simplify that logic using islice to do the work of getting the first 15 without explicitly writing a for-loop and breaking at the 15th iteration:
import pandas as pd
from itertools import permutations, islice
# df = pd.read_csv('')
# combo = df['col1'].tolist()
combo = list("abcefg")
perm_generator = permutations(combo,3)
# get first 15 permutations without running the generator
first_15_perms = islice(perm_generator, 15)
# Store the first 15 permutations into a Series object
series_perms = pd.Series(list(first_15_perms), name="permutations")
print(series_perms)
0 (a, b, c)
1 (a, b, e)
2 (a, b, f)
3 (a, b, g)
4 (a, c, b)
5 (a, c, e)
6 (a, c, f)
7 (a, c, g)
8 (a, e, b)
9 (a, e, c)
10 (a, e, f)
11 (a, e, g)
12 (a, f, b)
13 (a, f, c)
14 (a, f, e)
Name: permutations, dtype: object
If you want this as a single column in a DataFrame you can use the to_frame() method:
df_perms = series_perms.to_frame()
print(df_perms)
permutations
0 (a, b, c)
1 (a, b, e)
2 (a, b, f)
3 (a, b, g)
4 (a, c, b)
5 (a, c, e)
6 (a, c, f)
7 (a, c, g)
8 (a, e, b)
9 (a, e, c)
10 (a, e, f)
11 (a, e, g)
12 (a, f, b)
13 (a, f, c)
14 (a, f, e)
While not quite as elegant as the previous answers, If you truly want to create a random sampling of values, not just the first you could also do something along the lines of the following:
def newFrame(df: pd.DataFrame, srccol: int, cmbs: int, rows: int) -> pd.DataFrame:
il = df[srccol].values.tolist()
nw_df = pd.DataFrame()
data = []
for r in range(rows):
rd =[]
for ri in range(cmbs):
rd.append(rnd.choice(il))
data.append(tuple(rd))
nw_df['Combinations'] = data
return nw_df
Which when passed a a df as shown in your example in the form of:
new_df = newFrame(df, 0, 3, 15)
Produces:
Combinations
0 (a, f, e)
1 (a, d, f)
2 (b, c, d)
3 (a, a, d)
4 (f, b, c)
5 (e, b, b)
6 (e, e, d)
7 (c, f, f)
8 (f, e, b)
9 (d, c, e)

cannot output accumilated list of tau prolog answers

I am using the Tau Prolog library in my project and it has been working fine till I tried this.
I am attempting to output multiple schedules and their corresponding extra hours (the context is not relevent here).
Here is the output in the console when I use session.answers( x => console.log( pl.format_answer(x) ) );
// Query the goal
session.query("getSchedules(123,Schedule,ExtraHours).");
// Show answers
session.answers(x => console.log(pl.format_answer(x)));
CONSOLE:
Schedule = [a, b, c, d, e, f, m, g], ExtraHours = 0 ;
Schedule = [a, b, c, d, e, f, j, k], ExtraHours = 0 ;
Schedule = [a, b, c, d, e, f, j, x], ExtraHours = 0 ;
Schedule = [a, b, c, d, e, f, j, g], ExtraHours = -2 ;
Schedule = [a, b, c, d, e, f, k, x], ExtraHours = 0 ;
Schedule = [a, b, c, d, e, f, k, g], ExtraHours = -2 ;
Schedule = [a, b, c, d, e, f, x, g], ExtraHours = -2 ;
false.
I am trying to get all these schedules in 1 list but whenever I try to accumulate the results in a global variable, the resulting list only has the 1st schedule. Does anyone know how I can get a list with all the schedules?

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