Examples of java.io.PrintWriter.printf()

java.io.PrintWriter.printf()
Prints a formatted string. The behavior of this method is the same as this writer's format(String format, Object... args) method.
The method uses the default for the current JVM instance locale, as if it is specified by the Locale.getDefault() call. @param format A format string. @param args The arguments list. If there are more arguments than those specified by the format string, then the additional arguments are ignored. @return This writer. @throws IllegalFormatException If the format string is illegal or incompatible with the arguments or the arguments are less than those required by the format string or any other illegal situation. @throws NullPointerException If the given format is null.

    public static void writeWeighted(
            File f, WeightedGraph<? extends WeightedEdge> g) 
               throws IOException {
        PrintWriter pw = new PrintWriter(f);
        for (WeightedEdge e : g.edges()) {
            pw.printf("%d %d %f%n", e.from(), e.to(), e.weight());
        }
        pw.close();
    }


    public static void writeWeighted(

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                v1 = String.valueOf(e.from());
            String v2 = vertexLabels.lookup(e.to());
            if (v2 == null)
                v2 = String.valueOf(e.to());


            pw.printf("%s\t%s\t%f%n", v1, v2, e.weight());
        }
        pw.close();
    }
}

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            IntIterator iter = g.vertices().iterator();
            while (iter.hasNext()) {
                int v = iter.nextInt();
                String label = vertexLabels.lookup(v);
                if (label != null)
                    pw.printf("%d \"%s\"%n", v, label);
            }
        }
        
        // We will flatten all the parallel edges together, which requires
        // iterative over the edges to see how many unique compacted edges there

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                        fromWeight += e.weight();
                    else
                        toWeight += e.weight();
                }
                if (fromWeight != 0)
                    pw.printf("%d %d %f%n", v1, v2, fromWeight);
                if (toWeight != 0)
                    pw.printf("%d %d %f%n", v2, v1, toWeight);
            }
        }

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                        toWeight += e.weight();
                }
                if (fromWeight != 0)
                    pw.printf("%d %d %f%n", v1, v2, fromWeight);
                if (toWeight != 0)
                    pw.printf("%d %d %f%n", v2, v1, toWeight);
            }
        }
        
        pw.close();
    }

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                    // If the edge similarity is above the threshold, compute
                    // the kernel similarity for each new edge.
                    if (dataSimilarity > edgeSimThreshold) {
                        double edgeWeight = kernelSim.sim(row1, row2);
                        affMatrixWriter.printf("%d %d %f\n",i+1,j+1,edgeWeight);


                        // If the kernel metric is symmetric, just reuse the
                        // previously calculated edge weight.  Otherwise
                        // recalculate it.
                        edgeWeight = (kernelSim.isSymmetric())

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                        // previously calculated edge weight.  Otherwise
                        // recalculate it.
                        edgeWeight = (kernelSim.isSymmetric())
                            ? edgeWeight
                            : kernelSim.sim(row2, row1);
                        affMatrixWriter.printf("%d %d %f\n",j+1,i+1,edgeWeight);
                    }
                }
            }


            affMatrixWriter.close();

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                    // which to use.
                    double dataSimilarity = edgeSim.sim(curRow, otherRow);
                    
                    if (dataSimilarity > edgeSimThreshold) {
                        double edgeWeight = kernelSim.sim(curRow, otherRow);
                        affMatrixWriter.printf("%d %d %f\n",
                                               row+1, other+1, edgeWeight);


                        // If the kernel metric is symmetric, just reuse the
                        // previously calculated edge weight.  Otherwise
                        // recalculate it.

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                        // recalculate it.
                        edgeWeight = (kernelSim.isSymmetric())
                            ? edgeWeight
                            : kernelSim.sim(otherRow, curRow);


                        affMatrixWriter.printf("%d %d %f\n",
                                               other+1, row+1, edgeWeight);
                    }
                }
                curRow = nextRow;
                matrixIter.reset();

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                    // Clean and write the posting's content to the output file.
                    sb.append("\n");
                    String cleanedContent = processor.process(sb.toString());
                    System.out.println(awardFile.getAbsolutePath());
                    pw.printf("%s\n", cleanedContent);
                    br.close();
                }
            }
        }
        pw.close();

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