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Histogram Class ReferenceFlexible statistical analyses of the values in any AForm object. More... #include <histogram.h> Visible Fields
Macro Constants
Routines
Detailed DescriptionHistogram objects capture the distribution of values in an Array, Slice, or Frame, i.e. AForm. From a given histogram one can compute any of a variety of statistics about the values in an array form, and to compute foreground/background thresholds that are a function of its distribution. Almost all of the fields of a histogram are visibile to a user, but should only be used in a read-only fashion. It is not safe for a user to change any of the visible fields as doing so may create a semantic conflict with the private fields. A histogram can be read from and written to a file. A histogram is created (a) for an AForm by calling Histogram_Array, (b) for a Region, Partition P_Vertex, or Level_Tree Level_Set by calling Histogram_Region, Histogram_P_Vertex, or Histogram_Level_Set, respectively, or (c) by reforming the bin range of an existing histogram with Histogram_Slice. An initially empty histogram can also be created directly by calling Make_Histogram. Every bin boundary corresponds to a value which in turn corresponds to a percentile of the data points greater than said value. There are conversion routines to map between bins, values, and percentiles (Bin2Value, Value2Bin, Bin2Percentile, Percentile2Bin, Value2Percentile, Percentile2Value). The routine Print_Histogram provides a flexible set of options for producing an ASCII display of a histogram using the set of flags given in the Macro Constants section. Histograms, once computed, provide a convenient way to deliver statistics about the distribution of values in the array form or region the histogram was computed from. For example, if one builds a 256 bin histogram for a UINT8_TYPE array form, then thereafter one can deliver the mean, standard deviation, and any central moment with Histogram_Mean, Histogram_Sigma, Histogram_Variance, and Histogram_Central_Moment in O(nbins) time versus time proportional to the number of elements in the array form. Of course, the accuracy of a statistic versus that computed over the set of values in the array, depends on the bin size and the total number of elements. In the example above the statistics are perfectly accurate as the bin size is 1. But if a histogram of 256 bins were builts for a UINT16_TYPE array form, then each bin covers 256 values and depending on the distribution of values in the array, the computed statistic could deviate from the true value. As long as the total number of data points is large, the accuracy of distributional statistics is generally acceptable. In addition to distributional statistics, one can compute entropy, and the cross entropy and relative entropy between two histograms (Histogram_Entropy, Histogram_Cross_Entropy, Histogram_Relative_Entropy). The class also currently offers three distribution-based methods for computing a foreground/background threshold (Otsu_Threshold, Triangle_Threshold, Intermeans_Threshold). A common scenario is to use a histogram as the means to compute one or more of the above quantities with respect to a Frame that is passed over every element in an array, implying that a histogram of the same type and range is needed thousands if not millions of times. Rather than create and free a histogram for each frame placement, the routine Histagain_Array allows one to accumulate the counts for a given array form into the bins of an existing histogram. Note carefully that the counts accumulate. To get a histogram for just the object at hand, one must explicitly reset the buckets to zero with Empty_Histogram. Please see the example included with the description of this routine. Moreover, one can also refill a histogram with the pixel values in a Region, Partition P_Vertex, or Level_Tree Level_Set by calling Histagain_Region, Histagain_P_Vertex, or Histagain_Level_Set, respectively. Visible Fields Documentation
A histogram can be over values of any of the three Value_Kinds. This field specifies which one.
The number of bins in the histogram.
The width or size of each bin in the histogram
The offset or lower boundary of the first bin, bin 0, in the histogram. Thus, the range covered by bin b is [offset+b*binsize,offset+(b+1)*binsize).
The total number of data points in the histogram or equivalently the sum of all the counts.
A vector of nbins counts for each bin 0 to nbins−1, i.e. counts[b] is the number of data points whose value is int the range covered by bin b. Routine Documentation
Return the lower border of bin b, i.e. offset + b*binsize. The parameter b does not need to be between 0 and nbins−1 in which case the return value will not be in the domain of the histogram.
Return the bin number b that contains the value v, i.e. maxb s.t. Bin2Value(b) ≤ v. The parameter v does not need to be in the domain of the histogram, in which case the return value will not be a bin number between 0 and nbins−1.
Return the percent of values in the histogram in bins b and higher, i.e. Σc≥b counts[c] / total. The parameter b does not need to be between 0 and nbins−1 but the return value will always be between 0 and 1.
Return the larget bin number b for which the tail of the histogram starting at b contains more than fraction f of the data points, i.e. maxb s.t. Bin2Percentile(b) ≥ f. The parameter f must be between 0 and 1.
Return the percentile of values in the histogram that are estimated to be not less than v, i.e. Bin2Percentile(b) − (v−b)*counts[b]/total where b = Value2Bin(v). Note that linear interpolation is used to estimate the number of values in bin b not less than v.
Return the value for which the tail of the histogram greater than v contains fraction f of the data points, i.e. maxb s.t. Value2Percentile(v) ≥ f.
Generate a histogram of the given kind with nbins bins of size binsize covering the range starting at offset. The histogram is initialized to be empty, i.e. total is zero as is every element of counts.
Empty all buckets of the histogram, i.e. set all buckets to 0.
Generate a histogram of AForm a with nbins of width binsize where the first bin's lower boundary is offset (see field descriptor for offset). The type of values given for binsize and offset should be congruent with the type of a. When nbins or binsize or both are zero, then the value of the parameter(s) with value 0, and the value of offset are selected according to the rules given in the following table, where the range of values in a is assumed to be [min,max]:
Note that when either of the two parameters is 0 then the value provided for offset is ignored as it is irrelevant. Moreover, in the case where a is of one of the small integer types -- UINT8_TYPE, UINT16_TYPE, INT8_TYPE, INT16_TYPE -- if one specifies nbins as the number of values in the range of the type, and offset as the smallest value in the range of the type, and binsize as 1, then the histogram module is smart enough to know that it does not need to check that values are in range, and consequently fills such histograms with the efficiency of hand-tailored code. Concretely, the calls below make for very efficient histogram constructions: Histogram_Array(a,256,VALU(1),VALU(0)) // for UINT8_TYPE Histogram_Array(a,0x10000,VALU(1),VALU(0)) // for UINT16_TYPE Histogram_Array(a,256,VALI(1),VALI(-128)) // for INT8_TYPE Histogram_Array(a,0x10000,VALI(1),VALI(0xffff)) // for INT16_TYPE
Generate a histogram of the pixel values in the respective Region, P_Vertex region v of Partition p, or Level_Set r of Level_Tree t. The interpretation of the arguments bins, binsize, and offset are exactly as for Histogram_Array above.
Accumulates into the bins of histogram h, the counts for the values in a. One must explicitly reset the histogram with Empty_Histogram if one wants just the histogram of a. The type of array a must be compatible with the type of h, and one should only call this routine with clip set to 0 (false) if one is certain that the values in a are within the range of the domain covered by h, i.e. [offset,offset+nbins*binsize]. Otherwise one must call it with clip set to true, in which case out of range values will be detected and clipped (and therefore the routine will not refill the histogram as efficiently). The idea of this routine is to allow one to more efficiently accumulate thousands of histograms, over for example frame windows, where the domain and type of the histogram are fixed. This saves the expense of creating and freeing every histogram. For example, suppose A is a 3D, UINT8_TYPE array. The code snippet below computes the entropy in a 5x5x5 window centered at every pixel of A: Frame *f; Histogram *h; Indx_Type p; double end; h = Make_Histogram(UVAL,256,VALU(1),VALU(0)); f = Make_Frame(A,Coord3(5,5,5),Coord3(2,2,2)); Place_Frame(f,0); for (p = 0; p < A->size; p++) { Histagain_Array(Empty_Histogram(h),f,0); ent = Histogram_Entropy(h); // ... do something with ent = the entropy in a 5x5x5 shape about p Move_Frame_Forward(f); } Free_Frame(f); Free_Histogram(h);
Accumulate into the bins of histogram h, the counts for pixels in the respective Region, P_Vertex region v of Partition p, or Level_Set r of Level_Tree t. Note carefully, that you must explicitly reset the histogram with Empty_Histogram if you want just the histogram of the given object. The interpretation of the argument clip is exactly as for Histagain_Array above.
Generate a histogram based on the histogram h consisting of the bins whose indices are in the interval [min,max-1]. min and max need not be between 0 and h->nbins but it must be that min < max. If min < 0 or max > h->nbins then the new histogram's domain will be expanded as necessary to cover the implied range of [Bin2Value(min),Bin2Value(max)].
Return the requested statistics for the histogram h. Histogram_Mean returns the mean or average. Histogram_Sigma returns the standard deviation. Histogram_Variance returns the variance, or square of the standard deviation. Histogram_Central_Moment returns the nth moment of the distribution, i.e. Σi (xi - μ)n where μ is the mean of the data series { x1, x2, ... xN }. Note carefully, that the accuracy of a statistic computed from the histogram in relation to the same statistic computed directly over the series of values in the AForm from which the histogram was derived, depends on the binning of values into the histogram. The general rule of thumb is that the smaller the binsize the more accurate the statistic.
Histogram_Entropy returns the entropy of the distribution of h, i.e. − Σb p(b) log2 p(b) where p(b) is counts[b]/total for each bin b. The cross entropy between two historams, h and g, returned by Histogram_Cross_Entropy is − Σb p(b) log2 q(b) where q(b), analagous to p(b), is the distribution for g. The histograms h and g must have the same binsize and while their offsets can be different, the difference must be a multiple of the bin size. Finally, Histogram_Relative_Entropy returns the relative entropy between h and g, i.e. − Σb p(b) log2 p(b)/q(b). Note carefully, that the accuracy of a statistic computed from the histogram in relation to the same statistic computed directly over the series of values in the AForm from which the histogram was derived, depends on the binning of values into the histogram. The general rule of thumb is that the smaller the binsize the more accurate the statistic.
Return the Otsu threshold (IEEE Trans. Sys., Man, & Cybernetics, 9, 1 (1979), 62-66) for the AForm over which the histogram h was built. The routine returns the index of the smallest bucket that should be considered foreground as the threshold is only accurate to the nearest multiple of the binsize of the histogram. Use Bin2Value in order to convert the index into a threshold value. In brief, the method picks the threshold that produces the greatest inter-class variance between the induced foreground and background classes.
Apply the "triangle method" of Zack, Rogers, and Latt (J. Histochem. Cytochem. 25, 7 (1977), 741-753) to compute and return the smallest bin index that should be considered foreground in the image array the histogram was derived from. Use Bin2Value in order to convert the index into a threshold value. In brief, the method converges to the threshold that is half-way between the means of the foreground and background classes. Initially the threshold is placed at the half way between the min and the max value in the histogram.
Return the inter-means threshold (IEEE. Trans. on Cybernetics (1978) 630-632 by Ridlar and Calvard) for the image array the histogram was derived from, to the nearest bin index. Use Bin2Value in order to convert the index into a threshold value. In brief, the method picks the threshold whose bin top is the furthest from the line that runs from the top of the bin with the highest count to the empty bin one greater than the non-empty bin with the greatest index.
Print an ascii display of histogram h on stream output indented by indent spaces. If binsize is not 0 then the histogram will be displayed in bins of the given size, with the bin boundaries being multiples of binsize. If binsize is not a multiple of the histogram's binsize (h->binsize), then the counts of spanning bins in the underlying histogram are interpolated. The parameter flag is the bitwise or of one or more of the constants introduced at the top of this page and that determine what is displayed and how it is displayed as outlined in the following table:
As an example, suppose A is a UINT8_TYPE array with a million elements that are randomly generated numbers between 1 and 6 inclusive. Suppose that we make a histogram h with the call Make_Array(A,8,VALU(1),VALU(0)). Then calling Print_Histogram with the flags BIN_COUNT| CUMULATIVE_COUNT|CUMULATIVE_PERCENT and binsize set to 0 (i.e. no effect), produces the following output: 7: 0 0 0.0% 6:<PHONE_NUMBER>78 16.7% 5:<PHONE_NUMBER>16 33.4% 4:<PHONE_NUMBER>07 50.0% 3:<PHONE_NUMBER>36 66.7% 2:<PHONE_NUMBER>53 83.3% 1:<PHONE_NUMBER>000 100.0% 0: 0 1000000 100.0% Calling Print_Histogram with the flags CUMULATIVE_COUNT|ASCENDING_HGRAM|CLIP_HGRAM and binsize set to 0 (i.e. no effect), on the same histogram would produce: 1: 166847 2: 333364 3: 499693 4: 666284 5: 833322 6: 1000000 As another example, suppose A is a FLOAT64_TYPE array with a million elements that are randomly generated numbers between .2 and .3 inclusive. Suppose that we make a histogram h with the call Make_Array(A,8,VALF(0),VALU(0)). Recall that with such parameter settings we are asking Make_Array to pick the largest number of bins not greater than 8 such that bins whose size is of the form [1,2,5]*10a cover the range of elements in A. In this instance it is 5 bins of size .02. Then calling Print_Histogram with the flags BIN_COUNT|CUMULATIVE_PERCENT and binsize set to 0 (i.e. no effect), produces the following output: 0.28 - 0.30: 200167 20.0% 0.26 - 0.28: 200357 40.1% 0.24 - 0.26: 199802 60.0% 0.22 - 0.24: 199738 80.0% 0.20 - 0.22: 199936 100.0% Calling Print_Histogram with the flags BIN_COUNT|CUMULATIVE_PERCENT and binsize set to VALF(.0125) on the same histogram produces the output below. Note carefully that the numbers for each "pseudo-bin" of size .0125 are obtained by linearly interperlating fractional parts of the .02 bins recorded in the histogram. 0.2875 - 0.3000: 125105 12.5% 0.2750 - 0.2875: 125152 25.0% 0.2625 - 0.2750: 125223 37.5% 0.2500 - 0.2625: 124946 50.0% 0.2375 - 0.2500: 124868 62.5% 0.2250 - 0.2375: 124836 75.0% 0.2125 - 0.2250: 124911 87.5% 0.2000 - 0.2125: 124959 100.0% Finally, calling Print_Histogram with the flags BIN_COUNT|CUMULATIVE_PERCENT|BIN_MIDDLE and binsize set to 0 (i.e. no effect), on the same histogram would produce: BIN_COUNT|CUMULATIVE_PERCENT|BIN_MIDDLE,VALF(0) 0.29: 200167 20.0% 0.27: 200357 40.1% 0.25: 199802 60.0% 0.23: 199738 80.0% 0.21: 199936 100.0% |


[1]
A+++++!!!!; Too may versions
[2]
Design, Integration, Security & User Experience; Multiple Versions, Consumer Confusion.
[3]
Apple Will Now Die; Apple Has 4% Market Share - Losers!


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git-merge - Join two or more development histories together
git merge [-n] [--stat] [--no-commit] [--squash] [--[no-]edit] [-s <strategy>] [-X <strategy-option>] [-S[<key-id>]] [--[no-]rerere-autoupdate] [-m <msg>] [<commit>...] git merge <msg> HEAD <commit>... git merge --abort
Incorporates changes from the named commits (since the time their histories diverged from the current branch) into the current branch. This command is used by git pull to incorporate changes from another repository and can be used by hand to merge changes from one branch into another.
Assume the following history exists and the current branch is "master":
A---B---C topic / D---E---F---G master
Then "git merge topic" will replay the changes made on the topic branch since it diverged from master (i.e., E) until its current commit (C) on top of master, and record the result in a new commit along with the names of the two parent commits and a log message from the user describing the changes.
A---B---C topic / e D---E---F---G---H master
The second syntax (<msg> HEAD <commit>...) is supported for historical reasons. Do not use it from the command line or in new scripts. It is the same as git merge -m <msg> <commit>....
The third syntax ("git merge --abort") can only be run after the merge has resulted in conflicts. git merge --abort will abort the merge process and try to reconstruct the pre-merge state. However, if there were uncommitted changes when the merge started (and especially if those changes were further modified after the merge was started), git merge --abort will in some cases be unable to reconstruct the original (pre-merge) changes. Therefore:
Warning: Running git merge with non-trivial uncommitted changes is discouraged: while possible, it may leave you in a state that is hard to back out of in the case of a conflict.
--commit, --no-commit
Perform the merge and commit the result. This option can be used to override --no-commit.
With --no-commit perform the merge but pretend the merge failed and do not autocommit, to give the user a chance to inspect and further tweak the merge result before committing.
--edit, -e, --no-edit
Invoke an editor before committing successful mechanical merge to further edit the auto-generated merge message, so that the user can explain and justify the merge. The --no-edit option can be used to accept the auto-generated message (this is generally discouraged). The --edit (or -e) option is still useful if you are giving a draft message with the -m option from the command line and want to edit it in the editor.
Older scripts may depend on the historical behaviour of not allowing the user to edit the merge log message. They will see an editor opened when they run git merge. To make it easier to adjust such scripts to the updated behaviour, the environment variable GIT_MERGE_AUTOEDIT can be set to no at the beginning of them.
--ff
When the merge resolves as a fast-forward, only update the branch pointer, without creating a merge commit. This is the default behavior.
--no-ff
Create a merge commit even when the merge resolves as a fast-forward. This is the default behaviour when merging an annotated (and possibly signed) tag.
--ff-only
Refuse to merge and exit with a non-zero status unless the current HEAD is already up-to-date or the merge can be resolved as a fast-forward.
--log[=<n>], --no-log
In addition to branch names, populate the log message with one-line descriptions from at most <n> actual commits that are being merged. See also git-fmt-merge-msg(1).
With --no-log do not list one-line descriptions from the actual commits being merged.
--stat, -n, --no-stat
Show a diffstat at the end of the merge. The diffstat is also controlled by the configuration option merge.stat.
With -n or --no-stat do not show a diffstat at the end of the merge.
--squash, --no-squash
Produce the working tree and index state as if a real merge happened (except for the merge information), but do not actually make a commit, move the HEAD, or record $GIT_DIR/MERGE_HEAD (to cause the next git commit command to create a merge commit). This allows you to create a single commit on top of the current branch whose effect is the same as merging another branch (or more in case of an octopus).
With --no-squash perform the merge and commit the result. This option can be used to override --squash.
-s <strategy>, --strategy=<strategy>
Use the given merge strategy; can be supplied more than once to specify them in the order they should be tried. If there is no -s option, a built-in list of strategies is used instead (git merge-recursive when merging a single head, git merge-octopus otherwise).
-X <option>, --strategy-option=<option>
Pass merge strategy specific option through to the merge strategy.
--verify-signatures, --no-verify-signatures
Verify that the commits being merged have good and trusted GPG signatures and abort the merge in case they do not.
--summary, --no-summary
Synonyms to --stat and --no-stat; these are deprecated and will be removed in the future.
-q, --quiet
Operate quietly. Implies --no-progress.
-v, --verbose
Be verbose.
--progress, --no-progress
Turn progress on/off explicitly. If neither is specified, progress is shown if standard error is connected to a terminal. Note that not all merge strategies may support progress reporting.
-S[<keyid>], --gpg-sign[=<keyid>]
GPG-sign the resulting merge commit.
-m <msg>
Set the commit message to be used for the merge commit (in case one is created).
If --log is specified, a shortlog of the commits being merged will be appended to the specified message.
The git fmt-merge-msg command can be used to give a good default for automated git merge invocations.
--[no-]rerere-autoupdate
Allow the rerere mechanism to update the index with the result of auto-conflict resolution if possible.
--abort
Abort the current conflict resolution process, and try to reconstruct the pre-merge state.
If there were uncommitted worktree changes present when the merge started, git merge --abort will in some cases be unable to reconstruct these changes. It is therefore recommended to always commit or stash your changes before running git merge.
git merge --abort is equivalent to git reset --merge when MERGE_HEAD is present.
<commit>...
Commits, usually other branch heads, to merge into our branch. Specifying more than one commit will create a merge with more than two parents (affectionately called an Octopus merge).
If no commit is given from the command line, merge the remote-tracking branches that the current branch is configured to use as its upstream. See also the configuration section of this manual page.
Before applying outside changes, you should get your own work in good shape and committed locally, so it will not be clobbered if there are conflicts. See also git-stash(1). git pull and git merge will stop without doing anything when local uncommitted changes overlap with files that git pull/git merge may need to update.
To avoid recording unrelated changes in the merge commit, git pull and git merge will also abort if there are any changes registered in the index relative to the HEAD commit. (One exception is when the changed index entries are in the state that would result from the merge already.)
If all named commits are already ancestors of HEAD, git merge will exit early with the message "Already up-to-date."
Often the current branch head is an ancestor of the named commit. This is the most common case especially when invoked from git pull: you are tracking an upstream repository, you have committed no local changes, and now you want to update to a newer upstream revision. In this case, a new commit is not needed to store the combined history; instead, the HEAD (along with the index) is updated to point at the named commit, without creating an extra merge commit.
This behavior can be suppressed with the --no-ff option.
Except in a fast-forward merge (see above), the branches to be merged must be tied together by a merge commit that has both of them as its parents.
A merged version reconciling the changes from all branches to be merged is committed, and your HEAD, index, and working tree are updated to it. It is possible to have modifications in the working tree as long as they do not overlap; the update will preserve them.
When it is not obvious how to reconcile the changes, the following happens:
h'-04' 1.h'+01'c
The HEAD pointer stays the same.
h'-04' 2.h'+01'c
The MERGE_HEAD ref is set to point to the other branch head.
h'-04' 3.h'+01'c
Paths that merged cleanly are updated both in the index file and in your working tree.
h'-04' 4.h'+01'c
For conflicting paths, the index file records up to three versions: stage 1 stores the version from the common ancestor, stage 2 from HEAD, and stage 3 from MERGE_HEAD (you can inspect the stages with git ls-files -u). The working tree files contain the result of the "merge" program; i.e. 3-way merge results with familiar conflict markers <<<===>>>.
h'-04' 5.h'+01'c
No other changes are made. In particular, the local modifications you had before you started merge will stay the same and the index entries for them stay as they were, i.e. matching HEAD.
If you tried a merge which resulted in complex conflicts and want to start over, you can recover with git merge --abort.
When merging an annotated (and possibly signed) tag, Git always creates a merge commit even if a fast-forward merge is possible, and the commit message template is prepared with the tag message. Additionally, if the tag is signed, the signature check is reported as a comment in the message template. See also git-tag(1).
When you want to just integrate with the work leading to the commit that happens to be tagged, e.g. synchronizing with an upstream release point, you may not want to make an unnecessary merge commit.
In such a case, you can "unwrap" the tag yourself before feeding it to git merge, or pass --ff-only when you do not have any work on your own. e.g.
git fetch origin git merge v1.2.3^0 git merge --ff-only v1.2.3
During a merge, the working tree files are updated to reflect the result of the merge. Among the changes made to the common ancestor(cqs version, non-overlapping ones (that is, you changed an area of the file while the other side left that area intact, or vice versa) are incorporated in the final result verbatim. When both sides made changes to the same area, however, Git cannot randomly pick one side over the other, and asks you to resolve it by leaving what both sides did to that area.
By default, Git uses the same style as the one used by the "merge" program from the RCS suite to present such a conflicted hunk, like this:
Here are lines that are either unchanged from the common ancestor, or cleanly resolved because only one side changed. <<<<<<< yours:sample.txt Conflict resolution is hard; let*(Aqs go shopping. ======= Git makes conflict resolution easy. >>>>>>> theirs:sample.txt And here is another line that is cleanly resolved or unmodified.
The area where a pair of conflicting changes happened is marked with markers <<<<<<<, =======, and >>>>>>>. The part before the ======= is typically your side, and the part afterwards is typically their side.
The default format does not show what the original said in the conflicting area. You cannot tell how many lines are deleted and replaced with Barbie(cqs remark on your side. The only thing you can tell is that your side wants to say it is hard and you(cqd prefer to go shopping, while the other side wants to claim it is easy.
An alternative style can be used by setting the "merge.conflictstyle" configuration variable to "diff3". In "diff3" style, the above conflict may look like this:
Here are lines that are either unchanged from the common ancestor, or cleanly resolved because only one side changed. <<<<<<< yours:sample.txt Conflict resolution is hard; let*(Aqs go shopping. ||||||| Conflict resolution is hard. ======= Git makes conflict resolution easy. >>>>>>> theirs:sample.txt And here is another line that is cleanly resolved or unmodified.
In addition to the <<<<<<<, =======, and >>>>>>> markers, it uses another ||||||| marker that is followed by the original text. You can tell that the original just stated a fact, and your side simply gave in to that statement and gave up, while the other side tried to have a more positive attitude. You can sometimes come up with a better resolution by viewing the original.
After seeing a conflict, you can do two things:
h'-04'(buh'+03'c
Decide not to merge. The only clean-ups you need are to reset the index file to the HEAD commit to reverse 2. and to clean up working tree changes made by 2. and 3.; git merge --abort can be used for this.
h'-04'(buh'+03'c
Resolve the conflicts. Git will mark the conflicts in the working tree. Edit the files into shape and git add them to the index.
You can work through the conflict with a number of tools:
h'-04'(buh'+03'c
Use a mergetool. git mergetool to launch a graphical mergetool which will work you through the merge.
h'-04'(buh'+03'c
Look at the diffs. git diff will show a three-way diff, highlighting changes from both the HEAD and MERGE_HEAD versions.
h'-04'(buh'+03'c
Look at the diffs from each branch. git log --merge -p <path> will show diffs first for the HEAD version and then the MERGE_HEAD version.
h'-04'(buh'+03'c
Look at the originals. git show :1:filename shows the common ancestor, git show :2:filename shows the HEAD version, and git show :3:filename shows the MERGE_HEAD version.
h'-04'(buh'+03'c
Merge branches fixes and enhancements on top of the current branch, making an octopus merge:
$ git merge fixes enhancements
h'-04'(buh'+03'c
Merge branch obsolete into the current branch, using ours merge strategy:
$ git merge -s ours obsolete
h'-04'(buh'+03'c
Merge branch maint into the current branch, but do not make a new commit automatically:
$ git merge --no-commit maint
This can be used when you want to include further changes to the merge, or want to write your own merge commit message.
You should refrain from abusing this option to sneak substantial changes into a merge commit. Small fixups like bumping release/version name would be acceptable.
The merge mechanism (git merge and git pull commands) allows the backend merge strategies to be chosen with -s option. Some strategies can also take their own options, which can be passed by giving -X<option> arguments to git merge and/or git pull.
resolve
This can only resolve two heads (i.e. the current branch and another branch you pulled from) using a 3-way merge algorithm. It tries to carefully detect criss-cross merge ambiguities and is considered generally safe and fast.
recursive
This can only resolve two heads using a 3-way merge algorithm. When there is more than one common ancestor that can be used for 3-way merge, it creates a merged tree of the common ancestors and uses that as the reference tree for the 3-way merge. This has been reported to result in fewer merge conflicts without causing mismerges by tests done on actual merge commits taken from Linux 2.6 kernel development history. Additionally this can detect and handle merges involving renames. This is the default merge strategy when pulling or merging one branch.
The recursive strategy can take the following options:
ours
This option forces conflicting hunks to be auto-resolved cleanly by favoring our version. Changes from the other tree that do not conflict with our side are reflected to the merge result. For a binary file, the entire contents are taken from our side.
This should not be confused with the ours merge strategy, which does not even look at what the other tree contains at all. It discards everything the other tree did, declaring our history contains all that happened in it.
theirs
This is the opposite of ours.
patience
With this option, merge-recursive spends a little extra time to avoid mismerges that sometimes occur due to unimportant matching lines (e.g., braces from distinct functions). Use this when the branches to be merged have diverged wildly. See also git-diff(1)--patience.
diff-algorithm=[patience|minimal|histogram|myers]
Tells merge-recursive to use a different diff algorithm, which can help avoid mismerges that occur due to unimportant matching lines (such as braces from distinct functions). See also git-diff(1)--diff-algorithm.
ignore-space-change, ignore-all-space, ignore-space-at-eol
Treats lines with the indicated type of whitespace change as unchanged for the sake of a three-way merge. Whitespace changes mixed with other changes to a line are not ignored. See also git-diff(1)-b, -w, and --ignore-space-at-eol.
h'-04'(buh'+03'c
If their version only introduces whitespace changes to a line, our version is used;
h'-04'(buh'+03'c
If our version introduces whitespace changes but their version includes a substantial change, their version is used;
h'-04'(buh'+03'c
Otherwise, the merge proceeds in the usual way.
renormalize
This runs a virtual check-out and check-in of all three stages of a file when resolving a three-way merge. This option is meant to be used when merging branches with different clean filters or end-of-line normalization rules. See "Merging branches with differing checkin/checkout attributes" in gitattributes(5) for details.
no-renormalize
Disables the renormalize option. This overrides the merge.renormalize configuration variable.
rename-threshold=<n>
Controls the similarity threshold used for rename detection. See also git-diff(1)-M.
subtree[=<path>]
This option is a more advanced form of subtree strategy, where the strategy makes a guess on how two trees must be shifted to match with each other when merging. Instead, the specified path is prefixed (or stripped from the beginning) to make the shape of two trees to match.
octopus
This resolves cases with more than two heads, but refuses to do a complex merge that needs manual resolution. It is primarily meant to be used for bundling topic branch heads together. This is the default merge strategy when pulling or merging more than one branch.
ours
This resolves any number of heads, but the resulting tree of the merge is always that of the current branch head, effectively ignoring all changes from all other branches. It is meant to be used to supersede old development history of side branches. Note that this is different from the -Xours option to the recursive merge strategy.
subtree
This is a modified recursive strategy. When merging trees A and B, if B corresponds to a subtree of A, B is first adjusted to match the tree structure of A, instead of reading the trees at the same level. This adjustment is also done to the common ancestor tree.
With the strategies that use 3-way merge (including the default, recursive), if a change is made on both branches, but later reverted on one of the branches, that change will be present in the merged result; some people find this behavior confusing. It occurs because only the heads and the merge base are considered when performing a merge, not the individual commits. The merge algorithm therefore considers the reverted change as no change at all, and substitutes the changed version instead.
merge.conflictstyle
Specify the style in which conflicted hunks are written out to working tree files upon merge. The default is "merge", which shows a <<<<<<< conflict marker, changes made by one side, a ======= marker, changes made by the other side, and then a >>>>>>> marker. An alternate style, "diff3", adds a ||||||| marker and the original text before the ======= marker.
merge.defaultToUpstream
If merge is called without any commit argument, merge the upstream branches configured for the current branch by using their last observed values stored in their remote-tracking branches. The values of the branch.<current branch>.merge that name the branches at the remote named by branch.<current branch>.remote are consulted, and then they are mapped via remote.<remote>.fetch to their corresponding remote-tracking branches, and the tips of these tracking branches are merged.
merge.ff
By default, Git does not create an extra merge commit when merging a commit that is a descendant of the current commit. Instead, the tip of the current branch is fast-forwarded. When set to false, this variable tells Git to create an extra merge commit in such a case (equivalent to giving the --no-ff option from the command line). When set to only, only such fast-forward merges are allowed (equivalent to giving the --ff-only option from the command line).
merge.log
In addition to branch names, populate the log message with at most the specified number of one-line descriptions from the actual commits that are being merged. Defaults to false, and true is a synonym for 20.
merge.renameLimit
The number of files to consider when performing rename detection during a merge; if not specified, defaults to the value of diff.renameLimit.
merge.renormalize
Tell Git that canonical representation of files in the repository has changed over time (e.g. earlier commits record text files with CRLF line endings, but recent ones use LF line endings). In such a repository, Git can convert the data recorded in commits to a canonical form before performing a merge to reduce unnecessary conflicts. For more information, see section "Merging branches with differing checkin/checkout attributes" in gitattributes(5).
merge.stat
Whether to print the diffstat between ORIG_HEAD and the merge result at the end of the merge. True by default.
merge.tool
Controls which merge tool is used by git-mergetool(1). The list below shows the valid built-in values. Any other value is treated as a custom merge tool and requires that a corresponding mergetool.<tool>.cmd variable is defined.
h'-04'(buh'+03'c
araxis
h'-04'(buh'+03'c
bc3
h'-04'(buh'+03'c
codecompare
h'-04'(buh'+03'c
deltawalker
h'-04'(buh'+03'c
diffmerge
h'-04'(buh'+03'c
diffuse
h'-04'(buh'+03'c
ecmerge
h'-04'(buh'+03'c
emerge
h'-04'(buh'+03'c
gvimdiff
h'-04'(buh'+03'c
gvimdiff2
h'-04'(buh'+03'c
gvimdiff3
h'-04'(buh'+03'c
kdiff3
h'-04'(buh'+03'c
meld
h'-04'(buh'+03'c
opendiff
h'-04'(buh'+03'c
p4merge
h'-04'(buh'+03'c
tkdiff
h'-04'(buh'+03'c
tortoisemerge
h'-04'(buh'+03'c
vimdiff
h'-04'(buh'+03'c
vimdiff2
h'-04'(buh'+03'c
vimdiff3
h'-04'(buh'+03'c
xxdiff
merge.verbosity
Controls the amount of output shown by the recursive merge strategy. Level 0 outputs nothing except a final error message if conflicts were detected. Level 1 outputs only conflicts, 2 outputs conflicts and file changes. Level 5 and above outputs debugging information. The default is level 2. Can be overridden by the GIT_MERGE_VERBOSITY environment variable.
merge.<driver>.name
Defines a human-readable name for a custom low-level merge driver. See gitattributes(5) for details.
merge.<driver>.driver
Defines the command that implements a custom low-level merge driver. See gitattributes(5) for details.
merge.<driver>.recursive
Names a low-level merge driver to be used when performing an internal merge between common ancestors. See gitattributes(5) for details.
branch.<name>.mergeoptions
Sets default options for merging into branch <name>. The syntax and supported options are the same as those of git merge, but option values containing whitespace characters are currently not supported.
git-fmt-merge-msg(1), git-pull(1), gitattributes(5), git-reset(1), git-diff(1), git-ls-files(1), git-add(1), git-rm(1), git-mergetool(1)
Part of the git(1) suite


NROFF
Section: User Commands (1)Updated: 11 November 2010
Index Return to Main Contents
NAME
nroff - emulate nroff command with groffSYNOPSIS
nroff [ -h ] [ -i ] [ -m name ] [ -n num ] [ -o list ] [ -p ] [ -r cn ] [ -S ] [ -t ] [ -T name ] [ -U ] [ -v ] [ file ... ]
DESCRIPTION
The nroff script emulates the nroff command using groff. Only ascii, ascii8, latin1, utf8, nippon, and cp1047 are valid arguments for the -T option. If an invalid or no -T option is given, nroff checks the current locale to select a default output device. It first tries the locale program, then the environment variables LC_ALL, LC_CTYPE, and LANG, and finally the LESSCHARSET environment variable.The -h and -c options are equivalent to grotty's options -h (using tabs in the output) and -c (using the old output scheme instead of SGR escape sequences). The -C, -i, -n, -m, -o, and -r options have the effect described in troff(1). In addition, nroff silently ignores the options -e, -q, and -s (which are not implemented in troff). Options -p (pic), -t (tbl), -S (safer), and -U (unsafe) are passed to groff. -v shows the version number.
ENVIRONMENT
- GROFF_BIN_PATH
- A colon separated list of directories in which to search for the groff executable before searching in PATH. If unset, `/usr/bin' is used.
NOTES
This shell script is basically intended for use with man(1), so warnings are suppressed. nroff-style character definitions (in the file tty-char.tmac) are also loaded to emulate unrepresentable glyphs.SEE ALSO
groff(1), troff(1), grotty(1)
Index
This document was created by man2html, using the manual pages.
Time: 05:29:04 GMT, December 24, 2015


We are a group of Electrical and Computer engineers at Georgia Insitute of Techonology trying to solve an on-going problems in our society. With Covid – 19 affecting the whole world, people are forced to communicate virtually, which can be somewhat limited. Body languages and gestures play a huge role in conversation and some will even argue that body languages are more important than verbal communication. To alleviate this problem, we came up with the idea of a web-controlled robot that does certain gestures depending on the user's control


--- layout: page title: Contact permalink: /contact/ description: I care about my readers' opinions. Please leave a note or just say hello. ---
I care about my readers' opinion. Please leave a note or just say hello.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Suscipit praesentium vel autem consequuntur vitae recusandae repellat itaque, quisquam perspiciatis id! Dicta tempora sit totam. Enim quod rerum sit iure soluta?


|
MoveToCode
|
Contains information about which game object has the focus currently. More...
Properties | |
| float | RayDistance [get, set] |
| Distance along the ray until a hit, or until the end of the ray if no hit More... | |
| Vector3 | Point [get, set] |
| The hit point of the raycast. More... | |
| Vector3 | Normal [get, set] |
| The normal of the raycast. More... | |
| GameObject | Object [get, set] |
| The object hit by the last raycast. More... | |
| MixedRealityRaycastHit | LastRaycastHit [get, set] |
| The last raycast hit info. More... | |
| RaycastResult | LastGraphicsRaycastResult [get, set] |
| The last raycast hit info for graphic raycast More... | |
| Vector3 | PointLocalSpace [get, set] |
| Vector3 | NormalLocalSpace [get, set] |
Contains information about which game object has the focus currently.
Also contains information about the normal of that point.
|
getset |
The last raycast hit info for graphic raycast
|
getset |
The last raycast hit info.
|
getset |
The normal of the raycast.
|
getset |
|
getset |
The object hit by the last raycast.
|
getset |
The hit point of the raycast.
|
getset |
|
getset |
Distance along the ray until a hit, or until the end of the ray if no hit


JavaSMT is a generic API allowing unified access to different SMT solvers.
All the interaction with a solver is performed through the {@link org.sosy_lab.java_smt.api.SolverContext} interface, which encapsulates a single context. {@link org.sosy_lab.java_smt.api.SolverContext} instances are created using {@link org.sosy_lab.java_smt.SolverContextFactory}.


If you are a refugee hoping get help, please send 9512 a message. In the message please include the code above, your UNID, and your need, like the example below:
{pole_code},xxxx,food
Don't worry, help is on the way!


Planetary Defense
TECH: Unity3D, ARCore, Photon Unity Networking (PUN)
Planetary Defense was the first AR title I released, and it was highly experimental. That being said, I think it held up well and I personally enjoy going back and playing it even today. This title had several features which made it stand out:
- The player used their phone to "aim" and position their spaceship in the world.
- Synchronous multiplayer gameplay created with Photon Unity Networking (PUN).
- Rank and powerup systems encouraged players to keep playing and beat their high-scores.
Planetary Defense was developed with ARCore and released as a beta on the Google Play Store. If you have an android phone, you can download it here.


Markoview
set network size
show matrix
random stochastic matrix
show vector
random stochastic vector
draw network
clear network


Event Location:
Microsoft Mobile Oy (Ltd)
Keilalahdentie 2-4
Espoo, , Finland
Abstract:
Let me show you how easy it is to use PowerShell to accomplish many everyday tasks straight from the command line with the community developed module dbatools. Afraid of PowerShell? Worried its too complicated? Don't want to go through the learning curve? Let me show you with plenty of demos how easy and straight forward it can be and I will save you time starting Monday Want to restore an entire servers databases to the latest available point in time of the backups in just one line? Be useful to know the Last DBCC Check for your entire estate in only one line of code? Need to test your restores but its complicated? and many many more All this in a fast paced, fun session
Speaker(s): Rob Sewell,
Abstract:
Are you tired of creating and updating the same SSIS packages again and again? Is your wrist hurting from all that clicking, dragging, dropping, connecting and aligning? Do you want to take the next step and really speed up your SSIS development? Say goodbye to repetitive work and hello to Biml, the markup language for Business Intelligence projects. In this session we will look at the basics of Biml. First learn how to use Biml to generate SSIS packages from database metadata. Then see how you can reuse code to implement changes in multiple SSIS packages and projects with just a few clicks. Finally, we will create an example project that you can download and start with to speed up your SSIS development from day one. Stop wasting your valuable time on doing the same things over and over and over again, and see how you can complete in a day what once took more than a week!
Speaker(s): Cathrine Wilhelmsen,
Abstract:
Extended Events provide deep insight into SQL Server's behavior and allow us to gather information not available by other means. However, compared to other technologies such as SQL Trace and Event Notifications, Extended Events don't seem to provide a way to react to the events as soon as they happen. In this session we will see how the Extended Events streaming API can be used to process events in a near real-time fashion. We will demonstrate how this technology enables new possibilities to solve real world problems, such as capturing and notifying deadlocks or blocking sessions. We will also offer a different approach to analyzing captured events, without shredding XML files.
Speaker(s): Gianluca Sartori,
Abstract:
The last couple of years have seen the emergency of "Big Data", "Cloud" and "Internet of Things". Subsequently, Gartner at the 2016 Gartner Summit in Barcelona declared the Enterprise data warehouse (EDW) as dead. Which of course is silly. Sensible companies don't just throw money out of the window. But they need to adapt and change when new opportunities arrive. Enter the hybrid data warehouse. Combining the power of big data and cloud with your trusty EDW. This session will take a look at a few different approaches to a hybrid data warehouse, with components such as SQLServer 2016, Azure Data Lake, HDInsight, Azure Analysis Services, Azure SQL Data warehouse and Polybase, with some scenarios where the approaches might become relevant. And some pitfalls you need to know about along the way.
Speaker(s): Johan Ludvig Brattås,
Abstract:
Let’s go beyond the standard visuals available in Power BI for making maps. In this session we won’t talk about Bing or ArcGIS services. We want to explore all the available features for creating custom maps without having to rely on existing ones. Do you know what is a shapefile? Do you know how to create your own choropleth and import it into Power BI? What else? R support into Power BI opened the doors to the huge number of packages for spatial data analysis and statistical calculations included in the environment. Do you want to draw multi-layered interactive maps? Want to geocode your data with direct calls? With R in Power BI, now you can. Last but least, we will able to discover Synoptic Panel, an awesome component that connects areas in a custom image with attributes in the data model and draws the data on a map. There are endless possibilities; the only limit is your imagination!
Speaker(s): Andrea Martorana Tusa,
Abstract:
Python is one of the most popular languages this days and we are very excited to have an ability to use Python inside SQL Server stored procedures starting SQL Server 2017. Machine learning is not the only usecase for this wonderful feature, it can solve many challenges when dealing with text files, bulk loads and even simplify ETL flows when you need to move data from databases other than SQL Server. Moreover, you can offload the big data querying to nosql database and use Python to get the results into SQL server. Target Audience: Application and Infrastructure DBAs that want to see various usages for Python language from inside SQL Server stored procedures.
Speaker(s): Maria Zakourdaev,
Abstract:
The software development landscape is changing. More and more, there is an increased demand for AI and cloud solutions. As a user buying cinema tickets online, I would like to simply ask "I want to buy two cinema tickets for the movie Dunkirk, tomorrow's viewing at 1pm" instead of manually following a pre-defined process. In this session, we will learn how to build, debug and deploy a chatbot using the Azure Bot Service. We will enrich it using the Microsoft Cognitive suite to achieve human like interactions. Will it pass the Turing test, no, but we can extend the bot service using Machine Learning (LUIS), APIs (Web Apps) and Worflows (Logic Apps).
Speaker(s): Jose Mendes,
Abstract:
Everybody is talking about best practices, and like standards, most everybody has them. But why do they look like they do, and why would you use a specific set of "best practices" that someone has put together? This session goes through my set of best practices that I've accumulated over 20 years of DBA work, disassembles each and every one of them to see how they came about and discusses why I still use them - or don't. There is no such thing as the ultimate best practices, but I aim to provide the attendee with as much food for thought as possible in order to let each and everyone decide on their own path forward for their own set of best practices. The session covers primarily SQL Server 2012 to 2016, with SQL Server 2017 thrown in for good measure.
Speaker(s): Alexander Arvidsson,
Abstract:
One of the most common problems I have encountered as a DBA is the complaints from users that a particular query is slow, just one query. Many times one that used to run in acceptable time, but that over time has slowed down substantially. In this session we will show some of the causes for this, with emphasis on I/O requests being too high for the query. First part of the session will explain how to find these numbers, looking at a few queries with some major performance issues, including explaining why they have a problem. The second part will focus on how to reduce I/O requests. All of this can be done without the need for any 3rd party tools, all within the scope of what is available to SQL Server, all versions, all editions, including Azure.
Speaker(s): Anders Pedersen,
Abstract:
The range of options for storing data in Microsoft Azure keeps growing, the most notable recent addition is the Managed Instance. But what is it, and why is it there? Join John as he walks through what they are and how you might start using them. Managed Instances add a new option for running workloads in the cloud. Allowing near parity with a traditional on-premises SQL Server. Including SQL Agent, Cross Database Queries, Service Broker, CDC, and many more. Overcoming many of the challenges to using Azure SQL Databases. But, what is the reality, how do we make use of it, and are there any gotcha’s that we need to be aware of? This is what we will cover, going beyond the hype and looking at how we can make use of this new technology.
Speaker(s): John Martin,
Abstract:
In times past, Data Science was only for those elite few with a rare combination of skills including advanced knowledge of statistics. Microsoft has been making sure that everyone can participate in the data revolution by giving people access to predictive API’s, in-database advanced analytics and drag-and-drop predictive experiments. All thanks to SQL Server 2016 and the Cortana Intelligence Suite in Azure. These advances have given people with less knowledge of statistics and programming the ability to become what Gartner calls citizen data scientists. Should we be worried about creating fools-with-tools or should we embrace the democratization of data science as the golden age of data? In this demo heavy session we explore Microsoft’s solutions to ensure democratization of data science and the possible dangers that lurk below the surface.
Speaker(s): Jan Mulkens,
Abstract:
In this session, database expert Martin Wild of Quest Software will lift the lid on SQL Server on Linux. He’ll explore the mechanics of deploying SQL Server on Linux, what is and is not in the current Linux build and discuss quirks, insights and observations on setup and configuration. Once the stage is set, Martin will cover tuning and performance on Linux and bring you through some new DMVs for Linux monitoring. He’ll then compare the plans produced on Linux vs. Windows for consistency… or not! Speaker: Martin Wild Martin Wild is a principal systems consultant at Quest. He frequently presents at SQL Server events such as SQL Bits and SQL Saturdays, and Oracle user groups. Martin has expertise with Oracle, SQL Server, Sybase, DB2, Windows, UNIX, Linux, VMware and Hyper-V. He has worked in IT for more than 30 years, initially in manufacturing and retail organizations. For the last 17 years he has held various database pre-sales roles and is a member of the British Computer Society
Speaker(s): SQLSaturday Finland,
Abstract:
In this session, we will demonstrate the power of Discovery Hub® by building an end-to-end solution from scratch in just 30min. We automate the majority of the tedious tasks related to a DWH project with high quality auto-generated scripts, documentation, data lineage tracing managed deployment/execution and many other value-adding features. We accelerate BI projects dramatically and allows BI developers to focus their efforts on the tricky modelling tasks, rather than the majority of standard technical steps. Speaker: Mahmoud Ismail Mahmoud is a Solution Architect in TimeXtenders Customer Service Success team and has significant experience in implementing and utilizing the Discovery Hub in a number of industries and sectors. He also has excellent knowledge in regards to data modelling for both Qlik applications, OLAP Cubes and Tabular models. He takes part in a lot of projects ranging, from presales, training consulting and hands-on DWA developing.
Speaker(s): SQLSaturday Finland,
Abstract:
Experts should work with facts, not guesstimates – how you learn to love large scale SQL Server consolidation projects Have you ever been struggling with the consolidation or migration planning of a sizable SQL Server platform? Traditional data platform capacity planning contains a lot of time consuming manual work and is often based on rough estimates. It is seen more as a task for the data platform architect than a mathematical challenge. The truth is: It is both. Find out how to achieve highly automatized, perfectly optimized plan, based on facts rather than guesswork! Speaker: Jani K. Savolainen. Founder CTO @ DB Pro.
Speaker(s): SQLSaturday Finland,
Abstract:
We will cover the main aspects to migrate to one of the three architectures available in SQL Server in Azure from SQL Server On Premise. This session consists of: -> What is the best platform for my environment? IaaS, PaaS, or SQL Datawarehouse. -> Best Practices and best tools for our migration process depending on the platform chosen. -> After the migration, we have several outstanding questions: Can I keep both environments synchronized? How is the performance of my database?
Speaker(s): Jose Manuel Jurado Diaz,
Abstract:
Still unthinkable a few years ago, Microsoft’s strategy toward the Open Source world is shaking the computer sphere. Bare metal or virtual machine, SQL Server can now be installed on a Windows OS or… on Linux. In parallel, DevOps culture and micro services seem to be the architecture model for the decade. Docker containers offers IT Pros or Developers interesting scenarios. During this discovery session let’s install Docker, create a first container, install SQL Server and then commit the image for future use. We will also pull an official SQL Server image and walk through some use cases.
Speaker(s): Christophe Laporte,
Abstract:
Azure SQL DB brings a lot of benefits for new and existing workloads. In this session we are going to explore the various aspects of an Azure SQL DB. How we can have a self managed, high available and high performing Database. Properly monitoring is also an important part of the job and we will cover several aspects of monitoring an Azure SQL DB. After this session you will feel comfortable in moving your workload to the cloud.
Speaker(s): Marcos Freccia,
Abstract:
Everthing is connected. Everything is accessible. Everything is hackable. This is a security "worst" practices session for developers (yes, yes, the boring "best" practices are also included). As always, should you or any of your colleagues be hacked or exploited, the Demo Gods will disavow any knowledge of the speakers' actions. This session will self-destruct in 60 minutes. Luck has nothing to do with it, Jim…
Speaker(s): André Melancia,
Abstract:
Join this session by Heidi Enho, Power BI consultant, Microsoft Certified Trainer, Data Platform and Excel MVP. Learn how to use Power BI bookmarks, buttons, drill-through filters and for example brand new report tooltips to communicate insights in your data. Heidi will show in this highly demo based session many examples and tips how to use new navigation and storytelling capabilities.
Speaker(s): Heidi Enho,
Abstract:
Azure SQL Datawarehouse is a petabyte range Massively Parallel Processing Datawarehouse provided as a managed service in Azure. This session will delve into the architecture, new optimized for compute instances, common workload and implementation patterns, performance considerations, loading patterns and strategies and some real-life customer deployment examples.
Speaker(s): Arun Justus,
Abstract:
A common requirement in database applications is that users need a function to search a set of data from a large set of possible search conditions. The challenge is to implement such searches in a way that isboth maintenanble and efficient in terms of performance. This session looks at the two main techniques to implement such searches and highlights their strengths and limitaitons.
Speaker(s): Erland Sommarskog,
Abstract:
Azure Data Factory v1 has not been considered a full blown ETL solution on the market. Data Factory v2 is now introduced to fill in the gaps. We will deliver the understanding of the different features functionalities of both versions as well as a summary comparison between the two. We will also demonstrate the latest and greatest capabilities by orchestrating an end-to-end pipeline with Data Factory v2 including machine learning workloads with Azure DataBricks.
Speaker(s): Oskari Heikkinen,
Abstract:
Welcome to join this session to hear more about data platform that integrates umbarella organization's all different data touch points to new single source of truth. - What are the main components of the Enterprise Data Platform in Azure? - Where to start building? - How to keep it up and running? In this webinar Olli Lindroos from Solita will go through how they have developed multiple organisation wide data platforms. See how for example Azure Data Lake and Power BI were leveraged in this solution and hear best practices from the project.
Speaker(s): Olli Lindroos,
Abstract:
Microsoft has added new performance improvements and new features to SQL Server 2016 and 2017’s implementation of Always On Availability Groups. This session will cover improvements that range from Standard Edition support for AGs to load balanced replicas to new ways to create those replicas. We’ll kick the tires on the improved Azure support and discuss the massive performance improvements in Always On as well.
Speaker(s): Matt Gordon,
Abstract:
Ok, I know Microsoft Data Platform and I know R but where is the intersection?? What can I use and where? In-Database R, Power BI with R, ML Server… there are a lot of tools where we have R included but what can you do with them? In this session we will go through the offering with simple examples and talk openly about what is good and what needs improvements. If you’re data platform specialist that needs to talk with data scientists about possibilities this session is for you! If you’re data scientist and want to know the contact points in Microsoft Data Plat this is very well also for you!
Speaker(s): Vesa Tikkanen,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
LinkedIn: https://www.linkedin.com/in/alexanderarvidsson
Contact: http://www.arcticdba.se
Alexander is a principal solutions architect at Atea in Linköping, Sweden. Nobody really knows what it means to be a principal solutions architect, but he spends his days helping clients of all shapes and sizes to take better care of their data. He has spent the last 23 years toying with databases and related infrastructure services such as storage, networking and virtualization, occasionally emerging from the technical darkness to attend a Star Wars convention somewhere in the world. He is a frequent international speaker, a Data Platform MVP, podcaster, blogger and a Microsoft Certified Trainer, focusing on SQL Server, the Azure data stack and Power BI.
LinkedIn: https://www.linkedin.com/in/sqlatspeed
Contact: http://www.sqlatspeed.com
Matt is a Microsoft Data Platform MVP and has worked with SQL Server since 2000. He is the leader of the Lexington, KY PASS local group and a frequent domestic and international community speaker. He's an IDERA ACE alumnus and 2020 Friend of Redgate. His original data professional role was as a database developer, which quickly evolved into query tuning work that further evolved into being a full-fledged DBA in the healthcare realm. He has supported several critical systems utilizing SQL Server and managed dozens of 24/7/365 SQL Server implementations. He currently utilizes that real world experience as a data platform consultant helping clients design solutions that meet their ever-changing business needs.
LinkedIn: https://www.linkedin.com/in/johanludvig/
Contact: http://brattas.org/sqlmusings
Johan Ludvig Brattås is a managing consultant at Capgemini, and a dedicated community guy. He has worked with MS SQL server since late 1999, mostly with BI in one form or another. The last 6 years, most of his work has been in Azure working on data platforms, Power BI and the last three years expanding to Azure IoT and Stream Analytics. Combining his passion for Microsoft SQL Server with his passion for sharing knowledge, he has spoken at various events in the SQL Community. This is also a way to give back to the community for all the things he has learned over the years. When not working, Johan Ludvig either spends his time with his kids, playing with new technology, or teaching coeliacs how to bake glutenfree food.
LinkedIn: https://www.linkedin.com/in/mendesjose/
Contact: http://blogs.adatis.co.uk/josemendes/
A Principal Data Analytics Consultant working for Adatis Consulting with experience in delivering Microsoft Azure/ SQL Data Analytics solutions. Presented for the first time in 2017 and since then has been blogging and speaking about the Bot Framework, Power BI, Data Lakes, Databricks and other cool Azure services. Co-organizer of the Surrey Data Platform Group.
LinkedIn: http://fi.linkedin.com/in/vesatikkanen/
Contact: http://www.qumio.com/Blog
Vesa is agile oriented architect from Finland. He is Microsoft Certified Master and MVP. He has passion towards Microsoft Data Platform including both relational and non-relational worlds! Vesa has been working with SQL Server since SQL Server 2000 and counts himself as DBA because he has seen corruption. :) Nowadays he spends his time with advanced analytics related workloads on cloud and on-premise. Vesa Blogs at http://www.qumio.com
LinkedIn: https://www.linkedin.com/in/redheaddba/
Contact: http://sqlblog.com/blogs/maria_zakourdaev/default.aspx
I have been working with SQL Server for more about 20 years. I have experience managing enterprise-wide environments, both transactional and data warehouse flavors. This days, also working closely with other database technologies, including Postgresql, Redis, RedShift, CouchBase and ElasticSearch. However, my preferred technology is still an SQL Server.
LinkedIn: https://www.linkedin.com/in/anders-pedersen-993676
Contact: http://blog.AndersOnSQL.com
20+ years of experience with SQL Server, from version 6.0 to 2017. Funnily enough, the only certification I have is on SQL 2012, the one version I have never used. Mostly worked at medium sized companies, by choice. Was a consultant for 6+ years, working on anything from facility security systems, background checks, retail PoS systems, to major financial systems. Passion for performance, and teaching people easy ways to better SQL performance.
LinkedIn: http://it.linkedin.com/pub/gianluca-sartori/23/50b/a12
Contact: http://spaghettidba.com
Gianluca Sartori is a Data Platform MVP, independent consultant and performance tuning specialist. He has been working in the software industry since 1999 and has been working with SQL Server ever since. He also works as a SQL Server trainer and in his spare time he writes technical articles and participates the SQL Server forums. Gianluca enjoys presenting SQL Server topics at conferences in Europe and in Italy in particular. He is currently working as lead DBA at a famous Formula 1 team.
Andrea Martorana Tusa is a Business Intelligence Team Manager at Würth Phoenix, the IT and consulting company of the Würth-Group. He is awarded as MVP in the Data Platform category Former BI Specialist at Widex, a Danish manufacturing company, and BI Developer in the IT department of an Italian banking group. 20+ years of experience working with data. He is focused on the entire BI stack: database development, data warehousing, data analysis, reporting, etc. Andrea is a usual speaker at many events: SQLSaturdays, conferences in Europe and PASS Summit, and for PASS Virtual Groups. Andrea is an author for sqlshack.com, sqlservercentral.com, and UGISS (User Group Italiano SQL Server).
Contact: http://HExcelligent.fi
Heidi Enho has been consulting and training Power BI and it’s predecessors Power Pivot Power Query since their release. She has a passion for data and visualizations and has two Finnish Power BI sites HExcelligent.fi and vilahdus.fi. Senior Consultant, Microsoft Certified Trainer, Data Platform Excel MVP.
Contact: http://www.sommarskog.se
Erland Sommarskog is an independent consultant based in Stockholm, working with SQL Server since 1991. He was first awarded SQL Server MVP in 2001, and has been re-awarded every year since. His focus is on systems development with the SQL Server Database Engine and his passion is to help people to write better SQL Server applications.
LinkedIn: https://www.linkedin.com/in/janmulkens
Contact: http://www.janmulkens.be
Jan Mulkens is a Microsoft MVP in AI, a Solution Expert at Ordina Belgium, and a Microsoft Data Platform BI Consultant. In his spare time, he is a speaker at conferences and user groups in Europe and he organizes two user groups and a conference in Belgium. Power BI Days conference (www.powerbidays.com), Belgium Microsoft Advanced Analytics User Group (bit.ly/msaaug), and Flemish Power BI User Group (meetup.powerbibelgium.com).
LinkedIn: https://www.linkedin.com/in/brittongray/
Britton Gray is a veteran of database development, data management, business intelligence, analytics, and data privacy in BI. He has successfully completed projects in a variety of technologies in different technology stacks. Coming from a family full of teachers, he thoroughly enjoys the opportunity to share knowledge and insights; it's an extension of "getting the right information to the right people at the right time" mantra of BI. He lives near Indianapolis, Indiana, and is the Director of BI for Project Lead The Way, a nonprofit organization providing transformative learning experiences in computer science, engineering, and biomedical sciences.
We proudly present our great sponsors at the event. They have top-notch products, solutions and services to help you with your SQL related work. Get to know their expertise in the special sponsor sessions!
LinkedIn: https://www.linkedin.com/in/oskariheikkinen/
I have several years of experience in using Azure for data analytics at large scale. I have been implementing numerous projects for some of the largest companies in the Nordics. I am a Microsoft MVP, and I currently hold the MCSE: Data Management and Analytics certification. As a Microsoft Certified Trainer (MCT), I hold classes for subject-matter experts and consultants internally as well as give external customer training sessions. I am also an active speaker on community events.
LinkedIn: https://www.linkedin.com/in/ollilindroos/
I do two things, I design data strategies and I put those into practice by building the best agile team in the market to work on the opportunity. It's my 8'th year in analytics coaching organizations to be data driven and implementing advanced analytics solutions. All my years as a developer taught me that technology is the easy part but changing the culture and the mindset to catch and overcome rapidly changing business environment is the hard part. I appreciate simple quality solutions with polished user experience, love good presentations and enjoy selling. My passion is to help the business to create rapidly something new and valuable for their customers by using modern development methods technologies.
LinkedIn: http://LinkedIn.COM/in/AndreMelancia
Contact: http://Andy.PT
Owner / Principal Consultant at LunarCat.PT Microsoft Certified Trainer (MCT) focusing on SQL Server, Azure, IoT and Security. 19+ years' fun developing information and multimedia systems, DBA, project and IT management. Data Community Portugal, IT Pro Portugal and PowerShell Portugal communities organiser. IPv6 Portugal, DNSSec Portugal and Windows Development Portugal online communities moderator. Actively volunteering, organising, speaking or just participating at community meetings and events around the world. Proud uncle and food devouring expert, with dangerous рuϧϧy cat as companion. Go to http://Andy.PT and you'll know the same as the NSA...
I have recently moved into a Global Account Executive role in the Telco Industry. My previous role was as Cloud Architect in Data Platform area working for Microsoft Finland. Prior roles at Microsoft include Big Data Advisor, Data Platform Solution Architect, Dynamics CRM Technical Lead and Business Intelligence Lead at Microsoft Western Europe Area level. Past work experience is from SAP and Land Transport Authority, Government of Singapore.
LinkedIn: https://uk.linkedin.com/in/robsewellsqldba
Contact: http://sqldbawithabeard.com
Rob was once a production SQL Server DBA, but is now generally found automating the Data Platform and providing training for clients. He has a passion for PowerShell, Data, and DevOps. He is an MVP, an officer for the DevOps PowerShell VG, and has spoken and volunteered at many PowerShell and Data events. He is a member of the committee that organises Data In Devon and the European PowerShell Conference. He is a proud supporter of the Data and PowerShell communities. He relishes sharing and learning and can be found doing both via Twitter @sqldbawithbeard and his blog sqldbawithabeard.com. He spends most of his time looking at a screen and loves to solve problems.
LinkedIn: https://br.linkedin.com/in/marcosfreccia
Contact: http://marcosfreccia.wordpress.com
Currently working as a Microsoft SQL Server DBA at Zalando SE, Marcos has over 9 years of SQL Server experience, working from small to enterprise environments with High Availability, Disaster Recovery, Database Optimization, etc.. Holding several Microsoft certifications such as: MCITP DBA DEV, MCSE Data Plataform and his last certification on Microsoft Azure Design and Implement Cloud Data Platform Solutions. In 2013 Marcos was awarded as a Microsoft MVP by his contributions in the Brazilian SQL Server community. Marcos is a frequent speaker in the SQL Server Community and he was the organizer of the first SQL Saturday in South Brazil.
LinkedIn: https://www.linkedin.com/in/cathrinewilhelmsen
Contact: https://www.cathrinewilhelmsen.net/
Cathrine loves teaching and sharing knowledge :) She is based in Norway and works as a Senior Business Intelligence Consultant in Inmeta, focusing on Data Warehousing, Data Integration, Analytics, and Reporting projects. Her core skills are Azure Data Factory, SSIS, Biml and T-SQL development, but she enjoys everything from programming to data visualization. Outside of work she's active in the SQL Server community as a Microsoft Data Platform MVP, BimlHero Certified Expert, author, speaker, blogger, organizer and chronic volunteer.
LinkedIn: https://www.linkedin.com/in/jose-manuel-jurado-diaz-5a586014/
José Manuel Jurado currently works as SQL Escalation Engineer and Subject Matter Expert in Azure SQL Database at Microsoft Spain. With over 20+ years of experience in SQL Server environments (administration and database development), he is a speaker for internal events at Microsoft and for public events such as SQLSaturday, SQL Nexus, SQLBits, Pass Summit, SQL Server Konferenze, TechReady, DotNetConference, and Azure BootCamp. In the past, he worked as Project Manager for large global retail company for more than 10 years developing projects using different Microsoft Technologies.
We proudly present our great sponsors at the event. They have top-notch products, solutions and services to help you with your SQL related work. Get to know their expertise in the special sponsor sessions!
We proudly present our great sponsors at the event. They have top-notch products, solutions and services to help you with your SQL related work. Get to know their expertise in the special sponsor sessions!
LinkedIn: http://uk.linkedin.com/in/johnqmartin/
Contact: https://www.mssqltips.com/sqlserverauthor/291/john-martin/
John Martin is a Data Platform Engineer working in the financial sector, as well as Vice President Marketing for the PASS organization and currently a Microsoft Data Platform MVP. Previously John has worked as a product manager for SentryOne and a Premier Field Engineer with Microsoft UK. John has over a decade of experience working with SQL Server and the Microsoft Data Platform. Working as a DBA, developer and consultant for Microsoft, he has been lucky enough to see how best, and how not, to use SQL Server and the Data Platform effectively.
LinkedIn: http://fr.linkedin.com/in/christophelaporte
Contact: http://conseilit.wordpress.com/
Christophe Laporte is based in Toulouse, France and has worked with SQL Server since 1997, starting with SQL Server 6.5. Focusing on high availability, VLDBs, and virtualization, Christophe also delivers performance audits on SQL Server and helps companies in choosing the appropriate architectures (Cloud, OnPremise, or Hybrid). In addition to his MCM certification, Christophe is also a SQL MVP, speaker, and Microsoft Certified Trainer since 2000.
The following is a list of sponsors that helped fund the event.


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The Weiler House was built in 1900, but it is unclear due to lack of accurate records who actually owned the house until 1923. Jacob Weiler purchased the house in 1923 and occupied it with his wife Lillie and their eight children. Jacob Weiler worked for the mines over the years as a pump man, fire boss and foreman. The house is somewhat larger than what we think of as a "miner's house" and is the cornerstone of the First Union Neighborhood. The young miners would often come by the house to pick up their work schedules, where they would socialize with Mr. Weiler's four teenage daughters.
In 1940, the house was furnished with indoor plumbing, installed in a room on the back porch. The one story structure is two rooms wide, three deep, including a living room, two bedrooms, dining room, kitchen and a sunroom on the east side, called the "sleeping porch" by the Weiler children. The Weiler House was placed on the Lafayette Register of Historic Properties in 2000. |
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M.K.M Tutorial is an one of the best website for coder to learn programing.Here you can learn most important programming language like Java,Python,C,C++,HTML,CSS etc. in easy way.
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Flatiron Student who is trying to change their career from Higher Ed Professional to Software Engineer.


Choosing a Persistence Strategy for Your Application
Objective
Titanium provides various means to save data to the user's mobile device. In this chapter, you will examine those options and select the best technique for a given situation.
Contents
Even the most rudimentary applications usually have some data storage requirements. As always, Titanium provides access to all the native functionality via its convenient, uniform interface. To use a device's local storage, the following objects are needed:
-
Titanium.App.Properties is ideal for storing application-related settings
-
Titanium.Database gives access to local SQLite3 databases
-
Titanium.Filesystem facilitates file and directory manipulation
Each of these enable data to persist on a device across application restarts, power cycles, re-installation and even migration to a new device.
Properties
The Titanium.App.Properties API provides a lightweight key/value store. Titanium provides methods for reading and writing string, integer, boolean, and array values in properties. Any data that can be JSON serialized can be stored in an application property. Properties are a great place to store small chunks of data, such as configuration data for your app. But if you've got a lot of data to store, or you need to set up relationships between those data points, you'd be better served putting it in a database.
Database
Both iOS and Android include a SQLite3 database engine. If you're not familiar with SQLite, you might want to take a brief side trip to http://sqlite.org. In a nutshell, SQLite is a simplified database management system that supports most of the SQL92 specification, including most of the familiar SQL statements and even transactions.
The database is the appropriate place to store lots of structured data or when you need transactional support. You can define tables and columns, and enforce relationships between tables just as you would with a SQLServer or MySQL database. Data persists in the database until the user uninstalls your app or until you overwrite or remove the data.
Filesystem
Titanium.Filesystem let's you read from and write to files on the user's device. Broadly speaking, your app is restricted to reading and writing its own files and cannot access files created by other apps. On Android devices, your app can save files to internal or external (SD card) storage. Files are a great place to store images or other binary data.
What kind of data storage should I use?
The decision about which of the three local storage options you choose is usually determined by the following:
-
Application Properties - used when one or all of the following is true:
-
the data consists of simple key/value pairs
-
the data is related to the application rather than the user
-
the data does not require other data in order to be meaningful or useful
-
there only needs to be one version of the data stored at any one time
-
-
Database - used this when one or all of the following is true:
-
there are many similar data items
-
items of data relate to each other
-
you require flexibility over how the data will be presented when you retrieve it
-
the data accumulates over time, such as transaction, logging or archiving data
-
-
Filesystem - used when one or all of the following is true:
-
the data is already provided in file format
-
the data is an image file
-
Although the local database has the capability to store images in blob (binary) format, this won't lead to optimal performance from your application. Instead, use Titanium.Database to store the image file path and name in the database, and Titanium.Filesystem to manage the physical files.
References and Further Reading
Summary
In this chapter, you examined the local storage options available to your Titanium apps. And we gave you some recommendations of which option to use in various situations. While we didn't dig into the implementation details yet, you got a chance to see when to use each of these persistence options. In the upcoming sections, we'll dig deep into each storage option.


{% extends "profiles/base.html" %} {% block title %}Member statuses{% endblock %} {% block breadcrumbs %} {{ block.super }}
| Username | Display Name | Legal Name | Status | Became member | Actions |
|---|---|---|---|---|---|
| {{ user.username }} | {{ user_profile }} | {{ user_profile.legal_name }} | {{ user_profile.status }} | {{ user_profile.became_member_on }} | Change Status | {% endwith %}


A car as analogy of a webpage:
The HTML of a car would be the structure of this, for example, the frame, the chassis, the door, the windows, the mirrows etc. The CSS provides the style, the painting, shape, the colour of the lights, basically the general look and feel. Sweet car!
The DOM is the driver. The person who understands how to drive the car and control the mechanism of the car, when to change gear, accelerate, stop or change a flat wheel.
boxifying design means that all the elements we can see on a webpage are within boxes/square or rectangular shapes, even the circules are inside boxes
The box model is the specification that defines how a box and its attributes relate to each other. In its simplest form, the box model tells browsers that a box defined as having width 100 pixels and height 50 pixels should be drawn 100 pixels wide and 50 pixels tall.
Box Model
Grid design is a structure comprising a series of horizontal and vertical lines which intersect and are then used to arrange content. Grid is a way of providing a system that developers and designers can work with to structure and present content and imagery in a much more readable and manageable way.
Smartphones, tablets, games consoles, smart tv, smart watch,laptops, smart wristband etc. aincreasing rapidly, so the importance of device-friendly websites is high
Responsive Web Design (RWD) provides an optimal website viewing experience, ease of reading and navigation with a minimum of resizing, panning, and scrolling across a wide range of devices (from desktop computer monitors to mobile phones)
Semantic structure is when the computers understand the roles of the elements inside the documents. If we want to creating proper semantics, we need to deeply understand the structure of our content and the capabilities of frontend technologies.
If you carefully plan the structure of your HTML documents, you can help computers make sense of the meaning of your content.
Keep Coding!


Unleashed dog bites child, 6, at Kalihi park playground | Honolulu Star-Advertiser
A dog with a history of biting people and animals bit a boy, 6, on the face Sunday at a playground in Kalihi, the boy’s father said. Read more
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Hosea 5:11
Ephraim is oppressed and broken in judgment, because he willingly walked after the commandment.


Deep CNN Models!
Deep CNN Models
Constructing and training your own ConvNet from scratch can be Hard and a long task.
A common trick used in Deep Learning is to use a pre-trained model and finetune it to the specific data it will be used for.
Famous Models with Keras
This notebook contains code and reference for the following Keras models (gathered from https://github.com/fchollet/keras/tree/master/keras/applications)
- VGG16
- VGG19
- ResNet50
- Inception v3
- Xception
- … more to come
References
- Very Deep Convolutional Networks for Large-Scale Image Recognition - please cite this paper if you use the VGG models in your work.
- Deep Residual Learning for Image Recognition - please cite this paper if you use the ResNet model in your work.
- Rethinking the Inception Architecture for Computer Vision - please cite this paper if you use the Inception v3 model in your work.
All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json
.
For instance, if you have set image_data_format="channels_last"
, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, “Width-Height-Depth”.
VGG16
VGG19
keras.applications
from keras.applications import VGG16
from keras.applications.imagenet_utils import preprocess_input, decode_predictions
import os
Using TensorFlow backend.
# -- Jupyter/IPython way to see documentation
# please focus on parameters (e.g. include top)
VGG16??
help(VGG16)
Help on function VGG16 in module keras.applications.vgg16:
VGG16(include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000)
Instantiates the VGG16 architecture.
Optionally loads weights pre-trained
on ImageNet. Note that when using TensorFlow,
for best performance you should set
`image_data_format="channels_last"` in your Keras config
at ~/.keras/keras.json.
The model and the weights are compatible with both
TensorFlow and Theano. The data format
convention used by the model is the one
specified in your Keras config file.
# Arguments
include_top: whether to include the 3 fully-connected
layers at the top of the network.
weights: one of `None` (random initialization)
or "imagenet" (pre-training on ImageNet).
input_tensor: optional Keras tensor (i.e. output of `layers.Input()`)
to use as image input for the model.
input_shape: optional shape tuple, only to be specified
if `include_top` is False (otherwise the input shape
has to be `(224, 224, 3)` (with `channels_last` data format)
or `(3, 224, 244)` (with `channels_first` data format).
It should have exactly 3 inputs channels,
and width and height should be no smaller than 48.
E.g. `(200, 200, 3)` would be one valid value.
pooling: Optional pooling mode for feature extraction
when `include_top` is `False`.
- `None` means that the output of the model will be
the 4D tensor output of the
last convolutional layer.
- `avg` means that global average pooling
will be applied to the output of the
last convolutional layer, and thus
the output of the model will be a 2D tensor.
- `max` means that global max pooling will
be applied.
classes: optional number of classes to classify images
into, only to be specified if `include_top` is True, and
if no `weights` argument is specified.
# Returns
A Keras model instance.
# Raises
ValueError: in case of invalid argument for `weights`,
or invalid input shape.
vgg16 = VGG16(include_top=True, weights='imagenet')
Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-4-622c1ff23a67> in <module>()
----> 1 vgg16 = VGG16(include_top=True, weights='imagenet')
/home/z/anaconda2/lib/python2.7/site-packages/keras/applications/vgg16.pyc in VGG16(include_top, weights, input_tensor, input_shape, pooling, classes)
162 weights_path = get_file('vgg16_weights_tf_dim_ordering_tf_kernels.h5',
163 WEIGHTS_PATH,
--> 164 cache_subdir='models')
165 else:
166 weights_path = get_file('vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5',
/home/z/anaconda2/lib/python2.7/site-packages/keras/utils/data_utils.pyc in get_file(fname, origin, untar, md5_hash, file_hash, cache_subdir, hash_algorithm, extract, archive_format, cache_dir)
201 functools.partial(dl_progress, progbar=progbar))
202 except URLError as e:
--> 203 raise Exception(error_msg.format(origin, e.errno, e.reason))
204 except HTTPError as e:
205 raise Exception(error_msg.format(origin, e.code, e.msg))
Exception: URL fetch failure on https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5: None -- [Errno 110] Connection timed out
from keras.utils.vis_utils import plot_model
from IPython.display import Image
plot_model(model, to_file="vgg16.png", show_shapes=True)
Image('vgg16.png')
If you’re wondering where this HDF5
files with weights is stored, please take a look at ~/.keras/models/
HandsOn VGG16 - Pre-trained Weights
IMAGENET_FOLDER = 'imgs/imagenet' #in the repo
!ls imgs/imagenet
apricot_565.jpeg apricot_787.jpeg strawberry_1174.jpeg
apricot_696.jpeg strawberry_1157.jpeg strawberry_1189.jpeg
from keras.preprocessing import image
import numpy as np
img_path = os.path.join(IMAGENET_FOLDER, 'strawberry_1157.jpeg')
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
print('Input image shape:', x.shape)
preds = vgg16.predict(x)
print('Predicted:', decode_predictions(preds))
('Input image shape:', (1, 224, 224, 3))
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-7-49458049ff08> in <module>()
9 print('Input image shape:', x.shape)
10
---> 11 preds = vgg16.predict(x)
12 print('Predicted:', decode_predictions(preds))
NameError: name 'vgg16' is not defined
img_path = os.path.join(IMAGENET_FOLDER, 'apricot_696.jpeg')
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
print('Input image shape:', x.shape)
preds = vgg16.predict(x)
print('Predicted:', decode_predictions(preds))
Input image shape: (1, 224, 224, 3)
Predicted: [[('n07747607', 'orange', 0.87526792), ('n07749582', 'lemon', 0.03620464), ('n07717556', 'butternut_squash', 0.021843448), ('n03937543', 'pill_bottle', 0.0126132), ('n03942813', 'ping-pong_ball', 0.0054204506)]]
img_path = os.path.join(IMAGENET_FOLDER, 'apricot_565.jpeg')
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
print('Input image shape:', x.shape)
preds = vgg16.predict(x)
print('Predicted:', decode_predictions(preds))
Input image shape: (1, 224, 224, 3)
Predicted: [[('n07718472', 'cucumber', 0.29338178), ('n07716358', 'zucchini', 0.2383192), ('n04596742', 'wok', 0.042132568), ('n07716906', 'spaghetti_squash', 0.038422), ('n07711569', 'mashed_potato', 0.036552209)]]
Hands On:
Try to do the same with VGG19 Model
# from keras.applications import VGG19
Residual Networks
ResNet 50
## from keras.applications import ...


Honzi/Bookmarks/Honzifox's EVE/Proteus PROWL-0
- Used for: cloaky amarr undock camping.
- Base Fitting: PROTEUS-UNDOCK
- Killmarks: 19
- Skin: Kopis Edge
- Subsystem Bay:
- Proteus Core - Friction Extension Processor
- Proteus Defensive - Augmented Plating
- Proteus Offensive - Support Processor
- Abyssal modules will never be used because they are worthless on zkill.


Unfortunately we are unable to process your request. You could start the form again, have a look through leeds.gov.uk or contact us for further help.
{% extends "layout_multi_sections-forms.html" %} {% block page_title %} Unable to process your request - Leeds City Council {% endblock %} {% block css_register %} {% endblock %} {% block service_start_page %} /forms/phrc/start-page {% endblock %} {% block service_name %} Register to join the Public Health Resource Centre {% endblock %} {% block header %} We are unable to process your request {% endblock%} {% block sectionOneTop %} {% endblock %} {% block sectionOneFull%} {% endblock %} {% block breadcrumb %} {% endblock %} {% block sectionOneContent %}
Unfortunately we are unable to process your request. You could start the form again, have a look through leeds.gov.uk or contact us for further help.


IN PICTURES | Strong winds tear through Cape Town
by Esa Alexander
Residents of Cape Town woke up to a different kind of city on Saturday as strong winds tore through the CBD.
Sunday Times photographer Esa Alexander was there to capture Capetonians struggling with the weather conditions.
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| For No Good Reason a film about Ralph Steadman. Johnny Depp guides the visually stunning journey, smashing narrative conventions, moving seamlessly from interview to animation and in the finest Gonzo tradition questions of witness and authenticity are challenged. Steadman's art is for the first time animated, including illustrations from Hunter S Thompson's Fear and Loathing in Las Vagas. Featuring Richard E Grant, Terry Gilliam, Bruce Robinson and with music from Slash, The All American Rejects, Jason Mraz, Crystal Castles, Ed Hardcourt and Beth Orton. A touching and at times funny film about honesty, friendship and the ambition driving an artist. This is a true record of the demise of the 20th Century counterculture and hipster dream with Ralph Steadman the last of the Gonzo visionaries. | |
| Genres: | Documentary, Biography, History, Music |
| Director: | Charlie Paul |
| Writer: | Cast: | Himself - Ralph Steadman Himself - Johnny Depp Himself - Hunter S. Thompson Himself - Terry Gilliam Himself - Richard E. Grant Himself - Jann Wenner Himself - Hal Willner Himself - Francis Bacon Himself - William S. Burroughs Leonardo DaVinci - Patrick Godfrey Himself - Warren Hinckle Himself - Richard Nixon Himself - Laurence Olivier Himself - Joe Petro Himself - Pablo Picasso |


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segments (optional) - cone detail. Defaults to 8.
solid (optional) - true for a cone with a base, false for a cone without a base. Defaults to true. parent (optional) - parent entity of cone |
|
Creates a cone mesh/entity and returns its handle.
The cone will be centred at 0,0,0 and the base of the cone will have a radius of 1. The segments value must be in the range 3-100 inclusive, although this is only checked in debug mode. A common mistake is to leave debug mode off and specify the parent parameter (usually an eight digit memory address) in the place of the segments value. As the amount of polygons used to create a cone is exponentially proportional to the segments value, this will result in Blitz trying to create a cone with unimaginable amounts of polygons! Depending on how unlucky you are, your computer will then crash. Example segments values (solid=true): 4: 6 polygons - a pyramid 8: 14 polygons - bare minimum amount of polygons for a cone 16: 30 polygons - smooth cone at medium-high distances 32: 62 polygons - smooth cone at close distances The optional parent parameter allow you to specify a parent entity for the cone so that when the parent is moved the child cone will move with it. However, this relationship is one way; applying movement commands to the child will not affect the parent. Specifying a parent entity will still result in the cone being created at position 0,0,0 rather than at the parent entity's position. See also: CreateCube, CreateSphere, CreateCylinder. |
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; CreateCone Example
; ------------------ Graphics3D 640,480 SetBuffer BackBuffer() camera=CreateCamera() light=CreateLight() RotateEntity light,90,0,0 ; Create cone cone=CreateCone() PositionEntity cone,0,0,5 While Not KeyDown( 1 ) RenderWorld Flip Wend End |


My Favorite Places
These are a few of my
favorite
places to visit!
Anywhere with a
beach
! Some favorites include
Newport Beach, CA
Pfeiffer Beach in Big Sur, CA
National Parks
Seattle, WA
San Francisco, CA


Model of a tank that is open to the environment at the fixed
pressure p_ambient
. The tank is filled with a single
or multiple-substance liquid, assumed to have uniform temperature
and mass fractions.
At the top of the tank over the maximal fill level height a vector of FluidPorts, called topPorts, is present. The assumption is made that fluid flows always in to the tank via these ports (and never back in to the connector).
The vector of connectors ports are fluid ports at the bottom and side of the tank at a definable height. Fluid can flow either out of or in to this port. The fluid level of the tank may be below one of these ports. This case is approximated by introducing a large pressure flow coefficient so that the mass flow rate through this port is very small in this case.
If the tank starts to over flow (i.e., level > height), an assertion is triggered.
When the diagram layer is open in the plot environment, the level of the tank is dynamically visualized. Note, the speed of the diagram animation in Dymola can be set via command animationSpeed(), e.g., animationSpeed(speed = 10)
| Name | Description |
|---|---|
| HeatTransfer |