JPH05324845A - Graph generating device - Google Patents

Abstract

PURPOSE:To output a graph on which variation of data can be recognized most easily by checking the variance state of the data and optimizing a scale when the graph is displayed. CONSTITUTION:The data are obtained from an input device 1 through a graph data input means 3 under the control of a control part 10 and an optimization checking means 4 checks the necessity of optimization; when the optimization is necessary, a scale information generating means 5 generates scale information required for the optimization and a data converting means 7 converts the data according to the scale information. Then, a graph image generating means 8 generate a graph image according to the converted data and the scale- optimized graph is displayed on an output device 2 through a graph image output means 9.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a graph generating device, and more particularly to a graph generating device for outputting a graph by an electronic computer.

[0002]

2. Description of the Related Art A conventional technique will be described with reference to the example shown in FIG.

For example, as shown in FIG.
When the input data of the number of beer sold in the store is output as a graph without performing the scale optimization process, the display scale of the graph is set based on the maximum value of data and 0, so the scale is 0 to 60,000. Up to 10000 steps (Fig. 7 (b): conventional graph). When there is not much variation in the data as in this case, the variation in the number of beers at each store displayed in the graph becomes small and it becomes impossible to visually recognize it.

[0004]

When input data having little variation is displayed as a graph as in the case of displaying the input data as a graph as described above, the fluctuation of the data cannot be visually recognized.

[0005]

A graph generation device of the present invention includes an input device for inputting data which is a basis for a user to output a graph, and an output device for outputting a graph.
Graph data input means that controls data input and acquires only the data necessary for graph output, optimization check means that checks the occurrence of scale optimization processing based on the input data, and scale Scale information generating means for generating optimized scale information when an optimization process occurs, an internal storage device for storing optimized scale information, and data based on the scale information stored in the internal storage device. Data conversion means for converting the data, graph image generation means for generating a graph image based on the converted data, graph image output means for controlling the output device to output a graph image,
It has a control unit that controls the work flow related to graph output, optimizes the scale when it is judged that the data group displayed in the graph has a unique value and it is better to perform the scale optimization process visually. It is characterized by displaying.

[0006]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Next, the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing an embodiment of the present invention. This embodiment comprises two external devices, an input device 1 for a user to input data and an output device 2 for outputting a graph, and a scale optimization graph generation device 11.

If the user receives a graph output instruction,
The control unit 10 of the scale optimization graph generation device 11 calls the graph data input means 3, and the user inputs the input device 1
Data required for graph output is extracted from the data input from, and the extracted data is passed to the optimization checking means 4, data validity check and data variation check are performed, and scale optimization processing is required. Or not. Next, the control unit 10 passes the input data as it is to the graph image generating unit 8 if the scale optimizing process is not necessary, and calls the scale information generating unit 5 if the scale optimizing process is necessary and requires it for the scale optimizing. The scale information is generated and written in the internal storage device 6, and then the data conversion means 7 is called to perform the data conversion work based on the information in the internal storage device 6,
The converted data is passed to the graph image generation device 8. In the graph image generation device 8, the output device 2 is based on the data.
Generate a graph image with the code to output the graph with.

Finally, the control section 10 calls the graph output means 9 and actually outputs the graph to the output device 2 based on the graph image generated by the graph image generation means 8.

FIG. 2 is a flowchart of the control unit 10, which will be described. First, the graph data input means (step 21) is used to acquire data for graph output, and the data is sorted in descending order (step 22).
Based on this data, the necessity of scale optimization processing is checked (step 23), and the flow of processing changes depending on the necessity of scale optimization processing (step 24).
If scale optimization processing is required, scale information generation means (step 25) and data conversion means (step 2)
6), the graph image generating means (step 27) is processed in this order, and if the scale optimization processing is not necessary, only the graph image generating means (step 28) is executed. Since the creation of the graph image to be output at this point has been completed, the graph output means (step 29) is executed and the process is ended.

FIG. 3 is a flow chart for explaining the process of the optimization check (step 23) in FIG. 2, and the operation thereof will be described.

Based on the first data (maximum value of data) and 0 of the data sorted in descending order, the minimum value of the scale
The maximum value / incremental value is calculated (step 31), and all the data are sorted into each class based on the calculated scale minimum value / maximum value / incremental value (step 3).
2).

For example, in the case of the input data shown in FIG. 7, the classification is as follows.

Class 1 (0 to 10000), Class 2 (10000 to 20000), Class 3 (2000 to 30000), Class 4 (30000 to 40000), Class 5 (40000 to 50000), Class 6 (50000 to 60000) Therefore, if all data are distributed to each class, they will concentrate on class 6.

Next, as a result of the classification, it is judged whether or not all the data are concentrated within three consecutive classes (step 33). If they are concentrated, the scale optimization flag is set to ON ( If the step 34) is not concentrated, the scale optimization flag is set to OFF (step 3).
Set 5) and finish.

FIG. 4 is a flow chart for explaining the processing of the scale information generating step 25 of FIG. 2, and the operation thereof will be described.

The first data (maximum value of data) and the last data (minimum value of data) of the data sorted in descending order.
The minimum / maximum / increment value of the scale is calculated based on the above (step 51), and the calculated minimum / maximum / increment value of the scale is written to the internal storage device (step 52).
finish.

FIG. 5 is a flow chart for explaining the processing of the data conversion step 26 of FIG. 2, and the operation thereof will be described.

The scale information is read from the internal storage device (step 61), the data is converted according to the scale information (step 62), and the converted data is written to the internal storage device (step 63).

FIG. 6 is a diagram showing an optimized grab according to this embodiment and corresponds to FIG. 7 (b).

[0020]

As described above, according to the present invention, the scale optimization graph is displayed when it is visually better to optimize the scale depending on the variation condition of the data set by the user. This has the effect that fluctuations are most easily recognized.

Moreover, since the present apparatus recognizes the data variation situation and performs the scale optimization division, the user can output a visually optimized graph without being aware of the data value.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing an embodiment of the present invention.

FIG. 2 is a flowchart illustrating an operation of a control unit in FIG.

FIG. 3 is a flowchart illustrating an optimization check operation in FIG.

FIG. 4 is a flowchart illustrating a scale information generation operation in FIG.

5 is a flowchart illustrating a data conversion operation in FIG.

FIG. 6 shows an optimized grab according to this embodiment.

FIG. 7A is a diagram showing input data, and FIG. 7B is a diagram showing a graph created by a conventional example.

[Explanation of symbols]

 1 Input Device 2 Output Device 3 Graph Data Input Means 4 Optimization Checking Means 5 Scale Information Generating Means 6 Internal Storage Device 7 Data Changing Means 8 Graph Image Generating Means 9 Graph Image Output Means 10 Controller 11 Scale Optimization Graph Generating Means

Claims (3)

[Claims] 1. An input device for inputting data as a basis for a user to output a graph, an output device for outputting a graph, and a data input control so that only data necessary for graph output is acquired. Graph data input means to perform, optimization check means to check the occurrence of scale optimization processing based on the input data, and scale information to generate optimized scale information when scale optimization processing occurs A generation unit, an internal storage device that stores optimized scale information, a data conversion unit that converts data based on the scale information stored in the internal storage device, and a conversion unit that stores the converted data. A graph image generating means for generating a graph image, a graph image outputting means for controlling the output of the graph image to the output device, and a graph outputting means. Equipped with a control unit that controls the work flow related to force, when the data group displayed in the graph is a unique value and it is judged that it is better to perform scale optimization visually, the scale is optimized and displayed. A graph generation device characterized by: 2. The control unit first obtains data for graph output, sorts the data in descending order, checks the necessity of scale optimization processing based on this data, and performs scale optimization. The scale information generating means, the data converting means, and the graph image generating means are processed in this order if processing is necessary, and only the graph image generating means is executed if scale optimization processing is not necessary. Graph generator. 3. In the necessity check of the optimization process, the minimum value, the maximum value, and the increment value of the scale are calculated based on the first data of the data sorted in descending order and 0. 3. The graph generating apparatus according to claim 2, wherein all data are sorted into each class based on the minimum value, the maximum value, and the increment value of the scale.